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					            1 Jun 2012 modify Calculator row 12 by inserting IF row 3 = 0,0; that way row 12 has the net markers reduced for zeros in the m
                       In the mutation array, change IF row 3 = 0 to IF row 12 = 0; that speeds up calculation by avoiding the ABS function
            29 Apr 2012 change Total column to CO; add macro Ctrl J to jump to CO9
            1 Sep 2011 minor correction in the formula in Calculator cell L12
            Type Documentation                  17 Oct 2010           Peter Gwozdz
Remember to save a backup of this master copy; if you make changes say so right here at the top
It's a good idea to make a separate copy of this file for each "type" analyzed
            Documentation sheets can be deleted in the copies
            Right click on a tab below
Do not cut & paste
            Use copy & paste instead
            Cut & paste may screw up the formulae
            OK to delete data
                       Be careful about deleting rows & column within a sheet; that might screw up the formulae
            If you know what you are doing, cut & paste may be used in some places
The "Calculator" sheet figures mutations for all samples in the database below row 13
            Compared to the comparison haplotype typed or copied into row 3
            The "Calculator" displays the mutation step distance for each sample in the "Total", column CI
Another file "Calculator.xls" has:
            A "Documentation" sheet including detailed instructions for use of a Calculator sheet
            Optional versions of the Calculator, on separate sheets, with formulae that can be copied into this file
            Documentation of the mutation formulae in the Calculator
            Tips for copying, pasting, sorting
            "Mask" explanation (row 12 in that file, rows 10-12 here) and more useful masks
            And more
This version of the Calculator by default is compatible with Ysearch (www.ysearch.org)
            "Total" is what Ysearch calls "Genetic Distance"
            "Total" is what I also call "step" or "count"
            The Calculator has rare small differences compared to Ysearch
                       Explained in the Documentation sheet of Calculator.xls
            Explained below are options that may cause significant differences compared to Ysearch
See the sheet "SBP Doc" for Documentation regarding Statistical Background Percent
See the sheet "ASP Doc" for Documentation regarding Average Square Distance
A brief "warm up" introduction to the "Calculator" sheet:
            Consider saving a working copy of this master file with a name like "TypeTest" to avoid an unintended change
            Notice the 45 in cell CI8 of the Calculator sheet
                       That means the best ranked 45 markers are being considered
                                   Ranking is done on the TypeRank sheet, row 18
                                               And copied to the Calculator sheet, row 11
                                   Notice at the top of column CI that 46 markers are ranked
                                               That's because two markers are tied at rank 45
                                                           See row 11, columns A and BK
                                   Notice the 42 at "Net Markers" at cell CI13
                                               That's because 4 compound markers, although ranked better than 45, are not being used
                                                           For technical reasons, explained below
                       The zeros in row 10 (the net mask) show which markers are not being used
                       Column CI, the "Total" column below row 13, is the step data (genetic distance) using only these best 42 markers
                                   Notice that column CB is where I made a copy of this data, and I added color and boldface, as an example
                                               Those 10 samples represent what I have been calling "P type" since 2007
                                               Notice cell CB12 (copy of cell CI12), SBP of 7.0% for these 42 markers
                                               Lower SBP means better fit, and also means better probability that this cluster of data represent
            Overtype the number in CI8
                        Try 23; notice that the column labeled CG is my copy of the Total column using 23 best ranked markers
                        Look at the top of column CI
                                    Notice the suggestion that you change the cutoff and gap to 2 and 5
                                                It makes sense that the cutoff should be smaller using only 23 markers
            No not type in the blue cells; these are formulae showing you calculated results
                        Type only in those 3 red cells, CI8, CI9, and CI10
            Overtype the red cutoff and gap to the suggested 2 and 5 values
                        Try other values, too
                        Notice that the SBP in the cell below gets recalculated
            Try 15, 5, 2 for those 3 red numbers: markers, cutoff, gap
                        Save the total column in one of the Results columns
            Ctrl i Macro Method to Save Results
                        A quick method to sort and save a column - a set of results
                        Press Ctrl i
                                    Press and hold the Ctrl key
                                    Press the I key (but not the shift capital key)
                                    Then release both keys
                        That runs the "TypeSort" macro that I wrote
                                    The macro will not run if you started this file with macros not allowed
                                    The macro is fast, but you might notice that the macro highlights all the data, sorts by column CI, and copi
                                    The macro finishes with the column CI data highlighted, because it just copied that to the clipboard
                        Use the left cursor to move 1 column to the left
                        Paste only the data; here is one way to do it:
                                    Press & release the Alt key if the menu bar is not visible
                                    Click on Edit, Paste Special, Values, OK
                                                (If you do a regular paste, the formulae get pasted, which comes out wrong.)
                        A copy of the results from column CI appears in your chosen column - CH in this example
            End of Ctrl i Macro method
                        You may delete such copy columns
                                    Highlight and press the Delete key
                                    (If you delete or insert columns, the macro won't work properly because the macro always sorts by column
            Close the file without saving these "warm up" changes
End of the "warm up" exercise
For examples of how to use this file, it might be helpful to look at my results
            For example: see PType.xls, NType.xls, Atype.xls, etc
                        Those are all copies of this file (with the "Documentation" sheets deleted) and with analysis for one type
            This master has only a small database from 2007
                        (the 40 R1a samples at 67 markers from the Polish Project)
It's a good idea to make a separate copy of this file for each "type" analyzed
For a new analysis, delete any unwanted notes
            "Notes" & "Results" columns are available in the center of the Calculator sheet
                        Columns BS to CH
                        These can be used for IDs
                        I like to use sequence numbers, so the database can be quickly resorted to my default order
                        Results from the "Total" column can be stored in these columns for comparisons of different results
            It's OK to copy over old notes
            Do not delete the actual columns, because then the "TypeSort" macro will not work properly
            Do not delete the blue cells
                        These are displays from the SBP sheet
            Careful about the labels in these Notes columns
                        Actually, you can delete these if you have other labels you prefer
Make sure there is room for your database
           Your database is a set samples - STR values by marker
           This file has room for only 40 samples
           If you have more than 40, use a copy of Type500.xls
                       That file has room for 500 samples
                       It's easier to delete extra rows (instructions below) than adding rows
                       Type500.xls does not have the 3 "Doc" instruction sheets
                       Type500.xls does not have those two ADS sheets
                                    But you can move those two ASD sheets into Type500.xls
                                                Moving instructions are in ASD Doc
           If you have more than 500, there are instructions below for adding more rows
                       Search for "Add rows to calculator"
Copy your database into the Calculator sheet below row 13
           OK to paste over old data
           Row 13 has DYS labels
                       Make sure your data is consistent
                       See Calculator.xls for instructions on how to change markers
                                    Those 3 columns on the far right, 464 e, f, g, are sometimes useful, but not required
Delete extra rows
           Delete all the extra rows at the bottom, below your new database
           Only deleting the data is not sufficient
                       Because then the SBP sheet will use the zeros from the empty rows
           Deleting the data and the formulae in those extra rows will work
                       but then it's irritating when you jump to the bottom of the Calculator and see blank rows
           Any Excel method for deleting rows is OK
           Here is one method:
                       Right after pasting in the new data
                                    While the new data is still highlighted
                                    Use the vertical scroll bar to find the bottom of the data
                       Click anywhere on the row just below your data
                       Press and hold Shift
                       Press Ctrl End and release (still holding shift)
                       Press the space bar to highlight all those rows below your data
                       Release Shift
                       Press & release the Alt key
                       Click "Edit, Delete" (do not use the Delete key)
                                    The file is now smaller, without all those extra rows of formulae
                       "File, Save"
The database rows may be sorted
           Do not sort columns unless you really understand what you are doing
           Any number of rows can be sorted, or all of them (Calculator below row 13)
                       Do not sort above row 14
           Be sure to highlight everything in each of the rows being sorted, including any Results columns to the right
                       Actually, the formulae, starting at the "Total" column, do not need to be sorted
                       But it is usually easiest to hold Shift and press Ctrl End to highlight everything, including the formulae
           Sorting rows can be done by any columns - by "Total", by any sequence of markers, or by copies of Results, or whatever
           More sorting tips are in Calculator.xls
Discovering new clusters
           "Cluster" means a subset of data (samples - rows in the database) that seem to be very similar in STR values
           I won't go into the art of discovering clusters in this documentation
                       This Excel tool is for validation of your proposed clusters
                       Usually a starting "signature" haplotype consists of a few marker values that are correlated (quite a few samples have
                       All you need to start here is a signature that you think may produce a reasonable cluster
                      A 3 to 5 marker "signature" may work well for a 1st try
          Usually, a cluster is a hypothetical haplogroup (a hypothetical clade)
                      But you can use this file to analyze any cluster
                      You can use this file to analyze a known haplogroup
                                  Considering the haplogroup data as a cluster within the parent haplogroup
New cluster initiation
          This brief section is for a new cluster analysis
          For a well established cluster with a known modal, skip this section
                      "Modal" is short for modal haplotype; most common value for each marker
          Start with a few good "signature" marker values
                      Do not use all 67 markers
                                  Use a "signature" modal with only a few markers
                                  Only 3 markers may be enough
                                  10 markers is usually too many for a first try
                      Type or copy the signature markers into row 3 of the Calculator
                                  Use blanks for most of the cells; OK to delete the previous data in row 3 of the Calculator
                      Type 67 into cell CI8
                                  In order to ignore the "TypeRank" sheet for this first try
                                  And to capture all your signature markers
                                  Don't worry; the calculator ignores markers with blanks in the modal
                                  Don't worry about a previous cluster in the TypeRank sheet - it's ignored with 67 in cell CI8
          No need to change the row 10 mask from my default values; but there needs to be a set of numbers in that row
                      There needs to be a number in the mask of row 10 for each of your signature markers
          Sort the calculator by the "Total" column
                      The Ctrl i macro will do this - instructions above
                                  Ignore the cutoff, gap and SBP values for now
                                  No need to save this first try, but you may save if you wish
                                              Instructions are above with the Ctrl i instructions
          The best samples, at the top of the sort, with lowest "Total", are the first choice as the cluster for the type
                      Usually, only the samples with total 0 are needed for the first cluster attempt
                      For a signature with many markers and few with 0 total, you should also consider total 1 and perhaps 2
                                  Use your judgment
End of new cluster initiation
Copy your cluster into the TypeRank sheet
          Use Ctrl i to sort the cluster to the top of the database, just below row 13 of the calculator
          Decide which samples at the top should be the cluster
          If more than 100 samples in the cluster data, range needs to be extended in TypeRank
                      Before copying
                      Instructions are below; search for "Add rows to TypeRank"
          Row 20 has DYS labels in TypeRank
                      Same labels as row 13 of Calculator
          Copy from the top of the database, just below row 13 of the Calculator sheet
          Paste just below row 20 of the TypeRank sheet
          Detailed instructions; one way to do the copy & paste:
                      Highlight the data for copying:
                                  Click on the Calculator sheet tab
                                  Click on A14
                                  Hold down the shift key
                                  Use the scroll bars to find the last column of data for the last row for copying
                                  Click on that last cell to finish the highlight
                                  Release the shift key
                      Edit, Copy
                      Click on the tab for the TypeRank sheet for receiving this data
                      Click on A21
                      Edit, Paste
          Option: you can copy IDs and Results over to the right
                      The TypeRank sheet does not use the IDs & Results, but it may be useful to you as notes
          Careful: do not paste over column DE
                      It's a column over to the far right in TypeRank
                      This calculation column is needed for DYS389-2
          OK to overcopy previous Type data
          If the type data has fewer rows than the previous type data
                      Be sure to delete the old data below the new copy
                      One way to delete data:
                                   Highlight the data and press the Delete key
                      Detailed instructions for one safe way to delete old data below a new smaller cluster:
                                   Right after copy and paste of the new cluster, when the new data is still highlighted:
                                   Use the vertical scroll bar if needed to see the bottom of the highlighted new cluster
                                   Use the horizontal scroll bar if needed so see column A
                                   Click in column A in the row just below the highlighted new cluster
                                   Ctrl Shift End
                                               That highlights everything below, including DE
                                   Continue to hold the shift key
                                   Cursor arrow one left
                                               This removes the highlight from column DE
                                   Release the shift key
                                   Press the Delete key
                                               That deletes the old data
                                               (Do not delete the rows)
                      It's not a good idea to delete entire rows
                                   That would change the range of the formulae
          Suggestion (not required):
                      Look at the right side of the TypeRank sheet in this master of Type.xls
                      Notice that I copied extra stuff
                                   IDs; columns of results; extra results below the cluster
                      The way I did this:
                                   In Calculator, I started the copy highlight from cell A13
                                               That includes the DYS label row
                                                            And also includes the number or markers for each column of results
                                   In Calculator, I continued the highlight before copy well below the cluster
                                   I pasted into cell A20 of TypeRank
                                   I deleted from this new data only the data for the extra samples below the cluster
                                               But I left the IDs and results for those samples
                      You can add more notes to the right of the data
                      Notice those blue cells that show you the current number of markers from the Calculator
End of copying cluster into TypeRank sheet
Determine the full modal haplotype
          It is automatically calculated in row 5 of the TypeRank sheet
                      These are the most common values for each marker in the data that you just copied to the TypeRank sheet
                      All 70 markers, if you have them
                      Whatever number of markers you are using
          Copy from row 5, all the values
          Use "Edit, Paste Special, Values" to paste this modal haplotype into row 3 of the Calculator
                      That pastes only the values, not the MODE formulae from row 5
Cluster improvement
          Use more markers
          Make sure row 3 of the Calculator has a full modal (previous topic)
          Type a number into Calculator cell CI8
                     A number larger than your initial number of markers
                                  12 might work fine for a cluster from a relatively old clade
                                  30 to 50 might work better for a cluster due to a very young clade
                     Continue to ignore the cutoff, gap, and SBP values for now
          Resort the Calculator data by "Total", same as before, using Ctrl i
                     Use your judgment to decide if the data sorted to the top looks better than the first cluster data
                     Take a look at the graph, in the SBP sheet
                     If a new cluster looks better, copy this new better data from the top of the Calculator to the TypeRank sheet
                                  Same as before
                     More comments are coming below on how to judge a good cluster
          Check the modal haplotype
                     Row 5 on the TypeRank sheet
                     It may have changed, with the new data
                     Row 3 on the TypeRank sheet is a copy from row 3 on the Calculator
                     If necessary, modify the modal on row 3 of the Calculator
                                  Do not modify row 3 of the TypeRank sheet
                                            These are formulae that copy row 3 from the Calculator, for your information
                                                        Same with row 3 on the "Haplotypes & Masks" sheets
                     The Calculator will not use a new modal from the TypeRank sheet
                     You need to type or copy your changes onto row 3 of the Calculator
                     Use "Paste Special, Values" when copying formula results to row 3 Calculator
          Look for a better cluster
                     Try different numbers in CI8 for the number of markers
                     It may help to use Ctrl i to save columns of results, as explained above
                     Each time you change the cluster in the TypeRank sheet, the modal may need adjustment again
                                  The rank may change
                                            So the saved columns of results may not be the same for the same number of markers
                                            You may need to redo all those saved columns whenever the cluster data is changed in the Type
          Remember to save backup copies from time to time
          Do not spend too much time on this, because I have lots of tips below
                     But first, read the "SBP Doc" sheet for an explanation of the SBP sheet
                     And read the following topic about masks
                     You need to at least generally understand those two topics to follow my tips below
End of Cluster Improvement
Mask Discussion
          Use a mask in row 10 of the Calculator to avoid the tedium of typing in marker changes
          As explained in the Calculator.xls Documentation, the mask restricts calculation to those columns with a number in row 10
                     Also, that number is used as the maximum mutation step at that marker
                     Except Calculator.xls has the mask in row 12
                                  Here, do not type a number into Calculator rows 11 or 12 - that removes the formulae
                                            Some of these are unique formulae, explained below
          Save useful masks in the "Haplotypes & Masks" sheet for copying to row 10
          This master has a useful 67 marker mask by default in row 10
                     There is a copy at the bottom of the Haplotypes & Masks sheet
          More masks are available in the "Masks" sheet of Calculator.xls
          OK to type experimental changes into row 10
          Row 12 is the actual mask used by the calculator
          Row 11 has a ranking of the best ranked markers from the TypeRank sheet
            You specify the number of markers in cell CI8
            Row 12 uses only the best ranked makers; zero for the others
            The Calculator actually looks at row 12, and ignores those columns with a zero in row 12
                        And uses the number in row 12 as a maximum step mutation count at that marker
Later, if you find that a particular marker causes problems
            You can type a zero in the mask, row 10, at that column
                        And that marker will not be used, regardless of rank
            Or you can type a small number into that column at row 10, to limit the mutation count
                        A 1 in row 10 is equivalent to what people call the "infinite alleles model"
Later, if you find that a particular marker works very well to define the type, but is not ranked well:
            You can force a marker to be used:
            Use a negative number in row 10 for the marker
            That bypasses the rank selection; that negative number is converted to a positive number in row 12 for use by the calc
By default, the Calculator produces the same "Total" genetic distance as Ysearch (www.Ysearch.org)
            Ysearch does not allow disregarding selected markers
                        Ysearch does allow a signature or definition with selected markers
                                    But values need to be added or removed to change markers
            Ysearch does not provide for limiting the count by marker
            Ysearch methods are explained in more detail in the Documentation sheet for Calculator.xls
Three compound markers have complications:
                        389-2, YCAII, and 464
                        Compound markers are explained in the Documentation sheet for Calculator.xls
            389-2: Normally, when 389-2 is used, 389-1 is also used, to be compatible with Ysearch
                        Ysearch does not allow a definition or signature with only 389-2
                                    If 389-1 is blank on Ysearch, a value for 389-2 is ignored
                        So my default formula for the 389-2 mask in row 12 of this Calculator checks the ranking of both 389-1 an
                                    389-1 can be ranked and used by itself
                                    389-2 is normally used only if both 389 markers are ranked well (both rank not more than the m
                        A negative value in row 10 for 389-2, cell L10, forces that corresponding positive value into row 12, cell L
                                    So in this case 389-2 is used regardless of the ranking of either marker
                                    So if 389-2 is well ranked but 389-1 is not the definition would not be compatible with Ysearch
                                    Using a negative value in row 10 for both markers can force them both to be used, compatible w
                                    Your choice
            YCAII: I abbreviate YCa and YCb to mean YCAIIa and YCAIIb
                        Normally, this pair is evaluated following the Ysearch method:
                                    This pair of markers is evaluated together, and the result is in the "a" column DL; the "b" colum
                                    This Ysearch method uses infinite alleles - one count for each marker that does not match in the
                                                Result can be 0, 1, or 2 for the pair
                                                0 if either marker is blank in either haplotype
                                    So normally a mask value in row 10 above YCa (cell AB10) greater than 2 has no effect
                                                My formula in row 12 truncates the mask value to 2 for YCa
                                                            And a 1 for YCb to let you know it is being used
                                                                        And to be sure it is used in the definition modal (see the "Hapl
                                                                        The mask input value in row 10 above YCb is ignored (norma
                                    If YCa mask is 0 in row 10 then both markers get 0 in row 12 and YCAII is not evaluated
                                    If YCa mask is 1 in row 10 then the result in DL is truncated to 1
                                                That means the result is 1 if either or both markers do not match
                                    All this works only if both markers of the pair are well ranked (both rank not larger than cell CI
                                                If either marker is not well ranked then both get 0 in row 12 for the effective mask
                                                            And of course YCAII is not evaluated
                                    A negative value in row 10 for YCa:
                                                Forces YCAII to be evaluated as a pair regardless of the rank of either
                                Still using the normal Ysearch infinite alleles method
                                Again with the mask row 10 truncated to 2
        A zero in row 9 above YCa, cell AB9, means this normal Ysearch method is used
                    A blank in row 9 works same as a zero
        Row 9: You can enter any value other than 0 or blank in row 9 above YCa - that means both markers are t
                    The standard way most markers are treated, including the other a, b, compound pairs
                    Step is absolute value of the difference in STR value for the haplotypes being compared at eithe
                                But only if that marker is well ranked (not greater than CI8)
                                Truncated to your maximum for that marker in row 10
                                0 if either haplotype is blank at that marker
                    Negative value in row 10 forces that marker to be used
                    A 0 for either in row 10 means the mask will be 0 in row 12 so that marker will effectively not b
                                The other one is still active (unless it also has 0)
                    Text works as a non-zero value in cell AB9
                                Careful - a space is invisible but works like a non-zero value
DYS464: I abbreviate just 464
        This topic for 464 is written in a style very similar to YCAII, above
                    It is more complicated because there are 7 markers in the set
        Normally, this set is evaluated following the Ysearch method:
                    This Ysearch method uses infinite alleles - one count for each marker that does not match in the
                                Including 464 e, f, g; which the Calculator has on the far right
                                Result can be 0 to 7
                                Result is 0 if any of the a through d markers is blank in either haplotype
                                I wrote the function "Ys" to evaluate 464 using the Ysearch method
                                             The function will not work if you start this file with functions not allowed
                                             To avoid multiple calls to the Ys function, the function is called only onc
                    This set of markers is evaluated as a set, and the result is in the "a" column, DF
                                The other columns have a zero in the corresponding step columns at the right for mu
                                             Including e, f, g, on the very far right
                    So normally a mask value in row 10 above 464a (cell V10) greater than 7 has no effect
                                My formula in row 12 truncates the mask value to 7 for 464a
                                             And a 1 for all the other markers to let you know they are being used
                                                        And to be sure they are used in the definition modal (see the "H
                                                        The mask input values in row 10 above 464 b to g are ignored
                    If 464a mask is 0 in row 10 then all 464 markers get 0 in row 12 and 464 is not evaluated
                    If 464a mask is 1-6 in row 10 then that value is copied to row 12 and the result in DL is truncate
                    Ranking: all this is done only if all 4 markers 464 a to d are well ranked (each of the 4 not large
                                If any of the 4 are not well ranked then all 7 of the 464 markers get 0 in row 12 for th
                                             And of course 464 is not evaluated
                    A negative value in row 10 for 464a:
                                Forces 464 to be evaluated as a set regardless of ranking
                                Still using the normal Ysearch infinite alleles method
                                Again with mask 10 positive and truncated to 7
        A zero in row 9 above 464a, cell V9, means this normal Ysearch method is used
                    A blank in row 9 works same as a zero
        Row 9: You can enter any value other than 0 or blank in row 9 above 464a - that means all the 464 marke
                    The standard way most markers are treated
                    Step is absolute value of the difference in STR value for the haplotypes being compared at each
                                But only if that marker is well ranked (not greater than CI8)
                                Truncated to your maximum for that marker in row 10
                                0 if either haplotype is blank at that marker
                    Negative value in row 10 forces that marker to be used
                                              A 0 for any 464 marker in row 10 means the mask will be 0 in row 12 so that marker will effect
                                                         The other markers in the 464 set are still active (except those that also have a 0)
                                              Text works as a non-zero value in cell AB9
                                                         Careful - a space is invisible but works like a non-zero value
                                 464 e, f, g, are not counted in the "Net Markers"
                                              Your modal may have values at these markers
                                              They should work as expected
End of mask discussion
Determine a good definition for your type
           This is the main purpose of this "Type.xls" analysis file
           Follow the instructions of "Cluster Improvement" above
           Except now you vary all 3 of those red input numbers at CI8, CI9, CI10
                       Number of Markers to Consider, Cutoff, Gap
           Also, adjust the modal
           Use the mask on row 10 to add & remove markers
                       And to see the effect on SBP
           In general, a lower SBP means a better definition of a cluster
                       A cluster must have SBP < 50% to be seriously considered as a "type"
                                   All types have a cluster, but not all clusters represent a type
                       A type with SBP < 20% is likely to represent a clade, or future haplogroup
                                   SBP is not the same as probability that a type is a clade
                                                See the SBP doc sheet
           The goal is to find the lowest possible SBP
                       I don't have a strict algorithm to find the lowest SBP
                       Don't worry about a "true" lowest SBP
                       You need to try several definitions
                                   Until you are satisfied that you spent enough analysis time to find a good definition
           A "Definition" is:
                       Specified modal (specified set of markers and STR values for each)
                                   That's not necessarily the number you type into CI8
                                   It's the net markers after you adjust the mask in row 10
                       with specified Cutoff and Gap
                       for a satisfactory low SBP
           Use the largest number of markers for the definition when a range of marker numbers provide the same SBP
           Example, column CB in this Type.xls master (if you have not changed it)
                       Definition in boldface; this is what I have been calling "P type" since 2007
                       40 markers in this example, 10 samples, SBP = 7.0%
                       The modal definition is on row 6 of the sheet "Haplotypes & Masks"
           Reminder: when you change to better cluster data in the TypeRank sheet:
                       Reconsider the modal (instructions are above in "Cluster Improvement")
                       You may need to redo any saved columns of results on the Calculator sheet
                                   These may come out differently with different TypeRank data
                                                Because the ranking may change
           With experience, you'll gain the skill and intuition needed to find good definitions quickly
           I have lots of tips below on this sheet
End of determine good definition
Some tips by example:
           Careful not to save this master with the following changes
           Forcing an increase of one marker:
                       Change the 45 to 46 at CI8
                                   Notice that the net markers are still 42
                                   Because there is a tie at 45, row 11 columns A and BK
           Change to 47 at CI8
                      Now net markers jumps to 45
                      With automatic ranking, 43 and 44 do not come up
           Note which two markers were added
                      Columns G and AB
           Examine the step count results for those two makers on the right
                      Watch for G and AB in the formulae
                      Columns CQ and DL
           Column AB is YCa; changing the rank limit to 47 allowed both YCa and YCb to be used
                      As explained above
           Column G is DYS426, which has a mutation in one of the samples in the cluster
                      Look at the top of the database for column G
                                   It has an unusual mutation for one of the samples of the cluster toward the top
                      Notice the column CI total for that marker has increased from 3 to 4
                                   Increasing the suggested cutoff from 4 to 5
                                   With higher SBP - not as good a fit
           Type a 0 (zero) in cell G10, the mask for that marker, removing 426 from the definition
                      Now there are 44 net markers
                                   YCAII has been added
                      This is a better definition
           Conclusion: It's good to spend some time studying marginal markers
                      "Marginal" means those with ranking close to the maximum in CI8
                      Markers can be excluded or forced by changing the mask
End of forcing one marker example
464:
           Leave the 0 in the mask at G10
           Type -4 in V10
                      That's the mask for the entire 464 set
                      Notice your -4 is changed to 4 in row 12
                      Notice all the 464 markers have now been included in the row 10 mask
                      Net markers now 48
                      Change back and forth 4 to -4 if you missed it
                      But SBP had increased
           Examine the data for 464, top of columns V to Y
                      Notice that one of the cluster samples has all 4 values 16
                      That same sample has both 459 values 9 (columns N & O)
                      That same sample has both CD values 32 (columns AH & AI)
