Microarray Data Analysis Using B

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Microarray Data Analysis Using B Powered By Docstoc
					Microarray Data
Analysis Using BASE

Danny Park
MGH Microarray Core
March 15, 2004
You’ve got data!

 What was I asking? – remember your
  experimental design
 How do I analyze the data?
    – How do I find interesting stuff? – learn
      some analysis tools
    – How do I trust the results? – statistics is
      key
What was I asking?

 Typically: “which genes changed expression
  levels when I did ____”
 Common ____:
    – Binary conditions: knock out, treatment, etc
    – Continuous scales: time courses, levels of
      treatment, etc
    – Unordered discrete scales: multiple types of
      treatment or mutations
   This tutorial’s focus: binary experiments
How do I analyze the data?

   BASE – BioArray Software Environment
    – Data storage and distribution
    – Simple filtering, normalization, averaging,
      and statistics
    – Export/Download results to other tools
 MS Excel
 TIGR Multi Experiment Viewer (TMEV)
 This tutorial’s focus: using BASE
Today’s Presentation

 Demonstrate the most basic analysis
  techniques
 Using our most frequently used
  software (BASE)
 For the most common kind of
  experiments
Work Flow
      RNA       QC & label        Labeled cDNA

                                     hybridize

                                      Slides
 Researcher
                                   scan, segment

                                    Images &
    analysis   BASE      upload     data files
The Most Common experiment

   Two-sample comparison w/N replicates
    – KO vs. WT
    – Treated vs. untreated
    – Diseased vs. normal
    – Etc
   Question of interest: which genes are
    (most) differentially expressed?
             Experimental Design – naïve
                       A       B




From Gary Churchill,
Jackson Labs
             Experimental Design – tech repl
                       A       B




From Gary Churchill,
Jackson Labs
             Experimental Design – bio repl
           Treatment    A   A   B     B
           Biological
           Replicate

           Technical
           Replicate

           Dye

           Array
From Gary Churchill,
Jackson Labs
The Most Common Analysis
 Filter out bad spots
 Adjust low intensities
 Normalize – correct for non-linearities
  and dye inconsistencies
 Filter out dim spots
 Calculate average fold ratios and p-
  values per gene
 Rank, sort, filter, squint, sift data
 Export to other software
BASE @ MGH

 BASE is a microarray data storage and
  analysis package
 BASE resides on our web server
    – Data is stored at our facility
    – Computation is performed on our machines
   All you need is a web browser
    – https://base.mgh.harvard.edu/
    – A Microarray Core technician will provide you with
      a username, password, and experiment name
BASE – Login page
BASE – Login page
BASE – Login page
BASE – Login page
BASE – Logged in
BASE – Logged in
BASE – Sidebar

            Reporters
BASE – Sidebar

            Reporters
BASE – Sidebar

            Array LIMS
BASE – Sidebar

            Array LIMS
BASE – Sidebar

            Biomaterials
BASE – Sidebar

            Biomaterials
BASE – Sidebar

            Hybridizations
BASE – Sidebar

            Hybridizations
BASE – Sidebar

            Analyze Data
BASE – Sidebar

            Analyze Data
BASE – Sidebar

            Users
BASE – Sidebar

            Users
BASE – My Account




               Change your password
               and access defaults
BASE – My Account




               Change your password
               and access defaults
BASE – My Account




               Change your password
               and access defaults
BASE – My Account




               Change your password
               and access defaults
Find your experiment
Find your experiment
Find your experiment
Find your experiment
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Group slide data together
Group slide data together
                 Select the slides that measure
                 the same thing. Later in
                 analysis, they will be averaged
                 together. In this experiment,
                 all ten slides are replicates, so
                 there is only one grouping.
Group slide data together
                 Select the slides that measure
                 the same thing. Later in
                 analysis, they will be averaged
                 together. In this experiment,
                 all ten slides are replicates, so
                 there is only one grouping.
Group slide data together
                 Select the slides that measure
                 the same thing. Later in
                 analysis, they will be averaged
                 together. In this experiment,
                 all ten slides are replicates, so
                 there is only one grouping.
Group slide data together
Group slide data together
                 Give your data set a descriptive
                 name to distinguish it from
                 other slide groupings. In this
                 Myd88 knockout experiment,
                 there is only one grouping, so a
                 generic name is fine.
Group slide data together
                 Give your data set a descriptive
                 name to distinguish it from
                 other slide groupings. In this
                 Myd88 knockout experiment,
                 there is only one grouping, so a
                 generic name is fine.
Group slide data together
                 Give your data set a descriptive
                 name to distinguish it from
                 other slide groupings. In this
                 Myd88 knockout experiment,
                 there is only one grouping, so a
                 generic name is fine.
Analysis: Begin
Analysis: Begin
Analysis: Begin
Analysis: Begin
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                         “Bad” spots are
                         marked with a
                         negative Flag value.
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup


                           “Bad” spots are
                           marked with a
                           negative Flag value.


                 Oligos are annotated with
                 species codes, but control
                 spots are not. Set species to
                 your two-letter code of
                 choice (Mm, Hs, Dr, Pa, etc)
Analysis: Filter Setup




                  Naming the filter and
                  the child data set are
                  essential to reducing
                  confusion later.
Analysis: Filter Setup




                  Naming the filter and
                  the child data set are
                  essential to reducing
                  confusion later.
Analysis: Filter Setup




                  Naming the filter and
                  the child data set are
                  essential to reducing
                  confusion later.
Analysis: Filter Run
Analysis: Quality Data
Analysis: Quality Data
Analysis: Unfiltered Data
Analysis: Filter Parameters
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Check job status
Analysis: Check job status
Analysis: Check job status
Analysis: Check job status
Analysis: Check job status

                   “All done” indicates
                   the job is complete.
Analysis: Check job status

                   “All done” indicates
                   the job is complete.
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Change data set name
Analysis: Change data set name
Analysis: Change data set name
                  Change the name of
                  this set to “Intensity
                  limited Data”
Analysis: Change data set name
Analysis: Change data set name
Analysis: Change data set name
Analysis: Change data set name
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: Check job status
Analysis: Check job status
Analysis: LOWESS Output
Analysis: LOWESS Output
Analysis: LOWESS Output
                Change the name of
                this set to “Normalized
                Data” using the same