                      This is called recLOH
                                   Read the Wiki article about RecLOH for explanation
                      It's really only one mutation, but it gets a high count using these markers
           Change that -4 to -1 at V10
                      That limits the 464 to a count of one for the full set
                      Look at column CI (new Totals), compared to the saved CB (original good fit Totals)
                                   Notice the new suggestion
                                               Use it - type 5 for the cutoff
                                   The new result has the same SBP 7.0%
                                   Two of the cluster samples at total 3 increased to 4
                                   But all 3 of the next samples at previous total 8 increased to 9
                      This definition is better because it uses more markers
           Here is another way:
                      Change V10 back to 4
                                   Type a 1 in cell V9
                                               Actually, any number will work at V9, even text, just not 0 or blank
                                   Now there are 47 markers
                                               The 464 markers are treated as individuals
                                               464a does not rank, so it is not included
                                   SBP is still 7.0%
                      Either way, the total is not compatible with Ysearch
                      My choice in such a situation:
                                   Include 464 in the definition
                                   The SBP will not be optimum on Ysearch
                                   But that's only because the total comes out wrong for one person
                                   I'm confident the definition serves it's purpose better with 464 included
                                               Providing an indication to most men if their sample is likely to belong to the hypothetical clade
                                               The men with recLOH need to learn about what that means
                      All this is an example of an exception to a rule
                                   Sometimes the lowest SBP is not really the best definition
                                               Human judgment is needed
           End of 464 example
           Multiple minima
                      Restore the original version of this master
                      Change the 45 to 67 at CI8
                      Notice the suggestion at the top of column CI
                                   6, 6 for cutoff and gap
                                   Try these values in CI9 & CI10
                      Notice the suggestion changes
                                   Try it; yet another suggestion
                      The computer is having problems because we are too far off
                      Look at the graph in the SBP sheet
                                   Multiple minima
                                   Zero samples at various step values
                      We know there should be 10 samples in the mountain
                                   Because we found a best SBP with a mountain of 10, 42 markers
                                   The 16 cutoff comes closest
                                   So 16, 1 is the best choice for cutoff and gap in this case
                      However, 13, 4 give a lower SBP of 33%
                      With multiple minima, human judgment may be needed
                                   In this example, we know there should be 10 samples
                                   But if the best definition has multiple minima it may be difficult to decide which cutoff is best
                      That might mean there is not enough data yet
                                   Perhaps when more data accumulates the best minimum might be obvious
                                   Maybe not
                                               If there is a subclade located far from the main clade, the graph will have multiple minima even
           End of multiple minima example
           Careful not to save this master with changes
End of tips by example
Next come some more tips:
Suggestion from SBP sheet
           Blue cells at the top of column CI in the Calculator
           For the current number of markers:
                      Suggested Cutoff and Gap
                      SBP value for that suggestion
           To try these numbers, type them into the red input cells
          Use TypeRank recursively
                      Keep extracting better data to the TypeRank sheet
                      Until you are satisfied you have a good cluster for the type
          Remember; a human is really better than a computer in the final decision for what is a better fit
                      Look at the graph in the SBP sheet and decide for yourself
                      Read SBP Doc for more information
                      The computer is better at trying slight changes to your current cutoff and gap;
                                   and calculating SBP for each possibility
                                   and displaying the best
          My SBP sheet does not make big changes to your current input numbers
                      So if you are way off, there will not be a good suggestion
Consider adding data to your database in the Calculator sheet
          Usually, the parent haplogroup is a good database
          Ranking usually comes out better for a larger database
                      Because more data means more variation
                                   With little data, too many markers come out tied in rank
                                   With too little data, 1 or 2 unusual samples might give misleading ranking
          The database must be at least twice as large as the cluster
                      That means the Calculator sheet has a database (below row 13) with:
                                   The samples that are in the cluster (TypeRank sheet), of course
                                   Plus at least that many more
          A database 3 or 4 times larger than the cluster is usually even better
          SBP comes out with misleading results if the database is not at least twice the size of a proposed type cluster
                      Look at the graph in the SBP sheet
                      The far side of the graph always has a downward slope
                      Any proposed cutoff will produce a good SBP on that down slope
                                   But that is completely misleading
          A true mountain in haplospace must be isolated from the rest of the parent haplogroup
                      That means a gap in the upslope of the main mountain of the parent haplogroup
          If your database is too small:
                      That is, if you cluster is about half the size of your database or less
                      Consider adding data from the next higher level haplogroup
                                   And from brother haplogroups (parallel branches in the haplogroup tree)
Consider deleting the bottom of your database in the Calculator sheet
          Usually, the parent haplogroup is a good database
          Ranking comes out better if your database does not have lots of data that is genetically very distant from your cluster
          So if your cluster is much smaller than your database consider making the database smaller
          After you have a pretty good cluster defined in the TypeRank sheet
                      And a good number of markers being considered - cell CI8
          Sort by Total - Ctrl i
          Consider removing the worst fit samples, at the bottom of the Calculator
                      See above instructions; search for "Delete extra rows"
                                   Same instructions, this time to make the database smaller
Ranking does not really matter
          Because you get to choose markers by using zeros and negative numbers in the mask, row 10 of the Calculator
                      For better SBP
          A good ranking just means you do not need to adjust the mask as much
          A good ranking makes it easier to find a good "Definition" - which is the goal
          A good ranking makes it easier next time, when do another analysis with more data accumulated in your database
          Once you get a good definition, the ranking is no longer the important issue
TypeRank does not need to be the entire cluster
          "Entire cluster" for a type means all the samples in the mountain
                      All the samples with step less than the cutoff
                      From your database
          Usually ranking by TypeRank is best when the entire cluster is used
          Not always
                      Sometimes ranking gives good results more quickly with only the best samples in TypeRank
                      Those at the top of the sort in the Calculator by column CI (Ctrl i)
          See "Ranking does not really matter" above
An "infinite loop" is theoretically possible
          If you only follow the ranking, without modifying the mask
          That's unusual, but possible
          For example, cluster A might suggest that cluster B is a better cluster
                      And then when you put cluster B into TypeRank, that might suggest cluster A is better
          Or maybe an infinite loop going around several different clusters
          Don't worry about that
          You can break the loop by adjusting the mask
          Again, it does not really matter at the end of the analysis what is in the TypeRank sheet
          All that matters is your choice of "Definition"
Modal Comments
          "Modal" is short for modal haplotype - the most common value at each marker
          The full modal is always available in row 5 of the TypeRank sheet
          The definition modal is always available in row 6 of the Haplotypes & Masks sheet
          Excel function MODE
          Ties use the value that appears first in the list
          When considering the modal on the TypeRank sheet:
                      Row 3 has a copy of the current active modal from the Calculator sheet, row 3
                                  That's the one that is used for mutation count and for ranking
                      Row 5 has the new calculated modal from the data in the TypeRank sheet
                      Row 4 is a blank row, handy for making a new modal
                                  OK to copy a modal here on row 4, modify it, copy it somewhere else, delete it here - but do not use cut, d
                      Rows 6 & 7 have average and median
                      Row 8 highlights those markers that do not have the same value in all rows
                                  And displays how much the average differs from the current modal
          Small clusters can cause problems
                      The MODE function in row 5 of TypeRank gets confused if there is not a number with least 2 copies in that column b
                                  Feel free to type extra numbers below the TypeRank data to force a choice in columns having problems wi
          Option: you can start with a single haplotype in row 21 of the TypeRank sheet
                      I adjusted the MODE row so the value in row 21 is used if row 22 is blank
                      That way, you can try the modal haplotype by itself as the type, if you wish
                                  Be sure it matches row 3 of the Calculator, including blanks
                                  Be sure row 22 is blank
                      Or, you can force selected markers (columns) of the modal:
                                  Forced value in row 21
                                  Blank in row 22
                                  Data below row 22 is ignored at that marker
                      If not using this option, be sure row 22 is not blank
          When the modal is changed, stored data in the "Results" columns may need to be deleted and recalculated
                      Consider a backup sheet
                                  Instructions below at "TypeRank sheet copies"
          You do not need to change the modal if you think there is a statistical problem with the new value
                      But explain this if you publish, of course
          It is not necessary to keep changing a fast mutating marker
                      Markers with high "Rank", TypeRank sheet row 17
                                  High Rank number means not a good marker for this type
                     The CDy is an example of a rapid mutator
                     These may change rank often when a new cluster set is copied to the "TypeRank" sheet
                     These may change rank month-to-month as more samples are available in the Calculator sheet database
                     These changes in rank make minor changes in the stored "Results" columns of step counts
                     Such changes usually make no difference on which samples belong to the type mountain in the best fit definition
                                  It just looks funny when the data is recalculated, and comes out differently compared to saved columns wit
                     So it's silly to keep changing the poorly ranked rapid mutator modal values
         Sometimes a modal value need not be used
                     Example: look at column M in TypeRank in this master file (if it has not been changed)
                                  Marker 458
                                  Modal is 16
                                  5 of the 10 samples have the value 16
                                  But 4 of the 10 have the value 17
                                  This is data for what I call "P type" in 2007
                                  Over the years, as data accumulated, the modal switched between 16 and 17 at this marker
                                  Notice it is ranked 59 - it does not get used in a definition
                                              But sometimes a well ranked marker does this
                                  There is no need to keep changing the modal at this marker
                                  This is a "bimodal" marker
                                              There are probably two subclades with values 16 vs 17 in this P type example
                                                          But if so, the two clades do not form "types" with the STR data at 67 markers becaus
                                                                      At least not yet with the data available
                     Another example: column AJ
                                  Marker 442, 4 of 10 samples have the modal value 14
                                  But the other 6 samples have values 11, 12, and 13
                                  The average is 12.9 (column 6)
                                  The median is 13 (column 7)
                                  In this case, 13 is more representative than the modal 14
End of modal comments
Breadth
         "Breadth" is another figure of merit for a type; the larger the better
                     Range of marker number (range of "net" number of markers a few lines below CI8) that produce the same mountain c
                     The breadth range means not necessarily the same cutoff; not necessarily a low SBP
         Example: Calculator sheet: columns BY to CE
                     The same mountain with 37 to 64 markers
                                  This is a particularly good type
                     I highlighted the cluster in red for each column
                     Notice that I consider 64 markers to be within the breadth even though the best SBP at 64 gives one less sample at cut
                                  Because cutoff 14 provides the same samples as the definition
                     However, 65 markers has one sample out of sequence, so the same cluster as the definition cannot be extracted
         I like to define breadth with 10%
                     In other words, compared to a best marker set, with a particular "mountain number" of samples less than the cutoff,
                                  Another marker set is within the breadth if
                                              (missing + extra) sample number / mountain number < 10%
                                              Allow 1 (missing or extra) for 11 to 20 mountain number, 2 (missing plus extra) for 21 to 30, 3
         Notice that within this breadth example, the marker range 38 to 42 provides the same SBP = 7.0%
                     A wide range with the best SBP is another figure of merit
         Of course, that range of SBP is really greater
                     As shown in an example above, we can use the mask to include more markers at 7.0%
         The breadth is also greater than 37 to 64 for the same reason
         I don't think it's worth spending effort to find a wider breadth
                      I think it's worth spending some effort to find more markers with the same minimum SBP
                                   More markers is a better definition
                                   Example above
                      I don't think it's worth spending effort to find a minimum marker set with the same SBP
          However, for a particular modal definition, it is worth noting the breadth, which is another measure of the value of the definition
End of breadth
Cherry Picking
          "Cherry Picking" is slang for selecting only the best
          It is possible to improve SBP by selectively masking out those markers that have mutations only at the gap
                      Use Ctrl i to sort by Total
                      Scroll down to those few rows located at the gap
                      Move slowly to the right, using the arrow key or the horizontal scroll bar
                      Examine the mutation steps by marker in all those cells to the right
                      Watch for a number other than zero indicating a mutation at one of those gap rows
                                   Where the rows immediately below have all zeros
                                               Or, more specifically, each row below - with Total greater than the gap - does not have a value
                      Click on that marker cell and observe the pointer
                                   For example, if the formula starts with the "IF(AL" that means that column points to the values in column
                      Go to that column in row 10, the mask
                      Change the value at the mask in that column to zero, or to a small number
                      A zero removes the marker
                      That should drop the row you are working on out of the gap to a lower total step value
                      Continue this for more rows in the gap, maybe even in the rows for Total one step above or below the gap
                      Try increasing the Number of Markers Considered in CI8 to look for more such markers
                                   Increase CI8 by 1 at a time, find any extra markers, and mask them out if they add mutations to the gap
                                   If you find markers with higher rank that do not increase the gap number, that's good; it improves the defin
          Cherry picking example:
                      In this master, or better in a copy of this master:
                      Type 62, 11, 2 in the red box at CI8 for Number, Cutoff, Gap
                      Notice SBP = 13.9%
                      Sort with Ctrl i
                      Observer one sample just below the gap, at Total 10
                      Notice in column EO this row has a 2
                                   And all zeros below it
                      That column points to column BE (DYS444)
                      If you mask out BE - 0 in cell BE10:
                      The suggested cutoff is now 10, gap 3
                      SBP has decreased to 9.3%
          I discuss cherry picking in my publication, lower left of page 157, Fall 2009 issue of:
                      www.jogg.info
          Here is an argument that such cherry picking is not statistically fair:
                      Cherry Picking selects marker that do not have any mutations at the gap
                                   But those are mostly just there by luck
                      Future samples that get added to the database
                                   Might have mutations in the gap at other markers, just by luck
                      It's called selection bias
                      The definition is not really as good as it seems
          Here are 4 arguments that cherry picking is OK:
                      My SBP has statistical down rating to account for selection bias
                      Any sample in the database should be considered a representative of a very small clade in the general population
                                   The clade comprising that person plus all his distant cousins who have not submitted data
                                   Maybe that mutation in the gap happened in one of their ancestors a few centuries ago
                                   So that sample might be representative of a small clade located near the gap
                                   Such a small clade can be included in the type by masking out the corresponding marker
                      The whole point of masking markers is to remove "structure" from the definition of the type
                                   Automatic ranking gives high rank (removes) markers associated with subtypes, which are just very the lar
                                   Cherry picking extends that technique to potential small clades
                      One reason for looking for a good definition of a type:
                                   To objectively assign men in a project database
                                   So cherry picking is good insofar as it provides better assignments
          My opinion:
                      If various people use SBP to compare the quality of their types
                      And if those various people do not all spend the same effort optimizing their definitions
                      And if some use cherry picking and some do not
                      Then those who work hard and cherry pick come up with lower SBP
                      Two people analyzing the same type in the same database might come up with slightly different definitions, slightly d
                      People judging SBP results should look for a factor of 2
                                   SBP of one half is definitely better
                                   The main advantage of SBP is distinguishing 1% vs 2% vs 5% vs 10% vs 20%
          Haplogroups
                      Type analysis is one way to come up with an STR prediction for a known haplogroup
                      Treat the haplogroup as a type
                      SBP is a measure of how good the definition is for predicting SNP results for new STR data
                      Previous known SNP results can be used with cherry picking to improve the definition
                      I did this for P type after the L260 SNP was discovered
End of cherry picking
Ties
          For a small database there are quite a few markers that have no mutations in the database
                      These come out with equal ranking - a tie
                      For example, in this master, there are 11 such markers
                                   They are tied for rank 28
                      In TypeRank, examine rows 10 to 16
                                   Notice that these markers have all 40 database samples modal, and all 10 cluster samples modal
                                   Concentration = 1.000 for these
          Try typing 27 in CI8
                      Notice 27 Top Ranked Markers, top cell in column CI
                      Notice 23 actual markers, cell CI13, due to 464 and YCAII
          Now change that 27 to 28 in CI8
                      Notice the jump to 38 Top Ranked Markers
                      Actual markers jumps to 34
          In a larger database, many of these markers will have 1 or 2 or a few mutations
                      They come out with similar rank, but slightly different
                      Some of them might have a mutation in a sample at the gap
                      So those work very well for cherry picking, previous topic
Number of markers
          This file can be used for a database with fewer than 67 markers
          Blanks are OK
          Markers (columns) with all blanks come out tied for worst rank (highest rank number)
          If you know what you are doing you can delete the columns for both data and step formulae
                      Or add columns for more than 67
          If you know what you are doing you can redefine markers by column
          You can copy alternate step formulae from my file "Calculator.xls"
                      Or compose your own formulae
          All samples do not need to have the same number of markers
                       It is easiest if all samples in the Calculator database have the same number of markers
                                    Sorting is easier, and file size is smaller
                                    You can use "Shift, Ctrl, End" to highlight everything for sorting
                       However, it is OK to use the full database
                                    Even samples with fewer marker data
                                                For example, when producing a type cluster using all 67 markers
                                                            It's OK to have the full database in the Calculator including samples with 12, 25, and
                                                The Excel functions ignore zeros and blanks
                                                The ranking is better for those markers that have better statistics from more data
                                    The TypeRank sheet can also have mixed data
                                                But the Type cluster is generally best defined only using data with all the markers being tested
                                    If necessary, sort to the bottom the samples that do not have all the markers being tested
                                    The downside: sorting by "Total" is more tedious
                                                You need to highlight only the rows with all the markers being tested
                                                You cannot use Ctrl i with mixed marker number
          TypeRank uses functions with ranges in rows 5 to 14
                       These functions ignore blanks, so the cluster can be a mix, for example some samples at 12, 25, 37, 67 markers
                                    For example, in figuring a MOD or AVERAGE, Excel only considers the non-blank rows
                                    Careful: a zero is treated as data; only true blanks are ignored
End of number of markers
How to add rows to Calculator:
          Skip this section if your database has 500 or fewer samples
          It's easier to use Type500.xls and delete any extra rows
          Brief explanation for Excel experts:
                       I use the "Range" feature to point to the database from other sheets
                       So just adding more data at the bottom will not include it in the range
                       Instead, the database needs to be expanded by insertion of rows
                                    Excel will automatically edit all my functions that use the Range
          This insertion must be done before pasting in the database
          Go to the bottom of the Calculator sheet
                       One way: press & hold Ctrl, then press End
          Make sure you are at the bottom
                       You should be in a row of data and numbers that are the result of mutation formulae
                       (You need to be inside my "Range" for Excel to automatically expand the Range with insertion of rows)
          Anywhere in the bottom row is fine
          Insert extra rows just above the bottom row
                       Here is one way to insert rows:
                                    Hold the shift key
                                    Hold the down arrow key to highlight the number of rows you wish to insert
                                    Release shift
                                    Press & release the Alt key
                                    Click "Insert"
                                    Click "Rows"
                       It's OK to insert too many rows, since deleting extra rows is easy
          Next copy the formulae into the new rows
                       Go to the bottom again, column CI
                                    That should be a SUM formula
                                                with your new blank rows above it
                       Copy all the formulae from there to the far right
                                    Hold the shift key
                                    Press the right arrow cursor key 2 or more times
                                    Press & release the End key
                                   Press & release the right arrow cursor once
                                   Release shift
                                   Click "Edit" and "Copy"
                       Paste the formulae into the new blank rows
                                   Hold the shift key
                                   Press & release the End key
                                   Press & release the up arrow cursor once
                                   Release shift
                                   Click "Edit" and "Paste"
End of instructions for adding rows to the Calculator database
Add rows to TypeRank
           Alert: For more than 100 samples in a cluster, a range change is needed in TypeRank:
           The range needs to be increased
           This is similar to increasing the range in the Calculator database, explained above
                       Except there is only one formula to copy - in column DE
           Here are the instructions for increasing the TypeRank range to more than 100 samples:
                       Before copying the cluster into the TypeRank sheet:
                       Click anywhere between rows 22 and 119 on the TypeRank sheet
                                   And insert as many rows as needed
                                   Excel will automatically change the range in all formulae
                       Spot check a few
                                   For example the MODE function in row 3
                                   That "120" should be changed to the last row
                       Copy in row DE (used for 389-2)
                                   Click in column DE, above where you inserted the extra rows
                                               Make sure you see the formula
                                               Copy
                                               Holding shift, Page Down (or down arrow key) enough to highlight all the inserted rows
                                               Paste
                                                           Excel inserts and adjusts the formulae
The TypeASD sheet uses this same range 21-120 by default
           If more than 100 samples are used in the TypeASD sheet:
                       Use above row insertion procedure for the Type ASD sheet
TypeRank sheet copies
           When you have a pretty good modal & cluster
                       but you would like to try to make a better one
           Consider a backup copy of this entire file
           Or, consider making a backup copy the TypeRank sheet right in the same file
                       Right click on the "TypeRank" tab to create a copy
                       Give the copy sheet a new name (right click on the tab)
           This copy still works if the data is changed
                       So if the modal on the Calculator changes, so does the modal on row 3 on this new copy sheet
                       So you are only saving the Type data with such a copy
           To save an archive backup of only the result:
                       Highlight the entire new copy sheet
                       Copy
                       Paste Special, Values
                                   That gets rid of the formulae and just saves the results
           Right click on the tab to delete a copy
The "Haplotypes & Masks" sheet has an assortment of useful signatures & masks; more haplotype & mask copies can be stored there
           Check the labels on the far right
           It should be obvious enough how to use this sheet
Detailed Documentation
          The rest of this sheet is not instructions - just explanations of how things work:
Net mask markers; Calculator row 12
          Most columns use a standard formula, for example column A
                     This formula considers the mask in row 10
                                  negative number means always use this marker, changing the number to positive in row 12
                                  0 means do not use this marker
                                  A positive number is the maximum mutation count for this marker
          Three compound markers use unique marker formulae, explained above
                     389-2, 464 (7 markers), YCAII (2 markers)
Detailed Documentation of the "TypeRank" sheet:
          There are notes to the far right of the data
          Row 3 is a copy of the current Modal Haplotype from the Calculator sheet
          Row 5 is the calculated Modal Haplotype
          Row 4 is a blank row, handy for making a new modal
                     OK to copy a modal here, modify it, copy it somewhere else, delete it here - but do not use cut, do not delete the row
          Cluster data is copied below row 20
          Rows 1, 2, 9, & 20 are notes & labels; not used for calculations; information only
          Column DE is used for 389-2, which is really "389b", a difference between 389-2 and 389-1
Detailed Documentation of the marker formulae on the TypeRank sheet:
          Calculation formulae in rows 5-9
          Row 5 is the modal for the cluster data on this sheet, as figured by the Excel MODE function
                     This is the most common value for that marker on this TypeRank sheet
                     For more discussion, see "Modal Comments" above
          Row 6 is the average; AVERAGE function
          Row 7 is the median, the middle value when arranged in order, MEDIAN function
          Row 8 is an alert if one of the 3 calculated values differs from your official modal in row 3 at that marker:
                     A dash "-" means no difference
                                  A dash means that all 3 calculated values in rows 5, 6, and 7 are the same as in row 3
                                              (Averages rounded off to integers)
                     A value in row 8 means not all 3 calculated (and rounded off) values are the same as the row 3 modal at that marker
                                  A value in row 8 is the difference between your value in row 3 vs the average in row 8 (this time not round
                                              You might consider using the average instead of the mode if the distribution looks bimodal (or
          There are a number of reasons you may decide to use an "official" value for a marker in row 3 other than the modal from row 5
                     One reason: a poorly ranked marker may fluctuate plus or minus one when new data is added to a database, and you m
                     It's your decision
          Use whole numbers for modals
                     The Calculator is not designed for fractions
          Use whole numbers for masks
Detailed Documentation for determining the concentration rank; TypeRank sheet:
          Formulae in rows 10-19
          Notice the row labels over on the far right
          Row 10 is the number of samples on the Calculator sheet that have a value at this marker
                     blanks are not counted
          Row 11 is the number of samples on the Calculator sheet that have the modal value (in row 3) at that marker
                     Row 12 is the fraction with this modal value; row 11 divided by row 10
          Row 13 is the number of samples on this TypeRank sheet that have a value at this marker
                     Below row 20
          Row 14 is the number of samples on this TypeRank sheet that have the modal value (in row 3) at that marker
                     Row 15 is the fraction with this modal value; row 13 divided by row 14
          Concentration is in row 16
                     Ratio of (fraction from row 15 cubed) divided by fraction from row 12
                               A larger number means that marker is particularly effective at concentrating samples into this cluster
                    This is my own method of objectively assessing the value of a marker for use as a definition or signature
                               I have not found in the literature a recommended objective test for signature markers
                               Please let me know if you know of a better method
                               I tried a simple ratio, but too often markers with high variance in the cluster came out with good rank
                                            Squaring that numerator seems to work better, cubing it better yet, at least for me so far
          Row 17 is rank. The largest number in row 16 - largest concentration value - gets a 1; 2nd largest gets a 2, etc
                    Rank 1 to 67
                               Ties get the same rank
          Row 18 highlights the best ones - easier to spot them
                    That's row 18 on the TypeRank sheet
                    And a copy on row 11 of the Calculator sheet
                    Number of markers to consider
                               You type in this number
                               In cell CI8 of the "Calculator" sheet
                                            Explained above
                    Actual type ranked markers
                               Might be greater than the number considered in case of a tie
                               Might differ because of compound markers, discussed above
                               Displayed in row 19 of TypeRank, with 1 at each marker that is ranked
                               Summed in TypeRank, displayed in blue below the number considered
                                            A copy of this actual ranking marker number is in the Calculator sheet in the top cell of column
                    Net markers
                               Might differ if you excluded a marker with a blank or zero in row 10 of the Calculator
                               Might differ if you include a marker using the negative code discussed above
                               Does not get adjusted for blanks in the modal haplotype - those are effectively excluded but not counted he
                               Does not include 464 e, f, g
                               Displayed in row 9 of TypeRank, with 1 at each net marker
                               Summed in TypeRank, displayed in blue below the actual number
                                            A copy of this net marker number is in the Calculator sheet row 13
                    The net mask is in row 12 of the Calculator
                               This can be copied elsewhere; use "Paste, Special, Values"
                    Haplotypes using actual markers and net markers are available in the sheet "Haplotypes & Masks"
                    That sheet also provides a net mask where you may type in the value to use for each marker
End of Documentation
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 o the TypeRank sheet




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 m both to be used, compatible with Ysearch



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 the rank of either
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 a, b, compound pairs
plotypes being compared at either of these two markers




that marker will effectively not be used




marker that does not match in the two haplotypes being compared


  in either haplotype
Ysearch method
 s file with functions not allowed
n, the function is called only once for each sample, in the very last column on the right
 "a" column, DF
 step columns at the right for mutation count (normally)

ater than 7 has no effect

 u know they are being used
n the definition modal (see the "Haplotypes & Masks" sheet)
10 above 464 b to g are ignored (normally - an exception is coming up)
2 and 464 is not evaluated
2 and the result in DL is truncated to that maximum
ll ranked (each of the 4 not larger than CI8)
64 markers get 0 in row 12 for the effective mask




 a - that means all the 464 markers are treated as individuals

plotypes being compared at each of these 7 markers
ow 12 so that marker will effectively not be used
ept those that also have a 0)
toward the top
belong to the hypothetical clade




which cutoff is best



will have multiple minima even with lots more data
nt from your cluster




in your database
ete it here - but do not use cut, do not delete the row




h least 2 copies in that column below row 20
 in columns having problems with MODE
tor sheet database

ain in the best fit definition
 compared to saved columns with higher SBP




7 at this marker




 type example
e STR data at 67 markers because they do not correlate with other markers




at produce the same mountain cluster of data




t 64 gives one less sample at cutoff 11

ition cannot be extracted

f samples less than the cutoff,


ssing plus extra) for 21 to 30, 3 for 31 to 40, etc
ure of the value of the definition




the gap - does not have a value at this marker such that removing it will drop that row into the gap

n points to the values in column AL in the database




ove or below the gap

hey add mutations to the gap
hat's good; it improves the definition




e in the general population
submitted data
ypes, which are just very the largest, oldest subclades




y different definitions, slightly different SBP




luster samples modal
cluding samples with 12, 25, and 37 markers

s from more data

ith all the markers being tested




 at 12, 25, 37, 67 markers
non-blank rows




 insertion of rows)
ight all the inserted rows




copies can be stored there
sitive in row 12




t use cut, do not delete the row




 he row 3 modal at that marker
age in row 8 (this time not rounded off)
e distribution looks bimodal (or multimodal) at that marker
 her than the modal from row 5
is added to a database, and you may prefer not to keep changing such a modal for trivial variations
g samples into this cluster
nition or signature


r came out with good rank
et, at least for me so far
st gets a 2, etc




r sheet in the top cell of column CI



vely excluded but not counted here
             SBP Documentation                          12 Sep 2010             Peter Gwozdz
I published an article explaining SBP
             I published this in JOGG, fall of 2009
                          www.jogg.info/52/index.html
                                        page 137
Very brief explanation:
             A "Mountain in Haplospace" is all samples from the database with mutation total less than a "cutoff" value
                          where the cutoff value has relatively few samples
                          In other words, a graph with y-axis the number of samples in "Total" vs x-axis the value in "Total" looks like a mo
                                        This master has a small mountain graph example in the SBP sheet
                                                       The mountain is on the left side of the graph
                                                       10 samples in a small mountain with a cutoff step 4
                                                                    And a "gap" of 4 steps from step 4 to 7
                                                       This is a very good mountain, very well isolated from the rest of the database
                                                                    The rest of the database is all the samples to the right, with step greater than
                          In general, a good mountain has:
                                        A relatively large number of samples at steps much less than the cutoff
                                        Fewer samples at steps just below the cutoff
                                        Very few samples at the cutoff
                                                       Or better yet, a "gap" which is a span of values starting at the cutoff
                                                                    With very few samples throughout the span of the gap
                          The SBP sheet automatically produces such a graph of frequency vs step
                                        Using the database from the Calculator sheet
                                                       Column CI - Total
             This Type.xls file is dedicated to the proposition that the mountain effect is evidence that the cluster is a clade
                          This is my own idea as far as I know
                          I came up with SBP as an Excel calculated value that objectively assesses the quality of the mountain effect
             SBP = Statistical Background Percent
                          "Background" means samples within a cluster mountain that really to not belong to the cluster
                                        Background is estimated based on how many samples are in the gap
                                        More samples in the gap means it is more likely there are "foreign" samples in the mountain
                          "Statistical" means adjusting for small sample size
                                        Bigger statistical background for smaller sample sizes, using a standard statistics equation
                          "Percent" means background number of samples as a percent of the number of samples in the mountain
             By "type" I mean all the following:
                          A known clade or a hypothetical clade
                          The corresponding cluster of data (STR values for samples) from a database
                          The modal for that cluster at any number of markers
                          The list of all haplotypes at that number of markers that differ from the modal by less than a specified cutoff
                          "Type" is my own term
                                        I use it to distinguish from "cluster" which is a common term used by DNA publications
             The "definition" of a type is the modal haplotype, plus the cutoff and gap values, using the set of makers and modal values that
                          I don't have a strict mathematical method to find the "best" definition
                          You need to try many combinations of those 3 numbers at CI6 in the Calculator
                                        Number of markers, cutoff, gap
                          I have some tips in the TypeDoc sheet
                          With experience, you'll gain the skill and intuition needed to find good definitions quickly
             SBP is not the same as probability that the type represents a true clade
                          But lower SBP is evidence that a type is more likely to represent a clade
                          A cluster must have SBP < 50% to be seriously considered as a "type"
                                        All types have a cluster, but not all clusters represent a type
                          A type with SBP < 20% is likely to represent a clade, or future haplogroup
The input data locations are highlighted red on the Calculator sheet
              Enter Number of Markers, Cutoff, & Gap values in CI6, CI7, and CI8
                            You determine the best cutoff and gap by trial and error
                                          The values that produce the lowest SBP
More input on the SBP sheet
              A3            Confidence = 70%            I don't recommend changing this
                                                        Read the companion article for an explanation of this Poisson confidence range
              A6            A6 is the display height for the gap
                            This is not used for calculations, just a convenient red marker on the graph
                            You can change this for better visibility of the gap
The output is highlighted blue
              Do not type in the blue cells
                            That removes the formulae there
              Notice that your input Cutoff and Gap from the Calculator
                            Is displayed in blue in the SBP sheet, A4 & A5
                                          Where it is used for the calculations
Step frequency data:
              The SBP sheet automatically gets this from the Calculator, column CI
Distribution Graph
              Standard Excel graph; see Excel documentation
              The x-axis may be too long for your analysis, since this is set up for 25 steps
                            There is a simple method to reduce the x-axis range on that graph, if you are unfamiliar with Excel graph ranges:
                                          First, be sure you have a copy of this master, because this simple method deletes the formulae in the b
                                          This simple method is written in red, above the data for the Distribution Graph
              I doubt anyone will ever need more than 25 steps
                            If you are experienced with Excel you can figure out how to expand the x-axis range
Cells N3 to N5 check your input Cutoff, Gap, Display
              And fix it if it is negative, or a decimal number, or otherwise wrong
This file has a macro function for calculating the Poisson distribution
              Excel gives you a choice to disable the macro when you open the file
              I downloaded the Poisson functions from:
                            http://statpages.org/confint.html
              There is a Poisson demonstration over on right in the SBP sheet
              Further right is a confidence demonstration
For comparison, this file calculates key parameters for various values of Cutoff and Step
              These are suggestions to you; possible better values
                            But a human has better judgment for this than a spread sheet
              In a table over to the right
                            "SBP Trials"
              Starting with your values in A3 & A4
                            And varying them, one pair for each row
              The minimum for important columns is displayed at the top
                            And a copy is displayed in the Calculator sheet
                                          At the top of column CI
              These suggestions are only for cutoff values close to your input cutoff
                            If your input is far from the gap the suggestions won't make sense
              The best cutoff & gap are usually the numbers that provide the smallest SBP
                            Consider these minimums
                                          Maybe they suggest to you better values for the cutoff & gap
                            Not always; sometimes a minimum SBP at the top of the column looks silly
                                          Maybe that is because it is too far away from the mountain
                                          Consider "local" minimums
                                                     compared to the "neighborhood" values
                                                     the neighborhood is highlighted blue in that array over to the right
                                                     with 1 added / subtracted to your input Cutoff / End of Gap
                                      Sometimes even a local minimum looks wrong
                                                     Maybe the problem has to do with the last step of the mountain
                                      Human judgment may be required in these cases
                                                     If your best judgment values are not minimum; that's OK
                                                                   You are a better than a computer to judge a good mountain and good gap
                                                                   But once you select the cutoff & gap
                                                                                 The computer calculates SBP
                                                                                              Or you can calculate, using the equations
Once you get experience on how SBP works, you can usually guess which "Totals" column will provide the lowest SBP
            You can save "Totals" columns in the Calculator sheet in the "Results" region
                         One column for each set of markers, or for each trial of the modal haplotype
                         You can sort and examine these columns and judge which columns are likely low SBP
            Obviously, a cutoff of zero usually produces a lower SBP than a cutoff with 1 sample
                         And a cutoff of 1 is better than 2; 2 is better than 3, etc
            However, a wider gap can be better than a narrower gap with fewer samples
                         Example: consider a gap of one step, with zero samples
                                                     The 70% statistics number for zero is 1.9
                                                                   Try it out in that Poisson demonstration, far right, SBP sheet
                                                     So the statistical background in the gap is 1.9
                                      Suppose the next step has one sample
                                                     The 70% statistics number for 1 (one) is 3.37
                                                     With a gap of 2, that statistical 3.37 gets averaged over 2 steps, which is 1.7 statistical ba
                                                                   Slightly better than the one-step gap of zero (1.9 statistical background, abov
                                      Suppose the third step has zero
                                                     Just like the example data, SBP sheet
                                                                   Averaged over a gap of 3 steps, the statistical 3.37 becomes 1.1 per step (in
You can set up the Calculator to automatically figure SBP
            Example: use the Total column
                         For data, point to the Total column:
                                      First, set the "Label" to "Total"
                                                     Click on SBP, A11
                                                     Type = (the equal sign)
                                                     Click on Calculator, CJ13 (the word "Total")
                                                     Hit Enter
                                      Next, copy the pointer to the column below
                                                     Click on SBP, A11
                                                      Edit, Copy
                                                     Hold Shift
                                                                   Press Page Down a few times
                                                                                 Enough rows to include enough data to go well beyond the mou
                                                                   Release Shift
                                                                   Edit, Paste
                                                                   Check if any left over data from a previous calculation, below this, needs to
                                                                   Check to be sure there are no zeros at the bottom for unused row calculation
            This can also be done using any one of the Results columns
            You can put a pointer above the data in Calculator, to display the SBP result in the Calculator:
                         Click in row 12, Calculator
                         =
                         Click in SBP, cell E1 (SBP result)
                         Enter
            Of course, this will not optimize the choice of cutoff and gap for each Calculator trial
                         You still need to click over to the SBP sheet to see if the cutoff and gap are reasonable
Copy of the SBP sheet
            Another option: multiple copies of the SBP sheet, for multiple columns from Calculator with SBP calculated simultaneously

You can set up SBP calculation of multiple columns at the same time
            Make a copy of the SBP sheet
                        Copy Instructions:
                                      Right click on the SBP tab
                                      "Move or Copy"
                                      "Create a Copy" (If you do not check this box, this merely moves the sheet
                                      Click on the location of the copy (select from "Before Sheet" list)
                                      OK
                                      Right click on the copy to change the name
            Change the input for that copy
                        Redirect the input to different cells in the Calculator
                        A4 & A5
                                      Redirect
                                      Or, just overtype new values
                        Frequency data
                                      Redirect to a different column
                                                   For example, one of the results columns
End of Documentation
han a "cutoff" value

axis the value in "Total" looks like a mountain




from the rest of the database
mples to the right, with step greater than 7




 arting at the cutoff
he span of the gap



 at the cluster is a clade

the quality of the mountain effect

belong to the cluster

eign" samples in the mountain

a standard statistics equation
er of samples in the mountain




 dal by less than a specified cutoff

used by DNA publications
the set of makers and modal values that produce the lowest SBP, usually the lowest gap




initions quickly
this Poisson confidence range




re unfamiliar with Excel graph ranges:
ple method deletes the formulae in the bottom rows
istribution Graph
y over to the right


f the mountain


judge a good mountain and good gap


 calculate, using the equations
vide the lowest SBP




 ion, far right, SBP sheet



d over 2 steps, which is 1.7 statistical background
 of zero (1.9 statistical background, above)


statistical 3.37 becomes 1.1 per step (in blue, cell J8 on the SBP sheet)




 enough data to go well beyond the mountain, which should be sorted to the top


 evious calculation, below this, needs to be deleted
at the bottom for unused row calculations
or with SBP calculated simultaneously
           ASD Documentation                    20 Sep 2010            Peter Gwozdz
"ASD"; Average Squared Distance
           My article about SBP also explains ASD
                      That article has explanations of how age of a clade is calculated using ASD
                      Also literature references
           The ASD sheet calculates age, many different ways, using the data from the "TypeASD" sheet
           ASD age is a complex subject
                      If you read and understand the companion article, the ASD sheet should be self-explanatory
           For examples of how to work with ASD, it might be helpful to look at my results
                      For example: see PType.xls, PcType.xls, Atype.xls, etc
                                   Those are all copies of this file (with the "Documentation" sheets deleted) and with analysis for one type
                                               Some of those have multiple copies of the ASD sheet
"TypeASD" Sheet
           This is similar to the "TypeRank" sheet
                      Except the pointers to the Calculator sheet are not used in TypeASD
                                   Because that would cause problems when copying the sheet
                      And the rank of markers is not done in TypeASD
           Copy the modal haplotype from row 3 of the "Calculator" sheet
                      Paste in row 3 of the TypeASD sheet
           Copy the Type data from below row 13 in the Calculator sheet
                      Paste below row 20 of the TypeASD sheet
                      The method for copying the data is exactly the same as for the TypeRank sheet
                                   See the TypeDoc sheet if you need copying instructions
                                               Look for "Copy your cluster into the TypeRank sheet below row 20"
Data for the TypeASD sheet
           May be the same as the data in the TypeRank sheet
                      But not necessarily
           The TypeRank sheet often works better if only the best fit data of the cluster is used
           The TypeASD sheet, on the other hand usually needs all the data from the mountain
           In addition, to determine the sensitivity of ASD results to choice of cutoff,
                      It is best to calculate ASD multiple times
                      For example:
                                   Once with the full mountain - all data up to but not including the cutoff (gap)
                                   Once with additional data from the gap, perhaps even data beyond the gap
                                               To show how much the ASD age increases with higher cutoff
                                   Once with only the best fit data
                                               To show how much the ASD age decreases with lower cutoff
                                   Perhaps also with different marker sets
           These can be done sequentially, using the same TypeASD sheet
                      Data in a TypeASD sheet can be changed; same as in a TypeRank sheet is changed
           Or multiple copies of the ASD sheet pairs can be moved into this file
                      Instructions for moving are below
The "TypeASD" and "ASD" sheet work together as a pair
           The formulae in the ASD sheet "point" to the data in the TypeASD sheet
                      When you change the name of a TypeASD sheet,
                                   Excel automatically changes the pointers in the ASD sheet
Deletion:
           If you wish to analyze a type without analyzing ASD age:
           You can delete both sheets TypeASD and ASD
                      This file works fine without them
           Deleting only TypeASD will cause an error in the pointers in the ASD sheet
           Deleting only the ASD will make TypeASD useless
Stand Alone ASD:
           If you with to analyze ASD but not SBP:
           You can delete all sheets except those two (TypeASD and ASD)
           They work fine with only those 2
Copies: If you want more working copies of the TypeASD & ASD sheet pair in the same file:
           You cannot just copy them
           Right clicking on the tab will not work for making working copies
                      Because with an ASD copy sheet
                                  Excel will point to the data in the original TypeASD sheet
                                               Even if that sheet is in a different file
                                  If you know how, you can change the formulae with pointers
                                               But it is easier to just move a pair of sheets
Instructions for moving to get extra copies in the same file:
           Assume you are working with a copy of this master, let's call it "TypeAnalysis.xls"
                      And assume you have it open
                      And you would like another copy pair
           Open Type.xls
           Move those two sheets (TypeASD and ASD) from Type.xls to TypeAnalysis.xls
           To move a sheet:
                      Right click on the tab
                      "Move or Copy"
                      Do not check the "Create a Copy" box; the box blank means the sheet is being moved, not copied
                      Click on the file to receive the sheet (select this file from "To Book" list)
                      Click on the location (select from "Before Sheet" list)
                      OK
                      (Excel changes the pointers twice to keep track of the proper renamed "TypeASD" data sheet)
           Close Type.xls without saving
           Comments:
                      If you save Type.xls after moving the two files will be lost from this master
                                  Closing without saving of course preserves them
                      Excel with add (2) to the name of a sheet if there is already a sheet by that name
                                  No problem; you can rename these sheets
                                  Or you can rename before moving
                      If you check that "Create a Copy" box when moving the ASD sheet,
                                  Excel will copy the sheet, not just move it
                                  The copy will point to the data in the original file
                                  Later, when you open the file with the copy, Excel will ask you to open the orignal file for the data
                      Several ASD pairs can be in the same file
Mask
           Row 21 of the ASD sheet is a mask, for quickly selecting markers to be included in the ASD average
           Zero removes the marker at that column from the average
           Any value selects that marker. The value is disregarded, changed to a 1 by a formula in row 22 for counting the markers that are
Compound Markers
           The default mask in row 21, with 59 markers, has some of the compound markers removed
                      These markers seem to have recLOH mutations most often
                                  recLOH copy mutations may cause large genetic step distances, providing unreasonably old ASD ages
                      For young clades, without many recLOH mutations, the age of a single compound marker may be meaningful
                      See the "Documentation" sheet in the file "Calculator.xls" for more explanation about recLOH and compound marker
           Of course you should edit this mask to only exclude the markers that actually have significant recLOH mutations in your "Type"
                      And exclude any other large mutation step problems
                      Watch out for selection bias:
                                  It is not fair to exclude only markers that seem old
                                 If any marker with recLOH is excluded, then all markers with recLOH should be excluded, even those that
          The infinite alleles method, starting on row 39, treats compound markers as combined entities
                     Any change from the modal value on either of the 2 markers (or any one of the 4 from 464) is a mutation for the set
                                 Mutations are figured in a table, for all 7 compound markers, over to the far right
                     The age is calculated only for the "a" column, but applies to the compound pair (or quartet)
                     The Chandler rates are multiplied by 2 for pairs, 4 for 464
The ASD sheet does not support 19b or 464 e to g; these can be added with some effort
End of Documentation
and with analysis for one type
 orignal file for the data




or counting the markers that are included



 unreasonably old ASD ages
 rker may be meaningful
  recLOH and compound markers
cLOH mutations in your "Type" data
uld be excluded, even those that came out young

464) is a mutation for the set
     A B C D E F G H I J K L M N O P Q R S T U V W X Y Z AAABACADAEAFAGAH AI AJ AKALAMANAOAPAQARASATAUAVAW                                                          AXAYAZBABBBC
 1      Calculator                    Peter Gwozdz                                    See TypeDoc sheet for more documentation in the file:         http://www.gwozdz.org/PolishCladesU
 2                Type or copy the proposed modal into row 3                          Sample data from the Polish Project R1a 12 Oct 2007
 3   13 25 17 10 10 14 12 12 10 13 11 30 16 9 10 11 11 23 14 20 31 12 15 16 16 11 11 19 23 16 16 18 19 34 39 13 11 11 8 17 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13
 4                Copy the database below row 13; markers with blank or zero are ignored
 5                  Delete extra rows below the database; deleting just data in cells will not work - the extra rows need to be deleted
 6                Copy or edit the mask into row 10; do not enter anything into rows 11 & 12
 7                Mutation count is the "Total", column CI, in the middle of this sheet
 8                  To save the Total column, try the "Ctrl i" macro, then move to the left, then Edit, Paste Special, Values
 9                                                                          0                    0 <<< 0 = Ysearch infinite alleles method for 464 & YCAII
10    4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 4 4 4 4 4 4 4 4 4 4 5 4 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6
11   45 - 3 10 1 14 - 20 - 39 20 18 - 28 44 14 28 7 20 20 - - 39 8 6 43 9 - 14 - - - - - - - 12 12 11 20 14 28 42 28 28 4 - 28 18 20 - 20 28 20 -
12    4 0 4 4 4 4 0 4 0 4 4 4 0 4 4 4 4 4 4 4 0 0 0 0 0 4 4 0 0 0 0 0 0 0 0 0 4 4 4 4 4 4 4 4 4 4 0 4 4 4 0 4 4 4 0
13                  385b       389-1 392            459b
     39339019 391385a 426388439 389-2 458459a 455454447437448449464a 464c 460GATAYCb56607576570CDa Db42438531578395a 590537641472406511425413a 557594436490534
                                                                               464b 464d        YCa 4                   C 4                395b                      413b
14   13 25 17 10 10 14 12 12 10 13 11 30 16 9 10 11 11 23 14 20 31 12 15 15 16 11 11 19 23 16 17 17 19 36 38 12 11 11 8 17 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13
15   13 25 17 10 10 14 12 12 11 13 11 30 17 9 10 11 11 23 14 20 32 12 15 16 16 11 11 19 23 15 16 18 20 35 38 14 11 11 8 17 17 8 12 10 8 12 10 12 22 22 14 10 12 12 14
16   13 24 17 10 10 14 12 12 11 13 11 30 17 9 10 11 11 23 14 20 31 12 15 16 16 12 11 19 23 16 16 17 19 34 40 12 11 11 8 17 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13
17   13 25 17 10 10 14 12 12 10 13 11 30 17 9 10 11 11 23 14 20 32 12 15 16 16 11 11 20 23 15 15 19 19 33 42 13 11 11 8 17 17 8 12 10 8 12 11 12 22 22 15 10 12 12 13
18   13 25 17 10 10 14 12 12 10 13 11 31 17 9 10 11 11 23 14 20 34 12 15 16 16 11 11 19 23 16 16 18 19 34 39 12 11 11 8 17 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13
19   13 26 17 10 10 14 12 12 11 13 11 30 16 9 10 11 11 23 14 20 32 12 15 16 16 11 11 19 23 15 16 19 20 36 38 14 11 11 8 17 17 8 11 10 8 12 10 12 22 22 16 10 12 12 14
20   13 25 17 10 10 14 12 12 10 13 11 30 16 9 10 11 11 23 14 20 31 12 15 15 16 11 11 19 23 15 16 17 17 37 39 13 11 11 8 17 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13
21   13 25 16 10 10 14 12 12 10 13 11 30 16 9 10 11 11 22 14 20 33 15 15 15 16 11 11 19 23 16 16 19 18 35 41 11 11 11 8 17 17 8 12 10 8 12 9 12 22 22 15 10 12 12 13
22   13 25 17 10 10 14 12 12 11 14 11 31 18 9 10 11 11 23 14 20 32 12 15 16 16 11 11 19 23 16 16 18 18 34 39 14 11 11 8 17 17 8 12 10 8 12 10 12 21 22 15 10 12 12 14
23   14 25 17 10 10 14 11 12 10 13 11 30 16 9 9 11 11 23 14 20 31 16 16 16 16 11 11 19 23 15 14 18 19 32 32 14 11 11 8 17 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13
24   13 25 15 10 11 14 12 12 11 13 11 29 16 9 10 11 11 23 14 20 33 12 15 15 16 11 11 19 23 17 16 18 19 34 42 14 11 11 8 17 17 8 11 10 8 12 9 12 21 22 15 10 12 12 13
25   13 25 16 10 11 14 12 12 10 13 11 30 15 9 10 11 11 24 14 20 31 13 14 15 15 11 12 19 23 16 15 18 17 34 40 12 11 11 8 17 17 8 12 10 8 11 10 12 22 22 15 10 12 12 13
26   13 25 16 10 11 14 12 12 11 14 11 30 15 9 10 11 11 23 14 20 32 12 14 15 15 11 11 19 23 16 16 18 18 33 37 14 11 11 8 17 17 8 11 10 8 12 10 12 22 22 15 10 12 12 13
27   13 24 16 10 11 14 12 12 10 13 11 30 14 9 10 11 11 24 14 20 30 12 12 15 15 11 11 19 23 14 16 18 18 35 38 14 11 12 8 17 17 8 12 10 8 11 10 12 22 22 15 10 12 12 15
28   13 24 16 11 11 14 12 12 11 13 11 30 15 9 10 11 11 24 14 20 31 12 14 15 17 11 12 19 23 16 16 17 18 32 38 13 11 11 8 17 17 8 12 10 8 11 11 12 22 22 15 10 12 12 13
29   13 25 15 10 11 14 12 12 10 13 11 31 17 9 10 11 11 23 14 20 31 13 15 15 15 11 12 19 23 16 15 17 17 34 39 12 11 11 8 17 17 8 12 10 8 11 10 12 22 22 15 10 12 12 14
30   13 25 16 10 11 14 12 12 10 13 11 30 14 9 11 11 11 24 14 20 30 12 12 15 15 11 11 19 23 14 16 19 20 34 38 15 11 11 8 17 17 8 12 10 8 11 10 12 22 22 15 10 12 12 14
31   13 25 16 11 11 14 12 12 11 13 11 30 17 9 10 12 11 24 14 20 31 11 15 15 16 11 11 19 23 17 16 16 19 34 38 15 11 11 8 17 17 8 12 10 8 11 11 12 22 22 15 10 12 12 13
32   13 25 17 10 11 14 12 12 10 14 11 31 15 9 10 11 11 24 14 20 32 12 15 15 16 11 11 19 23 17 15 17 20 35 38 12 11 11 8 17 17 8 12 10 8 10 10 12 21 22 15 10 12 12 13
33   13 25 15 10 11 14 12 12 11 14 11 31 15 9 10 11 11 24 14 20 32 12 15 15 15 11 12 19 23 16 16 18 18 33 37 12 11 11 8 17 17 8 12 10 8 11 11 12 22 22 15 10 12 12 13
34   13 25 15 10 12 14 12 12 11 13 11 29 16 9 10 11 11 23 14 20 32 12 15 15 16 11 11 19 23 17 16 18 18 35 41 14 11 11 8 17 17 8 11 10 8 12 10 12 21 22 15 11 12 12 13
35   13 25 16 10 11 14 12 12 10 13 11 30 14 9 11 11 11 24 14 20 30 12 12 15 15 11 11 19 23 14 16 19 20 35 35 14 11 11 9 17 17 8 12 10 8 11 10 12 22 22 15 10 12 12 12
36   13 25 17 11 11 14 12 12 10 13 11 31 14 9 10 11 11 24 14 20 34 13 15 15 16 11 12 19 23 15 16 18 19 35 40 14 11 11 9 17 17 8 12 10 8 11 10 12 22 22 15 10 12 12 13
37   13 26 16 10 11 14 12 12 10 13 11 30 15 9 10 12 11 23 14 20 31 15 15 15 15 11 12 19 23 15 15 17 17 34 39 12 11 11 8 17 17 8 11 10 8 11 10 12 21 22 15 10 12 12 12
38   13 25 15 10 11 14 12 14 10 13 11 30 15 9 10 11 11 24 14 20 32 14 15 15 15 11 13 19 23 16 15 19 15 35 39 12 11 11 8 17 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13
39   13 25 16 10 11 14 12 12 10 13 11 30 16 9 10 11 11 24 14 20 32 13 15 15 17 10 11 19 23 16 16 20 18 35 40 14 11 11 9 17 17 8 12 10 8 11 10 12 22 22 12 10 12 12 13
40   13 25 16 10 11 14 12 12 11 13 11 30 15 9 10 11 11 24 14 20 31 12 15 15 16 12 13 19 23 17 16 18 18 34 39 15 12 11 8 17 17 8 12 10 8 11 10 12 22 22 15 10 12 12 14
41   13 25 16 11 11 14 12 12 10 14 11 31 15 9 10 11 11 24 14 20 32 12 15 16 16 11 11 19 23 16 15 17 19 36 39 12 11 11 8 17 17 8 12 10 8 10 10 12 21 22 15 10 12 12 13
42   13 25 16 11 11 14 12 12 10 14 11 31 15 9 10 11 11 24 14 20 32 12 15 16 16 11 11 19 23 16 15 18 19 36 39 12 11 11 8 17 17 8 12 10 8 10 10 12 21 22 15 10 12 12 13
43   13 25 17 11 12 14 12 12 13 14 11 31 15 9 10 11 11 23 14 20 33 13 15 15 16 12 13 19 23 15 16 18 20 32 40 14 11 11 8 17 17 8 12 10 8 11 11 12 22 22 15 10 12 12 14
44   14 25 16 11 11 14 12 12 10 13 11 31 16 9 10 11 11 24 14 20 31 12 15 15 16 11 11 19 22 16 15 18 19 35 37 15 11 11 8 17 17 8 12 10 8 12 11 12 22 22 15 10 12 12 13
45   13 25 15 10 11 14 12 12 11 14 11 30 16 9 10 11 11 23 14 20 32 12 15 15 16 11 11 19 23 17 16 18 20 34 38 14 11 11 8 17 18 8 12 10 8 12 10 12 21 22 15 10 12 12 13
46   13 25 16 11 11 14 12 12 11 14 10 31 16 9 10 11 11 25 14 20 33 12 14 15 16 11 11 19 23 16 16 19 19 33 40 14 11 11 8 16 17 8 12 10 8 12 10 12 22 22 15 10 12 12 14
47   13 27 16 11 12 14 12 12 10 13 11 29 18 9 10 11 11 23 14 20 34 13 15 15 17 11 11 19 23 16 16 19 19 34 35 14 12 11 8 17 17 8 12 10 8 10 10 12 21 22 16 10 12 12 13
48   14 25 15 10 11 14 11 12 11 14 11 31 16 9 10 11 11 23 14 20 32 12 15 15 16 10 11 19 23 17 17 17 20 34 42 14 11 11 8 17 17 8 11 10 8 13 10 12 21 22 15 10 12 12 13
     A    B    C    D    E    F    G    H     I   J    K    L    M    N   O    P    Q    R    S    T    U    V    W    X    Y    Z AAABACADAEAFAGAH AI AJ AKALAMANAOAPAQARASATAUAVAW                  AXAYAZBABBBC
49   13   25   16   10   11   14   12   12   11   13   11   29   16   9   10   11   11   23   14   20   31   12   14   15   15   11 11 19 23 18 16 18 19 35 36 13 11 12 8 17 17 8 11 10 8 12 10 12 19 22 14 10 12 12 13
50   13   25   16   11   11   14   12   12   10   13   11   30   16   9   10   11   11   24   14   20   32   13   15   15   15   11 12 19 23 16 17 18 19 35 37 14 11 11 8 17 18 8 12 10 8 10 10 12 20 22 15 10 12 12 14
51   13   25   15   11   11   15   12   12   11   13   11   30   15   9   9    11   11   25   14   20   34   12   14   14   16   11 12 19 23 15 16 19 20 33 39 14 11 12 8 17 17 8 12 10 8 11 10 12 22 22 16 10 12 12 13
52   13   25   15   10   11   14   12   12   10   13   11   29   15   9   9    11   11   25   14   19   33   13   15   15   16   11 12 18 23 17 16 20 18 34 39 14 11 11 8 17 17 8 11 10 8 11 10 12 22 24 15 10 12 12 13
53   13   25   14   10   11   15   12   12   11   13   11   32   15   9   10   11   11   24   15   20   31   12   15   15   16   10 12 19 22 17 16 20 20 36 38 13 12 11 9 17 17 8 12 10 8 11 10 12 22 22 16 10 12 10 13
           BDBEBFBGBH BI BJ BKBLBMBNBOBPBQBR BS BT BU BV BW BX BY BZ                          CA CB CC CD CE CF CG CH CI CJ CK CL CM CN CO                                 CR CT
                                                                                                                                                                  CP CQ CS CU
         1
olishCladesUpdate/Type.xls                                                  Results Columns                     Do not type or copy into the blue cells 46 Top ranked markers
         2                                                                   ↓        ↓                       ↓                                        Suggestion from SBP sheet:
         3 8 14 25 21 12 12 11 13 12 11 12 13          < Modal Haplotype                                                                                ##### Cutoff     >>> Step (m
         4                                                                                                                                              ##### Gap        Do not type
         5                                                                                                                                              ##### Best SBP
         6                                                                                                                                             Total for each sample is in this
         7                                                          Notes ↓                                                                            (Total = Genetic Distance = ste
         8                                             ↓Project Sequence                                            User adjusts these 3 red numbers > 45 Number of Markers to
         9                                                 ↓ Kit Number     16 11 12 11        5 4 4 4 4 5 5                                              11 Cutoff
        10 4 4 4 4 4 4 4 4 4 4 4 4                     < Mask                1 4 2 2           3 4 4 4 3 2 2                                               2 Gap
        11 28 - 5 - 39 28 - 45 2 28 28 -               < Rank                8 6 9 10         10 10 10 10 10 11 11                                        24 Number of samples in t
        12 4 0 4 0 4 4 0 4 4 4 4 0 0 0 0 < Net Mask                         37 42 28 14        9 7.0 7.0 7.0 9.3 22 22                                  ##### SBP                 385
        13 450444481520446617568487572640492565464e 464g DYS
                                                  464f <            ↓ Name 67 65 64 62        45 42 40 38 37 34 23                                        42 Net Markers          a
        14 8 13 25 21 12 12 11 13 12 11 12 13           27 31257             8 5 4 3           0 0 0 0 0 0 0                                               0             00000
        15 8 14 25 21 12 12 10 13 12 11 12 12           30 N3646            12 10 9 8          0 0 0 0 0 0 0                                               0             00000
        16 8 13 25 21 12 12 11 13 12 11 12 13            3 N13715            8 7 6 5           1 1 1 0 0 0 0                                               1             00000
        17 8 13 24 21 12 12 10 13 12 11 12 13           28 N18946           14 13 10 8         2 1 1 1 1 1 1                                               1             00000
        18 8 14 25 21 12 12 11 13 12 11 12 13           29 85265             6 5 5 2           1 1 1 1 1 0 0                                               1             00000
        19 8 15 25 21 12 12 11 13 12 11 12 12           36 76637            15 12 11 9         1 1 1 1 0 0 0                                               1             00000
        20 8 14 25 20 12 12 11 14 11 11 12 13           26 4623             11 8 8 7           2 2 1 1 1 1 1                                               2             00000
        21 8 12 26 20 12 12 11 13 12 11 12 13           13 N30169           18 15 13 10        3 3 3 3 3 3 3                                               3             00100
        22 8 14 25 21 13 12 11 13 12 11 12 13           31 80813            10 9 9 8           3 3 3 3 3 1 1                                               3             00000
        23 8 14 25 21 12 12 11 13 13 11 12 13           40 71825            18 15 9 9          4 3 2 1 1 1 1                                               3             10000
        24 8 14 25 22 13 12 11 13 11 11 12 13            7 64924            19 18 15 13        8 8 8 8 7 5 5                                               8             00201
        25 8 14 23 21 12 12 11 13 11 11 12 13           16 83222            17 16 15 15        8 8 8 8 8 8 8                                               8             00101
        26 8 14 26 21 13 12 11 13 11 11 12 13 16        20 49093            18 16 14 13        8 8 8 8 7 4 4                                               8             00101
        27 8 14 23 21 12 12 11 13 10 11 12 13            1 49666            23 21 20 19        9 9 9 9 9 9 9                                               9             00101
        28 8 14 23 21 12 12 11 13 11 11 12 13            2 74991            20 18 17 16        9 9 9 9 9 9 9                                               9             00111
        29 8 15 23 22 12 12 11 13 11 11 12 13            6 65205            21 20 20 19        9 9 9 9 9 8 8                                               9             00201
        30 8 14 23 21 12 12 11 13 10 11 12 13           14 2805             22 20 19 17        9 9 9 8 8 8 8                                               9             00101
        31 8 13 23 21 12 12 11 13 11 11 12 12           24 57872            22 20 19 17        9 9 9 9 9 9 9                                               9             00111
        32 8 14 23 22 12 12 11 13 11 11 12 13           32 91748            20 18 17 15        9 9 9 9 9 8 8                                               9             00001
        33 8 14 23 21 12 12 11 13 11 11 12 13            9 N17933           21 19 17 16       10 10 10 10 10 9 9                                          10             00201
        34 8 14 25 21 13 12 11 13 11 11 12 13           11 N11424           19 17 15 14       10 10 10 10 9 7 7                                           10             00202
        35 8 14 23 21 12 12 11 13 10 11 12 13           15 39003            26 24 20 18       10 10 10 9 9 9 9                                            10             00101
        36 8 14 23 21 12 12 11 13 11 11 12 13           33 N16931           21 19 18 15       10 10 10 10 10 9 9                                          10             00011
        37 8 14 23 21 12 12 11 13 11 11 12 14           35 34835            23 22 22 21       10 10 10 10 9 9 9                                           10             00101
        38 8 14 23 21 12 12 11 13 11 11 12 13           10 N18269           24 22 22 20       11 11 11 11 11 11 11                                        11             00201
        39 8 13 21 21 12 12 11 13 11 11 12 13           17 82051            25 23 22 19       11 11 11 10 10 10 10                                        11             00101
        40 8 12 24 21 13 12 11 13 11 11 12 12           19 77875            22 20 20 20       11 11 11 10 10 9 9                                          11             00101
        41 8 14 23 21 12 12 11 13 11 11 12 13           22 N6668            18 15 15 13       11 11 11 11 11 10 10                                        11             00111
        42 8 14 23 21 12 12 11 13 11 11 12 13           23 N14048           17 14 14 13       11 11 11 11 11 10 10                                        11             00111
        43 8 13 23 21 12 12 11 13 11 11 12 13           34 N38418           28 25 24 22       11 11 11 10 10 9 9                                          11             00012
        44 8 13 23 21 12 12 11 15 11 11 12 12           39 84103            22 19 17 17       12 11 8 8 8 7 7                                             11             10111
        45 8 13 27 21 13 12 11 14 11 11 12 13            8 83153            20 19 18 17       12 12 11 11 11 8 8                                          12             00201
        46 8 13 23 22 13 12 11 13 11 11 12 12           25 N8570            24 22 21 18       12 12 12 12 12 10 10                                        12             00111
        47 8 14 24 22 13 12 11 13 11 11 12 13           37 N38416           30 29 25 21       12 12 12 12 12 10 10                                        12             00112
        48 8 14 26 21 13 12 11 13 11 11 12 13           38 N42486           24 23 20 18       13 12 11 10 9 7 7                                           12             10201
     BDBEBFBGBH BI BJ BKBLBMBNBOBPBQBR BS          BT BU BV BW BX BY BZ CA   CB   CC   CD   CE   CF   CG CH CI CJ CK CL CM CN   CO   CP    CR CT
                                                                                                                                          CQ CS CU
49    8 14 22 21 13 12 11 13 11 11 12 12 16 18   N17829     24 23 20 20 13   13   13   13   12   10   10                        13        00101
50    8 14 23 21 12 12 11 13 11 11 12 13    21   96332      23 21 19 18 13   13   13   13   13   13   13                        13        00111
51    8 13 23 22 12 12 11 13 11 11 12 13    12   68550      29 27 27 23 14   14   14   13   13   13   13                        14        00211
52    8 15 23 21 12 12 11 13 11 11 12 13     5   13282      28 27 27 23 17   16   16   15   14   13   13                        16        00201
53    8 14 24 21 12 12 11 13 10 11 12 12     4   N30333     32 30 29 27 20   19   19   18   18   16   16                        19        00301
                 CW CY DA DC DE DG DIDJ DL DN DP DR DT DV DX DZ EB ED EF EH EK EM EO EQ ES EU EW EY FA FC FE FG FI
               CV CX CZ DB DD DF DH DK DM DO DQ DS DU DW DY EA EC EE EG EIEJ EL EN EP ER ET EV EX EZ FB FD FF FH FJ
           1                                                                                                                                     389b
           2                                                                                                                        389-2 minus 389-1
           3
    >>> Step (mutation count) by marker; below row 13 >>>>>>>>>                                                                          Modal      17
    Do not 4
           type or copy into the mutation count, or into the Total                                        This column is used by the TypeRank sheet ↓
           5                                                                                                                                       ^
           6
 ample is in this column below row 13
c Distance7 step = total count)
            =
           8
  of Markers to Consider, by Rank
           9                                                                                                                                       ^
          10
          11
  of samples in type       389-2                                                                 425                                  464 Result ↓
          12 385                459              464           YCAII CDY         395               413                                    464
          13 b             ^ a b                 a bc d        a b   a b         a b             ^ a b                                    e f g ^
          14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 17
          15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 17
          16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 17
          17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 # 17
          18 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 18
          19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 17
          20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 # 17
          21 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 # 17
          22 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 # 17
          23 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          24 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 # 16
          25 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          26 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 # 16
          27 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 # 17
          28 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          29 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 18
          30 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 # 17
          31 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          32 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          33 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          34 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 # 16
          35 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 # 17
          36 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 18
          37 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          38 0 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          39 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          40 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 # 17
          41 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          42 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          43 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
          44 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 2 1 0 0 0 0 0 0 # 18
          45 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 1 0 0 1 1 0 0 0 0 0 0 # 16
          46 0 0 0 0 1 1 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 0 0 1 0 0 0 0 0 0 # 17
          47 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 # 16
          48 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 # 17
       CW CY DA DC DE DG DIDJ DL DN DP DR DT DV DX DZ EB ED EF EH EK EM EO EQ ES EU EW EY FA FC FE FG FI
     CV CX CZ DB DD DF DH DK DM DO DQ DS DU DW DY EA EC EE EG EIEJ EL EN EP ER ET EV EX EZ FB FD FF FH FJ
49   0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 1 0 0 0 1 0 0 0 0 0 0 # 16
50   0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
51   1 0 0 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 17
52   0 0 0 0 0 0 1 0 0 1 0 0 2 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 0 0 0 # 16
53   1 0 0 0 0 0 2 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 # 19
     A      B C D E F G H I J K L M N O P Q R S T U V W X Y Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN
 1         Type Rank, Mode, etc          Peter Gwozdz          Be careful not to delete column DE when deleting old data below row 20 on this sheet            For instructions, click Sheet "T
 2                Enter the type data below row 20. If no type data is available, enter the initial modal in row 21, and delete all data below row 21. The modal function fails if a marker has n
 3   13    25    17    10    10   14   12   12    10   13   11   30   16     9   10   11   11    23    14    20    31    12   15   16   16   11   11   19   23   16   16    18    19    34   39   13   11    11     8    17
 4
 5    13    25    17    10    10 14 12       12    10 13     11 30     16     9 10 11       11    23    14    20    31    12 15 16 16 11          11 19 23 16          16    18    19   34 38 14        11    11    8     17
 6    13    25    17    10    10 14 12       12    10 13     11 30     17     9 10 11       11    23    14    20    32    13 15 16 16 11          11 19 23 16          16    18    19   35 39 13        11    11    8     17
 7    13    25    17    10    10 14 12       12    10 13     11 30     17     9 10 11       11    23    14    20    32    12 15 16 16 11          11 19 23 16          16    18    19   35 39 13        11    11    8     17
 8     -     -     -     -     - - -          -     - -       - -       1     - - -          -     -     -     -     1    1 - - - -                - - - -              -     -     -    1 0 0           -     -     -     -
 9     1    0      1    1      1 1 0          1     0 1       1 1       0     1 1 1          1    1      1    1      0    0 0 0 0 1                1 0 0 0              0     0     0    0 0 0           1     1    1      1
10    40    40    40    40    40 40 40       40    40 40     40 40     40    40 40 40       40    40    40    40    40    40 40 40 40 40          40 40 40 40          40    40    40   40 40 40        40    40    40    40
11    37    34    12    29    10 38 38       39    22 30     39 28     14    40 35 38       40    19    39    39    13    27 30 9 26 34           27 38 38 18          27    18    15   14 11 5         37    37    36    39
12   0.9   0.9   0.3   0.7   0.3 1.0 1.0    1.0   0.6 0.8   1.0 0.7   0.4   1.0 0.9 1.0    1.0   0.5   1.0   1.0   0.3   0.7 0.8 0.2 0.7 0.9      0.7 1.0 1.0 0.5     0.7   0.5   0.4   0.4 0.3 0.1    0.9   0.9   0.9   1.0
13    10    10    10    10    10 10 10       10    10 10     10 10     10    10 10 10       10    10    10    10    10    10 10 10 10 10          10 10 10 10          10    10    10   10 10 10        10    10    10    10
14     9    8      9    10    10 10 9        10     6 9      10 9       5    10 9 10        10    9     10    10     4    8 9 7 10 9              10 9 10 5             7     4     5    3 3 2          10    10    10    10
15   0.9   0.8   0.9   1.0   1.0 1.0 0.9    1.0   0.6 0.9   1.0 0.9   0.5   1.0 0.9 1.0    1.0   0.9   1.0   1.0   0.4   0.8 0.9 0.7 1.0 0.9      1.0 0.9 1.0 0.5     0.7   0.4   0.5   0.3 0.3 0.2    1.0   1.0   1.0   1.0
16   0.8   0.6   2.4   1.4   4.0 1.1 0.8    1.0   0.4 1.0   1.0 1.0   0.4   1.0 0.8 1.1    1.0   1.5   1.0   1.0   0.2   0.8 1.0 1.5 1.5 0.9      1.5 0.8 1.1 0.3     0.5   0.1   0.3   0.1 0.1 0.1    1.1   1.1   1.1   1.0
17    45    54     3    10     1 14 47       20    58 39     20 18     59    28 44 14       28    7     20    20    63    49 39 8 6 43             9 47 14 61          56    64    60   66 65 67        12    12    11    20
18    45     -     3    10     1 14 -        20     - 39     20 18      -    28 44 14       28    7     20    20     -     - 39 8 6 43             9 - 14 -             -     -     -    - - -          12    12    11    20
19     1    0      1    1      1 1 0          1     0 1       1 1       0     1 1 1          1    1      1    1      0    0 1 1 1 1                1 0 1 0              0     0     0    0 0 0           1     1    1      1
20   393   390   19    391   385a385b426    388   43989-1
                                                     3         3
                                                            39289-2   458   459a459b455    454   447   437   448   449   464a464b464c464d460      GATAYCaYCb456       607   576   570   CDaCDb442      438   531   578   395a
21    13    25    17    10    10 14 12       12    10 13     11 30     16     9 10 11       11    23    14    20    31    12 15 15 16 11          11 19 23 16          17    17    19   36 38 12        11    11    8     17
22    13    25    17    10    10 14 12       12    11 13     11 30     17     9 10 11       11    23    14    20    32    12 15 16 16 11          11 19 23 15          16    18    20   35 38 14        11    11    8     17
23    13    25    17    10    10 14 12       12    10 13     11 31     17     9 10 11       11    23    14    20    34    12 15 16 16 11          11 19 23 16          16    18    19   34 39 12        11    11    8     17
24    13    24    17    10    10 14 12       12    11 13     11 30     17     9 10 11       11    23    14    20    31    12 15 16 16 12          11 19 23 16          16    17    19   34 40 12        11    11    8     17
25    13    25    17    10    10 14 12       12    10 13     11 30     17     9 10 11       11    23    14    20    32    12 15 16 16 11          11 20 23 15          15    19    19   33 42 13        11    11    8     17
26    13    26    17    10    10 14 12       12    11 13     11 30     16     9 10 11       11    23    14    20    32    12 15 16 16 11          11 19 23 15          16    19    20   36 38 14        11    11    8     17
27    13    25    17    10    10 14 12       12    10 13     11 30     16     9 10 11       11    23    14    20    31    12 15 15 16 11          11 19 23 15          16    17    17   37 39 13        11    11    8     17
28    13    25    17    10    10 14 12       12    11 14     11 31     18     9 10 11       11    23    14    20    32    12 15 16 16 11          11 19 23 16          16    18    18   34 39 14        11    11    8     17
29    14    25    17    10    10 14 11       12    10 13     11 30     16     9 9 11        11    23    14    20    31    16 16 16 16 11          11 19 23 15          14    18    19   32 32 14        11    11    8     17
30    13    25    16    10    10 14 12       12    10 13     11 30     16     9 10 11       11    22    14    20    33    15 15 15 16 11          11 19 23 16          16    19    18   35 41 11        11    11    8     17
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     A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V W   X   Y   Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN
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      A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V W   X   Y   Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN
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              AO AP AQ AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF BG BH                         BI BJ BK BL BM BN BO BP BQ BR BS BT BU BV BW BX BY BZ CA CB
           1
ns, click Sheet "TypeDoc", in the file:       http://www.gwozdz.org/PolishCladesUpdate/Type.xls                                 Be careful not to delete column DE when delet
           2
 if a marker has no value with at least 2 samples at that value.
           3 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 14 25 21 12                             12    11    13    12    11    12    13     0   0    0 Current modal - a copy from the "Calculator" shee
           4                                                                                                                                            Use this row to construct a new modal with adjust
           5 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 14 25 21 12                              12    11    13    12    11    12    13    0   0    0 Modal - from data below on this sheet
           6 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 14 25 21 12                              12    11    13    12    11    12    13    0   0    0 Average
           7 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 14 25 21 12                              12    11    13    12    11    12    13    0   0    0 Median
           8 - - - - - - - - - - - - - - - - - - - -                                                -     -     -     -     -     -     -    -   -    - Discrepancies - Current vs Average if all 4 are no
           9 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 1 0 1 0 1                                                1    0      1    1     1     1      0               Net mask markers after adjustment
          10 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40                           40    40    40    40    40    40    40    2 0 0 Count of samples that have this marker, from "Ca
          11 38 40 32 40 40 18 32 40 28 39 33 39 40 39 28 40 25 10 32 30                           40    38    37    8     40    40    31    0 0 0 Count of this modal value, "Calculator"
          12 1.0 1.0 0.8 1.0 1.0 0.5 0.8 1.0 0.7 1.0 0.8 1.0 1.0 1.0 0.7 1.0 0.6 0.3 0.8 0.8      1.0   1.0   0.9   0.2   1.0   1.0   0.8   2.0 2.0 2.0 Fraction
          13 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10                           10    10    10    10    10    10    10    0 0 0 Count of samples that have this marker, this sheet
          14 10 10 9 10 10 10 8 10 9 10 8 10 10 10 7 10 5 8 8 9                                    10    8      9    8     10    10     8    0 0 0 Count of this modal value , this sheet
          15 1.0 1.0 0.9 1.0 1.0 1.0 0.8 1.0 0.9 1.0 0.8 1.0 1.0 1.0 0.7 1.0 0.5 0.8 0.8 0.9      1.0   0.8   0.9   0.8   1.0   1.0   0.8   0.0 0.0 0.0 Fraction                       User does not adju
          16 1.1 1.0 0.9 1.0 1.0 2.2 0.6 1.0 1.0 1.0 0.6 1.0 1.0 1.0 0.5 1.0 0.2 2.0 0.6 1.0      1.0   0.5   0.8   2.6   1.0   1.0   0.7   0.0 0.0 0.0 Concentration                  45 Number of ma
          17 14 28 42 28 28 4 51 28 18 20 53 20 28 20 57 28 62 5 51 39                             28    55    45    2     28    28    50               Rank                           46 Ranking actua
          18 14 28 42 28 28 4 - 28 18 20 - 20 28 20 - 28 - 5 - 39                                  28     -    45    2     28    28     -               Best Ranked Signature          42 Net mask after
          19 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 1 0 1 0 1                                                1    0      1    1     1     1      0               Mask markers with ranking
          20 395b590 537 641 472 406 511 425 413a413b557 594 436 490 534 450 444 481 520 446      617   568   487   572   640   492   565   464e464f464g< DYS                 67 65 64 62 45 42
          21 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 13 25 21 12                              12    11    13    12    11    12    13               27 31257               8 5 4 3 0 0
          22 17 8 12 10 8 12 10 12 22 22 14 10 12 12 14 8 14 25 21 12                              12    10    13    12    11    12    12               30 N3646              12 10 9 8 0 0
          23 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 14 25 21 12                              12    11    13    12    11    12    13               29 85265               6 5 5 2 1 1
          24 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 13 25 21 12                              12    11    13    12    11    12    13                3 N13715              8 7 6 5 1 1
          25 17 8 12 10 8 12 11 12 22 22 15 10 12 12 13 8 13 24 21 12                              12    10    13    12    11    12    13               28 N18946             14 13 10 8 2 1
          26 17 8 11 10 8 12 10 12 22 22 16 10 12 12 14 8 15 25 21 12                              12    11    13    12    11    12    12               36 76637              15 12 11 9 1 1
          27 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 14 25 20 12                              12    11    14    11    11    12    13               26 4623               11 8 8 7 2 2
          28 17 8 12 10 8 12 10 12 21 22 15 10 12 12 14 8 14 25 21 13                              12    11    13    12    11    12    13               31 80813              10 9 9 8 3 3
          29 17 8 12 10 8 12 10 12 22 22 15 10 12 12 13 8 14 25 21 12                              12    11    13    13    11    12    13               40 71825              18 15 9 9 4 3
          30 17 8 12 10 8 12 9 12 22 22 15 10 12 12 13 8 12 26 20 12                               12    11    13    12    11    12    13               13 N30169             18 15 13 10 3 3
          31                                                                                                                                             7 64924              19 18 15 13 8 8
          32                                                                                                                                            20 49093              18 16 14 13 8 8
          33                                                                                                                                            16 83222              17 16 15 15 8 8
          34                                                                                                                                            32 91748              20 18 17 15 9 9
          35                                                                                                                                             2 74991              20 18 17 16 9 9
          36                                                                                                                                            14 2805               22 20 19 17 9 9
          37                                                                                                                                            24 57872              22 20 19 17 9 9
          38                                                                                                                                             1 49666              23 21 20 19 9 9
          39                                                                                                                                             6 65205              21 20 20 19 9 9
          40
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     AO AP AQ AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF BG BH BI BJ BK BL BM BN BO BP BQ BR BS   BT   BU BV BW BX BY BZ CA CB
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      AO AP AQ AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF BG BH BI BJ BK BL BM BN BO BP BQ BR BS   BT   BU BV BW BX BY BZ CA CB
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                CC CD CE CF CG CH CI CJ CK CL CMCN CO CP CQ CR CS CT CU CVCWCX CY CZ DA DB DC DD DE DF DG DH DI DJ DK DL DMDN DO
DE when 1    deleting old data below row 20 on this sheet                                        389-2 calculation column
             2                                                                                   Be careful not to paste anything over this
             3
Calculator" sheet                                                                                17
             4
odal with adjustments. Do not type in the rows with formulae
             5                                                                                   17
             6                                                                                   17
             7                                                                                   17
             8
 e if all 4 are not the same
             9
            10
arker, from "Calculator" data
            11
            12
arker, this13sheet
            14
            15
 r does not adjust these cells. Adjust the number of markers on the Calculator sheet
  Number16 markers to consider
             of
  Ranking17  actually used for the mask
            18
  Net mask after adjustment
            19                                                                                   Be careful not to delete this column
            20 40 38 37 34 23                                                                    389b
            21 0 0 0 0 0                                                                         17
            22 0 0 0 0 0                                                                         17
            23 1 1 1 0 0                                                                         18
            24 1 0 0 0 0                                                                         17
            25 1 1 1 1 1                                                                         17
            26 1 1 0 0 0                                                                         17
            27 1 1 1 1 1                                                                         17
            28 3 3 3 1 1                                                                         17
            29 2 1 1 1 1                                                                         17
            30 3 3 3 3 3                                                                         17
            31 8 8 7 5 5
            32 8 8 7 4 4
            33 8 8 8 8 8
            34 9 9 9 8 8
            35 9 9 9 9 9
            36 9 8 8 8 8
            37 9 9 9 9 9
            38 9 9 9 9 9
            39 9 9 9 8 8
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     CC CD CE CF CG CH CI CJ CK CL CMCN CO CP CQ CR CS CT CU CVCWCX CY CZ DA DB DC DD DE DF DG DH DI DJ DK DL DMDN DO
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      CC CD CE CF CG CH CI CJ CK CL CMCN CO CP CQ CR CS CT CU CVCWCX CY CZ DA DB DC DD DE DF DG DH DI DJ DK DL DMDN DO
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      Peter Gwozdz           Results:      #NAME? SBP = Statistical Background Percent
                                           #NAME? Statistical Mountain Number
70%   Confidence (70% is recommended) #NAME? Statistical (Mountain) Background
 11   Cutoff                                   11       Cutoff
 2    Gap                                       2       Gap
 3    Gap frequency display              Click sheet "SPD Doc" for instuctions
                                            To reduce the x-axis on the graph
                                    Delete cells at the bottom; all 5 of these columns
                              Do not delete the rows, just highlight the data & press Delete
                                Step         Total       Frequency       Gap       Display
                                  0             2            2             0           0
                                  1             6            4             1           0
                                  2             7            1             2           0
                                  3            10            3             3           0          Distribution
                                  4            10            0             4           0
                                                                             8
                                  5            10            0             57          0
                                  6            10            0             66          0




                                                                     Frequency
                                  7            10            0             75          0
                                  8            13            3             84          0
                                  9            19            6             93          0
                                 10            24            5           10.92         0
                                 11            31            7            11 1         3
                                 12            35            4            12 0         3
                                 13            37            2           12.1 0        05    10     15
                                 14            38            1            14           0           Step
                                 15            38            0            15           0
                                 16            39            1            16           0
                                 17            39            0            17           0
                                 18            39            0            18           0
                                 19            40            1            19           0
                                 20            40            0            20           0
                                 21            40            0            21           0
                                 22            40            0            22           0
                                 23            40            0            23           0
                                 24            40            0            24           0
                                 25            40            0            25           0
        12         End of the Gap
        24         Mountain Number
        11         Gap Number                          11 Cutoff integer check of user input
        5.5        Type Outliers                        2 Gap check
        5.5        (Mountain) Background                3 Gap display check
                   = Average Gap Frequency
  #NAME?           Statistical Gap Number                  SBP Trials            End = End of Gap = Cutoff + Gap -1
  #NAME?           Statistical Average Gap Frequency       Cutoff Gap Cutoff Gap End Mountain M+G Gap
                   = Statistical Background                                             Number          Number
    24.0           Size (of the Type)                                  11     2   12      24       35      11
  #NAME?           Size confidence minimum                   10    1   10     1   10      19       24       5
  #NAME?           Size confidence maximum                   10    2   10     2   11      19       31      12
                                                             10    3   10     3   12      19       35      16
Distribution                                                 11    1   11     1   11      24       31       7
                                                             11    3   11     3   13      24       37      13
                                                             12    1   12     1   12      31       35       4
                                                             12    2   12     2   13      31       37       6
                                                             12    3   12     3   14      31       38       7
                                                             9     0    9     1    9      13       19       6
                                              Gap            9     1    9     1    9      13       19       6
                                                             9     2    9     2   10      13       24      11
                                                             9     3    9     3   11      13       31      18
                                                             9     4    9     4   12      13       35      22
  15          20         25       30                         10    0   10     1   10      19       24       5
 Step                                                        10    4   10     4   13      19       37      18
                                                             11    0   11     1   11      24       31       7
                                                             11    4   11     4   14      24       38      14
                                                             12    0   12     1   12      31       35       4
                                                             12    4   12     4   15      31       38       7
                                                             13    0   13     1   13      35       37       2
                                                             13    1   13     1   13      35       37       2
                                                             13    2   13     2   14      35       38       3
                                                             13    3   13     3   15      35       38       3
                                                             13    4   13     4   16      35       39       4
              15.0%                   1.8    minimum from this column
           Poisson tail                       #NAME? minimum from this column
           for use in the Poisson function               #NAME? minimum SBP value from this column


                                             Statistical
Cutoff + Gap -1                    Gap          Gap
              Statistical Numbers Average     Average        SBP
              Mountain      Gap Frequency    Frequency
              #NAME? #####          5.5      #NAME?        #NAME? This is the requested Cutoff & Gap
              #NAME? #####          5.0      #NAME?        #NAME? These blue rows are the "neighbor" values
              #NAME? #####          6.0      #NAME?        #NAME?      Cutoff / Gap with +/- One
              #NAME? #####          5.3      #NAME?        #NAME?      There may be duplicates in here
              #NAME? #####          7.0      #NAME?        #NAME?      See if your values are "local minimums"
              #NAME? #####          4.3      #NAME?        #NAME?
              #NAME? #####          4.0      #NAME?        #NAME?
              #NAME? #####          3.0      #NAME?        #NAME?
              #NAME? #####          2.3      #NAME?        #NAME?
              #NAME? #####          6.0      #NAME?        #NAME? The rest of these are 2 counts beyond your values
              #NAME? #####          6.0      #NAME?        #NAME?      There may be "false minimums" at another gap beyond your gap
              #NAME? #####          5.5      #NAME?        #NAME?      And duplicates
              #NAME? #####          6.0      #NAME?        #NAME?
              #NAME? #####          5.5      #NAME?        #NAME?
              #NAME? #####          5.0      #NAME?        #NAME?
              #NAME? #####          4.5      #NAME?        #NAME?
              #NAME? #####          7.0      #NAME?        #NAME?
              #NAME? #####          3.5      #NAME?        #NAME?
              #NAME? #####          4.0      #NAME?        #NAME?
              #NAME? #####          1.8      #NAME?        #NAME?
              #NAME? #####          2.0      #NAME?        #NAME?
              #NAME? #####          2.0      #NAME?        #NAME?
              #NAME? #####          1.5      #NAME?        #NAME?
              #NAME? #####          1.0      #NAME?        #NAME?
              #NAME? #####          1.0      #NAME?        #NAME?
                         Poisson Confidence Interval (Demonstration)        Confidence Calculation

                                  4 Number of samples; must be an integer          40   Number of samples in the set; must be an integer
                                80% Enter the confidence                       90.0%    Probability
                                                                            #NAME?      Confidence Interval Lower Number
                          #NAME? Calculated Low Confidence Limit            #NAME?      Confidence Interval Upper Number
                          #NAME? Calculated High Confidence Limit

                         I downloaded the Poisson functions from:
                         http://statpages.org/confint.html
                         These Poisson functions are Macros
                         So Excel gives a warning when opening this file
                         Peter Gwozdz




er gap beyond your gap
 samples in the set; must be an integer

e Interval Lower Number
e Interval Upper Number

                                          This column finds the recommended cutoff
                                                     This column finds the recommended gap
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
                                           #NAME? #NAME?
     A      B C D E F G H I J K L M N O P Q R S T U V W X Y Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN
 1         Type Data for ASD            Peter Gwozdz           For instructions, click Sheet "TypeDoc", in the file: http://www.gwozdz.org/PolishCladesUpdate/Type.xls
 2                 Type or copy the modal haplotype into row 3
 3   13    25    17    10    10   14   12   12    10   13   11   30   16     9   10   11   11    23    14    20    31    12   15   16   16   11   11   19   23   16   16    18    19    34   39   13   11    11     8    17
 4
 5                     Copy the Type data below row 20
 6
 7
 8
 9
10
11
12
13   10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
14    9 8 9 10 10 10 9 10 6 9 10 9 5 10 9 10 10 9 10 10 4 8 9 7 10 9 10 9 10 5 7 4 5 3 3 2 10 10 10 10
15   0.9 0.8 0.9 1.0 1.0 1.0 0.9 1.0 0.6 0.9 1.0 0.9 0.5 1.0 0.9 1.0 1.0 0.9 1.0 1.0 0.4 0.8 0.9 0.7 1.0 0.9 1.0 0.9 1.0 0.5 0.7 0.4 0.5 0.3 0.3 0.2 1.0 1.0 1.0 1.0
16
17
18
19
20   393   390   19    391   385a385b426    388   43989-1
                                                    3         3
                                                            39289-2   458   459a459b455    454   447   437   448   449   464a464b464c464d460         YCaYCb456
                                                                                                                                                  GATA                607   576   570   CDaCDb442      438   531   578   395a
21    13    25    17    10    10 14 12       12    10 13     11 30     16    9 10 11        11    23    14    20    31    12 15 15 16 11          11 19 23 16          17    17    19   36 38 12        11    11    8     17
22    13    25    17    10    10 14 12       12    11 13     11 30     17    9 10 11        11    23    14    20    32    12 15 16 16 11          11 19 23 15          16    18    20   35 38 14        11    11    8     17
23    13    25    17    10    10 14 12       12    10 13     11 31     17    9 10 11        11    23    14    20    34    12 15 16 16 11          11 19 23 16          16    18    19   34 39 12        11    11    8     17
24    13    24    17    10    10 14 12       12    11 13     11 30     17    9 10 11        11    23    14    20    31    12 15 16 16 12          11 19 23 16          16    17    19   34 40 12        11    11    8     17
25    13    26    17    10    10 14 12       12    11 13     11 30     16    9 10 11        11    23    14    20    32    12 15 16 16 11          11 19 23 15          16    19    20   36 38 14        11    11    8     17
26    13    25    17    10    10 14 12       12    10 13     11 30     16    9 10 11        11    23    14    20    31    12 15 15 16 11          11 19 23 15          16    17    17   37 39 13        11    11    8     17
27    13    25    17    10    10 14 12       12    10 13     11 30     17    9 10 11        11    23    14    20    32    12 15 16 16 11          11 20 23 15          15    19    19   33 42 13        11    11    8     17
28    13    25    17    10    10 14 12       12    11 14     11 31     18    9 10 11        11    23    14    20    32    12 15 16 16 11          11 19 23 16          16    18    18   34 39 14        11    11    8     17
29    13    25    16    10    10 14 12       12    10 13     11 30     16    9 10 11        11    22    14    20    33    15 15 15 16 11          11 19 23 16          16    19    18   35 41 11        11    11    8     17
30    14    25    17    10    10 14 11       12    10 13     11 30     16    9 9 11         11    23    14    20    31    16 16 16 16 11          11 19 23 15          14    18    19   32 32 14        11    11    8     17
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     A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V W   X   Y   Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN
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      A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V W   X   Y   Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN
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     AO AP AQ AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF BG BH BI BJ BK BL BM BN BO BP BQ BR                                                                                BS       BT     BU BV BW BX BY BZ CA
 1
 2
 3   17   8    12    10     8    12    10    12    22   22   15   10    12    12    13     8    14    25    21    12    12    11    13    12    11    12    13   0   0 Current modal - a copy from the "Calculator" sheet
 4
 5
 6
 7
 8
 9
10
11
12
13   10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 0 0 Count of samples that have this marker, this sheet
14   10 10 9 10 10 10 8 10 9 10 8 10 10 10 7 10 5 8 8 9 10 8 9 8 10 10 8 0 0 Count of this modal value , this sheet
15   1.0 1.0 0.9 1.0 1.0 1.0 0.8 1.0 0.9 1.0 0.8 1.0 1.0 1.0 0.7 1.0 0.5 0.8 0.8 0.9 1.0 0.8 0.9 0.8 1.0 1.0 0.8 0.0 0.0 Fraction
16
17
18
19
20   395b590   537   641   472   406   511   425   413a413b557    594   436   490   534   450   444   481   520   446   617   568   487   572   640   492   565 464e464f< DYS
21    17 8      12    10    8     12    10    12    22 22 15       10    12    12    13    8     13    25    21    12    12    11    13    12    11    12    13              27     31257
22    17 8      12    10    8     12    10    12    22 22 14       10    12    12    14    8     14    25    21    12    12    10    13    12    11    12    12              30     N3646
23    17 8      12    10    8     12    10    12    22 22 15       10    12    12    13    8     14    25    21    12    12    11    13    12    11    12    13              29     85265
24    17 8      12    10    8     12    10    12    22 22 15       10    12    12    13    8     13    25    21    12    12    11    13    12    11    12    13               3     N13715
25    17 8      11    10    8     12    10    12    22 22 16       10    12    12    14    8     15    25    21    12    12    11    13    12    11    12    12              36     76637
26    17 8      12    10    8     12    10    12    22 22 15       10    12    12    13    8     14    25    20    12    12    11    14    11    11    12    13              26     4623
27    17 8      12    10    8     12    11    12    22 22 15       10    12    12    13    8     13    24    21    12    12    10    13    12    11    12    13              28     N18946
28    17 8      12    10    8     12    10    12    21 22 15       10    12    12    14    8     14    25    21    13    12    11    13    12    11    12    13              31     80813
29    17 8      12    10    8     12     9    12    22 22 15       10    12    12    13    8     12    26    20    12    12    11    13    12    11    12    13              13     N30169
30    17 8      12    10    8     12    10    12    22 22 15       10    12    12    13    8     14    25    21    12    12    11    13    13    11    12    13              40     71825
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     AO AP AQ AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF BG BH BI BJ BK BL BM BN BO BP BQ BR   BS   BT   BU BV BW BX BY BZ CA
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      AO AP AQ AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF BG BH BI BJ BK BL BM BN BO BP BQ BR   BS   BT   BU BV BW BX BY BZ CA
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     CB CC CD CE CF CG CH CI CJ CK CL CMCN CO CP CQ CR CS CT CU CVCWCX CY CZ DA DB DC DD DE DF DG DH DI DJ DK DL DMDN
 1                                                                                    389-2 calculation column
 2                                                                                    Be careful not to paste anything over this
 3                                                                                    17
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19                                                                                           Be careful not to delete this column
20                                                                                           389b
21                                                                                           17
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     CB CC CD CE CF CG CH CI CJ CK CL CMCN CO CP CQ CR CS CT CU CVCWCX CY CZ DA DB DC DD DE DF DG DH DI DJ DK DL DMDN
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      CB CC CD CE CF CG CH CI CJ CK CL CMCN CO CP CQ CR CS CT CU CVCWCX CY CZ DA DB DC DD DE DF DG DH DI DJ DK DL DMDN
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       A    B C D E F G H I J K L                        M          N         O       P        Q      R        S      T       U       V       W       X         Y         Z
 1         ASD            Peter Gwozdz        For instructions, click Sheet "ASD Doc", in the file:        http://www.gwozdz.org/PolishCladesUpdate/Type.xls
 2         Column A is input data
 3    25 < Years per generation; may be changed           DYS               393     390       19     391     385a    385b    426     388     439    389-1      392      389-2
 4                                                        ASD             0.09000 0.20000 0.09000 0.00000 0.00000 0.00000 0.09000 0.00000 0.24000 0.09000 0.00000 0.09000
 5   Mutation Rates >>>              Chandler Mutation Rates              0.00076 0.00311 0.00151 0.00265 0.00226 0.00226 0.00009 0.00022 0.00477 0.00186 0.00052 0.00242
 6                  Age in generations = ASD divided by rate                   118      64        60     0        0       0   1000       0      50      48          0       37
 7                                                       Years               2,961 1,608 1,490           0        0       0 25,000       0 1,258 1,210              0      930
 8                     Averages by various sets of markers:                                                                                        Average of first 12 markers
 9                              Average ASD; all 67 markers 0.28537                                                                                                    0.07417
10                          Chandler Mutation Rates Average 0.00335                                                                                                    0.00187
11                  Age in generations = ASD divided by rate           85                                                                                                   40
12                                               Age in years 2,131                                                                                                        992
13                                                   Thomas:                  1       2        3      4                                                         5
14                   Average ASD with the 5 Thomas markers 0.076 (Compare to Thomas average = 0.2226)
15                                              Thomas Rate 0.00210
16                  Age in generations = ASD divided by rate           36
17                                               Age in years        905 (Compare to Thomas 2,650)
18                                                      Mask:
19                  Masks are explained in the Documentation
20                  To specify which markers to use for ASD:
21   Mask >>>           Type or copy a mask into this row >>                  4       4        4      4                       4       4       4       4         4         4
22                                                      Count                 1       1        1      1        -       -      1       1       1       1         1         1
23                                        Number of Markers         59
24                                                        ASD               0.09     0.2     0.09     0                      0.09     0     0.24     0.09       0        0.09
25                                                        Rate             0.0008 0.0031 0.0015 0.0027                      9E-05 0.0002 0.0048 0.0019 0.0005 0.0024
26                           Average ASD; selected markers 0.14119
27                                               Average rate 0.00214
28                                                Generations          66
29                                                       Years 1,646
30
31                                                  Mask Tool: Be sure to use "Paste Special, Values" when copying a mask to another location
32   5,000 < Set the limit for the number of years in the mask
33                                                  Years Limit
34                                    Rank; oldest = 1, 2, 3 …             11        19       21       37      37       37        1        37        25       26       37       28
35                                            Highlight > Limit             -         -        -        -       -        -     25,000       -         -        -        -        -
36               Mask for all markers below the "Years Limit"               4         4        4        4       4        4        0         4         4        4        4        4
37
38                                                       DYS                393      390       19      391      385a     385b     426      388      439      389-1     392     389-2
39                                           Infinite Alleles:
40   10% < Limit for Fraction Mutated                            Set the limit in the red cell to the left for the percent of samples mutated (not the modal value)
41                                      Number of Samples                     10         10        10        10        10                10        10      10       10    10     10
42                         Number Mutated (not modal value)                    1          2         1         0         0                 1         0       4        1     0      1
43                                         Fraction Mutated                0.10000 0.20000 0.10000 0.00000 0.00000                    0.10000 0.00000 0.40000 0.10000 0.00000 0.10000
44                                              Generations                     132         64         66         0        0             1111          0      84       54    0      41
    A    B C D E F G H I J K L                   M      N     O       P       Q       R       S       T     U       V       W       X       Y       Z
45                                              Years         3289    1608    1656       0       0         27778       0    2096    1344       0    1033
46                            Infinite Alleles / ASD           1.11    1.00   1.11    1.00    1.00           1.11   1.00     1.67    1.11   1.00     1.11
47                        Markers Less Than Limit             -       -       -       1       1             -       1       -       -       1       -
48 Mask >>>            Enter 1 to Exclude a Marker
49 Mask >>>                Enter 1 to Add a Marker
50                                         Net Mask             0      0       0       1       1            0       1       0       0       1       0
51                                         Mutations            0      0       0       0       0            0       0       0       0       0       0
52               Total Mutations (values not modal)             1
53                              Number of Markers              26
54                                           Fraction       0.00000 0.00000 0.00000 0.00000 0.00000       0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
55                                 Average Fraction             0
56                                               Rate       0.00000 0.00000 0.00000 0.00265 0.00226       0.00000 0.00022 0.00000 0.00000 0.00052 0.00000
57                                     Average Rate          0.0007
58                                      Generations               0
59                                              Years             0
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      A   B C D E F G H   I   J   K L   M   N   O   P   Q   R   S   T   U   V   W   X   Y   Z
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                 AA      AB      AC       AD      AE      AF     AG       AH      AI      AJ      AK     AL     AM       AN      AO      AP       AQ      AR      AS      AT
          1
          2
          3      458     459a    459b    455     454     447     437     448     449     464a    464b     464c       464d   460   GATA YCa       YCb     456     607     576
          4    0.44000 0.00000 0.09000 0.00000 0.00000 0.09000 0.00000 0.00000 0.89000 2.01000 0.09000 0.21000 0.00000 0.09000 0.00000 0.09000 0.00000 0.25000 0.56000 0.60000
          5    0.00814 0.00132 0.00132 0.00016 0.00016 0.00264 0.00099 0.00135 0.00838 0.00566 0.00566 0.00566 0.00566 0.00402 0.00208 0.00123 0.00123 0.00735 0.00411 0.01022
          6          54       0     68       0       0      34       0       0     106     355      16         37         0    22     0     73       0      34     136      59
          7       1,351       0 1,705        0       0     852       0       0 2,655 8,878         398       928          0   560     0 1,829        0     850 3,406 1,468
          8
t 12 markers                                                                                   Average of first 25 markers
          9                                                                                                        0.18840
         10                                                                                                        0.00278
         11    Generations                                                                                               68
         12                                                                                                           1,694
         13                                                                                     Average of markers 13-25
         14                                                                                                        0.29385
         15                                                                                                        0.00362
         16                                                                                                              81
         17                                                                                                           2,028
         18
         19
         20
         21       4       4       4       4       4       4       4        4      4                                       4       4       4        4       4       4       4
         22       1       1       1       1       1       1       1        1      1        -       -      -       -       1       1       1        1       1       1       1
         23
         24     0.44     0    0.09     0      0    0.09            0        0    0.89                                    0.09      0    0.09     0    0.25   0.56    0.6
         25    0.0081 0.0013 0.0013 0.0002 0.0002 0.0026         0.001   0.0014 0.0084                                  0.004   0.0021 0.0012 0.0012 0.0074 0.0041 0.0102
         26
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         34      24      37       17      37      37      31      37      37      12       2       36    29      37      35      37       16      37      32      10       22
         35       -       -        -       -       -       -       -       -       -     8,878      -     -       -       -       -        -       -       -       -        -
         36      4        4        4       4       4       4       4      4        4       0       4     4        4       4      4         4       4       4       4        4
         37
         38      458    459a     459b    455     454     447     437      448    449     464a     464b   464c   464d    460     GATA     YCa      YCb    456      607     576
         39
         40
         41       10      10               10      10      10      10      10      10      10                             10      10      10               10      10      10
         42       5        1                0       0       1       0      0        6       4                              1      0        1                5       3       6
         43    0.50000 0.00000          0.00000 0.00000 0.10000 0.00000 0.00000 0.60000 0.20000                        0.10000 0.00000 0.10000          0.50000 0.30000 0.60000
         44          61      0                0       0       38      0       0       72      9                              25      0       41               68      73      59
     AA      AB      AC     AD      AE      AF      AG      AH      AI      AJ      AK   AL   AM     AN      AO      AP      AQ     AR      AS      AT
45    1536       0             0       0      947      0       0    1790      221                      622      0    1016           1701    1825    1468
46     1.14   1.00          1.00    1.00     1.11   1.00    1.00     0.67    0.02                     1.11   1.00     0.56           2.00    0.54    1.00
47    -       1             1       1        -      1       1       -        -                        -      1        -              -       -       -
48
49
50    0       1             1       1       0       1       1       0       0                        0       1       0              0       0       0
51    0       1             0       0       0       0       0       0       0                        0       0       0              0       0       0
52
53
54 0.00000 0.00000        0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000                  0.00000 0.00000 0.00000        0.00000 0.00000 0.00000
55
56 0.00000 0.00132        0.00016 0.00016 0.00000 0.00099 0.00135 0.00000 0.00000                  0.00000 0.00208 0.00000        0.00000 0.00000 0.00000
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      AA   AB   AC   AD   AE   AF   AG   AH   AI   AJ   AK   AL   AM   AN   AO   AP   AQ   AR   AS   AT
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       AU      AV       AW      AX      AY      AZ      BA      BB      BC       BD      BE      BF      BG      BH       BI      BJ     BK        BL      BM       BN
 1
 2
 3     570     CDa     CDb       442       438    531   578    395a    395b    590     537     641     472     406     511     425     413a    413b    557     594
 4   0.76000 2.04000 6.44000 1.09000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.09000 0.00000 0.00000 0.00000 0.20000 0.00000 0.09000 0.00000 0.20000 0.00000
 5   0.00790 0.03531 0.03531 0.00324 0.00055 0.00037 0.00008 0.00031 0.00031 0.00054 0.00057 0.00018 0.00001 0.00154 0.00128 0.00018 0.00202 0.00202 0.00321 0.00029
 6         96     58     182       336          0     0     0       0       0      0     158       0       0       0     156       0      45        0     62       0
 7      2,405 1,444 4,560 8,410                 0     0     0       0       0      0 3,947         0       0       0 3,906         0 1,114          0 1,558        0
 8                   Average of first 37 markers
 9                                       0.44946
10                                       0.00492
11                                             91
12                                          2,283
13                    Average of markers 26-37
14                                       0.99333
15                                       0.00938
16                                            106
17                                          2,648
18
19
20
21      4                       4       4       4       4       4        4        4       4       4       4       4       4       4       4        4        4       4
22      1       -        -      1       1       1       1       1        1        1       1       1       1       1       1       1       1        1        1       1
23
24    0.76                     1.09     0      0        0        0      0      0    0.09     0            0        0     0.2     0       0.09       0       0.2     0
25   0.0079                   0.0032 0.0006 0.0004    8E-05   0.0003 0.0003 0.0005 0.0006 0.0002        1E-05   0.0015 0.0013 0.0002    0.002     0.002   0.0032 0.0003
26
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34     13       23       7       3      37      37      37      37       37      37       8      37      37      37       9       37      27       37       20      37
35      -        -       -     8,410     -       -       -       -        -       -       -       -       -       -       -        -       -        -        -       -
36     4         4       4       0       4       4       4      4         4       4       4      4        4       4       4        4       4        4        4       4
37
38     570     CDa      CDb    442     438     531     578     395a     395b    590      537     641     472     406     511     425     413a     413b     557     594
39
40
41      10      10               10      10      10      10      10               10      10      10      10      10      10      10      10                 10      10
42      5        8                8       0       0       0      0                 0      1       0        0       0      2        0       1                  2       0
43   0.50000 0.70000          0.80000 0.00000 0.00000 0.00000 0.00000          0.00000 0.10000 0.00000 0.00000 0.00000 0.20000 0.00000 0.10000            0.20000 0.00000
44         63      10              247      0       0       0       0                0     175       0       0       0     156       0       25                 62      0
     AU      AV      AW     AX      AY      AZ      BA      BB      BC     BD      BE      BF     BG       BH      BI      BJ      BK      BL    BM       BN
45    1582     248          6173       0       0       0       0              0    4386       0       0       0    3906       0      619          1558       0
46     0.66   0.17           0.73   1.00    1.00    1.00    1.00           1.00     1.11   1.00    1.00    1.00     1.00   1.00     0.56           1.00   1.00
47    -       -              -      1       1       1       1              1        -      1       1       1       -       1        -             -       1
48
49
50    0       0             0       1       1       1       1              1       0       1       1       1       0       1       0              0       1
51    0       0             0       0       0       0       0              0       0       0       0       0       0       0       0              0       0
52
53
54 0.00000 0.00000        0.00000 0.00000 0.00000 0.00000 0.00000        0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000        0.00000 0.00000
55
56 0.00000 0.00000        0.00000 0.00055 0.00037 0.00008 0.00031        0.00054 0.00000 0.00018 0.00001 0.00154 0.00000 0.00018 0.00000        0.00000 0.00029
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      AU   AV   AW   AX   AY   AZ   BA   BB   BC   BD   BE   BF   BG   BH   BI   BJ   BK   BL   BM   BN
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       BO      BP      BQ      BR       BS      BT      BU       BV     BW       BX      BY       BZ      CA      CB      CC       CD CE CF CG CH           CI   CJ   CK
 1
 2
 3     436     490     534     450     444     481     520     446     617     568     487     572     640      492       565      DYS
 4   0.00000 0.00000 0.21000 0.00000 0.64000 0.20000 0.16000 0.09000 0.00000 0.16000 0.09000 0.20000 0.00000 0.00000 0.16000       ASD
 5   0.00018 0.00019 0.00832 0.00020 0.00321 0.00544 0.00245 0.00365 0.00042 0.00053 0.00097 0.00212 0.00034 0.00042 0.00087       Chandler Mutation Rates
 6         0       0      25       0     199      37      65      25       0     302      93      94       0         0       184   Age in generations = ASD divided by rate
 7         0       0     631       0 4,984       919 1,633       616       0 7,547 2,320 2,358             0         0 4,598       Years
 8                                                                                                    Average of all 67 markers
 9                                                                                                                      0.28537    Average ASD
10                                                                                                                      0.00335    Chandler Mutation Rates Average
11                                                                                                                            85   Age in generations = ASD divided by rate
12                                                                                                                         2,131   Years
13                                                                                                   Average of markers 38-67
14                                                                                                                      0.08300    Average ASD
15                                                                                                                      0.00141    Chandler Mutation Rates Average
16                                                                                                                            59   Age in generations = ASD divided by rate
17                                                                                                                         1,474   Years
18
19                                                                                                                                Compound Markers; Infinite Allele
20                                                                                                                          Modal 0 = Not mutated; 1 - Mutated
21      4       4       4       4        4       4       4       4        4       4       4        4      4      4      4   Count 10     9    6     9    2     10
22      1       1       1       1        1       1       1       1        1       1       1        1      1      1      1          385 459 464 YC CD 395
23                                                                                                                                  0    0    1     0    1      0
24      0      0    0.21     0    0.64    0.2   0.16   0.09     0    0.16                0.09     0.2     0      0    0.16          0    0    0     0    1      0
25   0.0002 0.0002 0.0083 0.0002 0.0032 0.0054 0.0025 0.0037 0.0004 0.0005              0.001   0.0021 0.0003 0.0004 0.0009         0    0    0     0    0      0
26                                                                                                                                  0    0    0     0    1      0
27                                                                                                                                  0    0    0     0    1      0
28                                                                                                                                  0    0    1     0    1      0
29                                                                                                                                  0    0    0     1    1      0
30                                                                                                                                  0    0    0     0    0      0
31                                                                                                                                  0    0    1     0    1      0
32                                                                                                                                  0    1    1     0    1      0
33
34     37      37       33      37       5      30       18      34      37       4       15      14      37      37       6
35      -       -        -       -       -       -        -       -       -     7,547      -       -       -       -       -
36     4        4        4       4       4       4        4      4        4       0       4       4        4       4       4
37
38    436      490     534     450      444     481     520     446      617     568     487     572      640     492     565      DYS
39
40
41      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10
42      0        0       3       0       5       2       2      1        0       2      1       2        0       0      2
43   0.00000 0.00000 0.30000 0.00000 0.50000 0.20000 0.20000 0.10000 0.00000 0.20000 0.10000 0.20000 0.00000 0.00000 0.20000
44         0       0       36      0      156      37      82      27      0      377    103       94      0       0     230
     BO      BP      BQ      BR      BS      BT      BU      BV      BW      BX      BY      BZ      CA      CB      CC CD CE CF CG CH   CI   CJ   CK
45       0       0     901       0    3894     919    2041     685       0    9434    2577    2358       0       0    5747
46    1.00    1.00    1.43    1.00     0.78   1.00     1.25   1.11    1.00    1.25    1.11     1.00   1.00    1.00     1.25
47    1       1       -       1       -       -       -       -       1       -       -       -       1       1       -
48
49
50    1       1       0       1       0       0       0       0       1       0       0       0       1       1       0
51    0       0       0       0       0       0       0       0       0       0       0       0       0       0       0
52
53
54 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
55
56 0.00018 0.00019 0.00000 0.00020 0.00000 0.00000 0.00000 0.00000 0.00042 0.00000 0.00000 0.00000 0.00034 0.00042 0.00000
57
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61
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64
65
66
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84
      BO   BP   BQ   BR   BS   BT   BU   BV   BW   BX   BY   BZ   CA   CB   CC   CD CE CF CG CH   CI   CJ   CK
 85
 86
 87
 88
 89
 90
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100
101
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               CL     CM       CN         CO         CP         CQ          CR         CS        CT         CU         CV         CW         CX         CY       CZ         DA     DB DC DD
           1               In this TRANSPOSE array, the "Years" are figured with ASD, copied from row 7, treating compound markers as individuals
           2                          But the "Mutations" are figured using "Infinite Alleles", copied from row 42; for compound markers the mutations are totaled in the "a" marker only
           3               Copy this array over to the right; use Paste, Special, Values                 The copy over here can be sorted by Rank
           4               Do not sort this "TRANSPOSE" array                                            Sort by Sequence to get back to standard order
           5                  Rank       DYS      Sequence Mutations Years                                 Rank       DYS      Sequence Mutations Years         Mask Notes
           6
vided by rate                  11         393         1           1          2,961                            1        426         7          1         25,000           One mutation out of 10 sa
           7                   19         390         2           2          1,608                            2       464a         22         4          8,878
           8                   21          19         3           1          1,490                            3        442         36         8          8,410
           9                   37         391         4           0               0                           4        568         62         2          7,547
         10                    37        385a         5           0               0                           5        444         57         5          4,984
vided by 11
          rate                 37        385b         6           0               0                           6        565         67         2          4,598
         12                     1         426         7           1        25,000                             7       CDb          35         0          4,560
         13                    37         388         8           0               0                           8        537         43         1          3,947
         14                    25         439         9           4          1,258                            9        511         47         2          3,906
         15                    26        389-1       10           1          1,210                           10        607         31         3          3,406
vided by 16
          rate                 37         392        11           0               0                          11        393         1          1          2,961
         17                    28        389-2       12           1            930                           12        449         21         6          2,655
         18                    24         458        13           5          1,351                           13        570         33         5          2,405
         19
s; Infinite Alleles            37        459a        14           1               0                          14        572         64         2          2,358
         20                    17        459b        15           0          1,705                           15        487         63         1          2,320
         21 9                  37         455        16           0               0                          16       YCa          28         1          1,829
         22 413                37         454        17           0               0                          17       459b         15         0          1,705
         23 0                  31         447        18           1            852                           18        520         59         2          1,633
         24 0                  37         437        19           0               0                          19        390         2          2          1,608
         25 0                  37         448        20           0               0                          20        557         51         2          1,558
         26 0                  12         449        21           6          2,655                           21         19         3          1          1,490
         27 0                   2        464a        22           4          8,878                           22        576         32         6          1,468
         28 0                  36        464b        23           0            398                           23       CDa          34         8          1,444
         29 0                  29        464c        24           0            928                           24        458         13         5          1,351
         30 1                  37        464d        25           0               0                          25        439         9          4          1,258
         31 0                  35         460        26           1            560                           26      389-1         10         1          1,210
         32 0                  37       GATA         27           0               0                          27       413a         49         1          1,114
         33                    16         YCa        28           1          1,829                           28      389-2         12         1            930
         34                    37        YCb         29           0               0                          29       464c         24         0            928
         35                    32         456        30           5            850                           30        481         58         2            919
         36                    10         607        31           3          3,406                           31        447         18         1            852
         37                    22         576        32           6          1,468                           32        456         30         5            850
         38                    13         570        33           5          2,405                           33        534         55         3            631
         39                    23         CDa        34           8          1,444                           34        446         60         1            616
         40                     7        CDb         35           0          4,560                           35        460         26         1            560
         41                     3         442        36           8          8,410                           36       464b         23         0            398
         42                    37         438        37           0               0                          37        391         4          0              0
         43                    37         531        38           0               0                          37       385a         5          0              0
         44                    37         578        39           0               0                          37       385b         6          0              0
     CL   CM   CN    CO    CP   CQ   CR      CS   CT   CU     CV    CW    CX   CY       CZ   DA   DB DC DD
45             37   395a   40    0       0             37     388    8     0        0
46             37   395b   41    0       0             37     392    11    0        0
47             37    590   42    0       0             37    459a    14    1        0
48              8    537   43    1   3,947             37     455    16    0        0
49             37    641   44    0       0             37     454    17    0        0
50             37    472   45    0       0             37     437    19    0        0
51             37    406   46    0       0             37     448    20    0        0
52              9    511   47    2   3,906             37    464d    25    0        0
53             37    425   48    0       0             37   GATA     27    0        0
54             27   413a   49    1   1,114             37    YCb     29    0        0
55             37   413b   50    0       0             37     438    37    0        0
56             20    557   51    2   1,558             37     531    38    0        0
57             37    594   52    0       0             37     578    39    0        0
58             37    436   53    0       0             37    395a    40    0        0
59             37    490   54    0       0             37    395b    41    0        0
60             33    534   55    3     631             37     590    42    0        0
61             37    450   56    0       0             37     641    44    0        0
62              5    444   57    5   4,984             37     472    45    0        0
63             30    481   58    2     919             37     406    46    0        0
64             18    520   59    2   1,633             37     425    48    0        0
65             34    446   60    1     616             37    413b    50    0        0
66             37    617   61    0       0             37     594    52    0        0
67              4    568   62    2   7,547             37     436    53    0        0
68             15    487   63    1   2,320             37     490    54    0        0
69             14    572   64    2   2,358             37     450    56    0        0
70             37    640   65    0       0             37     617    61    0        0
71             37    492   66    0       0             37     640    65    0        0
72              6    565   67    2   4,598             37     492    66    0        0
73
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      CL   CM   CN   CO   CP   CQ   CR   CS   CT   CU   CV   CW   CX   CY   CZ   DA   DB DC DD
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              DE DF DG DH DI DJ DK DL DMDN DO DP DQ DR DS DT DU DVDW
          1
          2
          3
          4
          5
          6
tion out of 10 samples in this slow mutating marker provides a very old age estimate
          7
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      A B C D E F G H I J K L M N O P Q R S T U V W X Y Z AA AB AC AD AE AF AG AH AI AJ AK AL AMANAO AP AQ AR AS AT AU AVAW
 1       Haplotypes
 2                     3 4
     39339019 391385a 85b26388439  389-1 392
                                          389-2 458459a 59b55454447437448449464a 64b64c 64d60GATA YCb
                                                        4 4                          4 4 4 4                              CDb              3 5
                                                                                                        YCa 456607576570CDa 442438531578395a 95b90537641472406511425413a
 3   13 25 17 10 10 14 12 12 10 13 11 30 16 9 10 11 11 23 14 20 31 12 15 16 16 11 11 19 23 16 16 18 19 34 39 13 11 11 8 17 17 8 12 10 8 12 10 12 22
 4   45 - 3 10 1 14 - 20 - 39 20 18 - 28 44 14 28 7 20 20 - - 39 8 6 43 9 - 14 - - - - - - - 12 12 11 20 14 28 42 28 28 4 - 28 18
 5   13 - 17 10 10 14 - 12 - 13 11 30 - 9 10 11 11 23 14 20 - - 15 16 16 11 11 - 23 - - - - - - - 11 11 8 17 17 8 12 10 8 12 - 12 22
 6   13 - 17 10 10 14 - 12 - 13 11 30 - 9 10 11 11 23 14 20 - - - - - 11 11 - - - - - - - - - 11 11 8 17 17 8 12 10 8 12 - 12 22
 7   Either modal from the 2 rows above can be copied elsewhere; use "Edit, Paste Special, Values" and delete the dashes
 8
 9   To compare the current modal haplotype to another, copy that other into the following row; the differences are highlighted on the next row:
10   14 25 17 10 10 13 12 12 10 13 11 30 16 9 10 11 11 23 14 20 31 12 15 16 16 11 11 19 23 16 16 18 19 34 39 13 11 11 8 17 17 8 12 10 8 12 10 12 22
11   13               14
12
13   Reference Haplotype Archive:       Delete the following examples and store your reference haplotypes here
14   13 25 17 10 10 14 12 12         13 11 30 16 9 10 11 11 23 14 20 31 12 15 16 16 11 11 19 23 16 16                  19              11 11 8 17 17 8 12 10 8 12 10 12 22
15          17 10 10          12     13 11 30           10 11 11 23              12 15 16 16       11                                  11 11 8           8 12 10 8 12         12
16          17     10                                             23                     16                                                                             12
17   13 25 17 10 10 14 12 12 10 13 11 30 16 9 10 11 11 23 14 20 31 12 15 16 16 11 11 19 23 16 16 18 19 34 39 13 11 11 8 17 17 8 12 10 8 12 10 12 22
18   13 25 17 10 10 14 12 12 10 13 11 17 17 9 10 11 11 23 14 20 32 12 15 16 16
19   13 25 16 10 11 14 12 12 10 13 11 30 16 9 10 11 11 24 14 20 32 12 15 15 16 11 11 19 23 16 16 18 19 34 39 14 11 11 8 17 17 8 12 10 8 11 10 12 22
20      Masks
21                     3 4
     39339019 391385a 85b26388439 389-1 392
                                         389-2 458459a 59b55454447437448449464a 64b64c 64d60GATA YCb
                                                        4 4                           4 4 4 4                                  CDb                   3 5
                                                                                                      YCa 456607576570CDa 442438531578395a 95b90537641472406511425413a
22   Any mask can be copied elsewhere; use "Edit, Paste Special, Values" and delete the dashes
23    3 0 3 3 3 3 0 3 0 3 3 3 0 3 3 3 3 3 3 3 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 3 3 0 3 3
24   13 25 16 10 11 14 12 12 10 13 11 30 16 9 10 11 11 23 14 20 32 12 15 15 16 11 11 19 23 16 16 18 19 34 39 14 11 11 8 17 17 8 12 10 8 12 10 12 22
25    = = 17 = 10 = = = = = = = = = = = = = = = - = = 16 = = = = = = = = = = = - = = = = = = = = = = = = =
26   Haplotype with high ranked non modal markers is in the row above. Equal values have equal =, comparing database modal (previous row) to the proposed type modal in Row 3 (a copy f
27    0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
28
29   Reference Mask Archive:              Delete the following examples and store your reference masks here
30    4 4 4 4 4 4 4 4             4   4    4 4
31    4 4 4 4 4 4 4 4             4   4    4 4 4 4 4 4 4 4 4 4 6 4 4 4 4
32    4 4 4 4 4 4 4 4             4   4    4 4 4 4 4 4 4 4 4 4 6 4 4 4 4 4 4 4 4                              4   4   5   4   6   6   4   4
33    4 4 4 4 4 4 4 4             4   4    4 4 4 4 4 4 4 4 4 4 6 4 4 4 4 4 4 4 4                              4   4   5   4   6   6   4   4   4   4   4   4   4   4   4   4   4   4   4   4
             AX AY AZ BA BB BC BD BE BF BG BH BI BJ BK BL BMBNBO BP BQ BR BS BT BU BV BWBX BY BZ CA CB CC CD CE CF CG CH CI CJ CK CL CMCN CO CP CQ
          1                                                                                                                 User does not adjust these cells. Adjust the number of markers on th
          2 413b57594436490534450444481520446617568487572640492565464e 64f 64g
                 5                                                           4 4                                              45 Number of markers to consider
          3 22 15 10 12 12 13 8 14 25 21 12 12 11 13 12 11 12 13 0 0 0 Current Modal from "Calculator"                        46 Ranking actually used for the mask
          4 20 - 20 28 20 - 28 - 5 - 39 28 - 45 2 28 28 -                            Rank                                     42 Net mask after adjustment
          5 22 - 10 12 12 - 8 - 25 - 12 12 - 13 12 11 12 -                           Modal based on current actual rank
          6 22 - 10 12 12 - 8 - 25 - 12 12 - 13 12 11 12 - - - - Modal based on net rank, row 12 on the "Calculator" sheet
          7
          8
          9
         10 22 15 10 12 12 13 8 14 25 21 12 12 11 13 12 11 12 13                     Another modal
         11                                                                          Markers from row 3 that differ
         12
         13                                                                          Reference Haplotype Archive: Markers Cutoff Gap
         14 22 15 10 12 12          8 14 25 21 12 12 11 13 12 11 12 13               P Definition 2008                  61
         15          10 12 12       8     25 21 12 12        12 11 12                P Definition 2009                  36
         16                               25                 12                      P Signature                         7
         17 22 15 10 12 12 13 8 14 25 21 12 12 11 13 12 11 12 13                     P Apr 2009                         67
         18                                                                          P(25) Oct 2007                     25
         19 22 15 10 12 12 13 8 14 23 21 12 12 11 13 11 11 12 13                     K Apr 2009                         67
         20
         21 413b57594436490534450444481520446617568487572640492565464e 64f
                 5                                                           4
         22                                                                            3 < Mask value for all markers
         23 3 0 3 3 3 0 3 0 3 0 3 3 0 3 3 3 3 0 0 0 0 ^ Mask with all net markers using this value
         24 22 15 10 12 12 13 8 14 23 21 12 12 11 13 11 11 12 13                     Modal for the Database on the Calculator sheet
         25 = = = = = = = = 25 = = = = = 12 = = =                                    Signature - Nonmodal markers (ranked) for the current modal in row 3 of the Calculator
         26
Row 3 (a copy from the Calculator). Ranking from TypeRank. Low ranked non modals have dash -.
         27 0 0 0 0 0 0 0 0 3 0 0 0 0 0 3 0 0 0                                      Mask for the signature, using the value above
         28
         29                                                                          Reference Mask Archive:            Markers
         30                                                                          M12                                12
         31                                                                          M25                                25
         32                                                                          M37                                37
         33 4 4 4 4 4 6 4 4 4 4 4 4 4 4 4 4 4 4                                      M67 My default mask                67
            CR CS CT CU CVCW
         1
of markers on the Calculator sheet
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        33

				
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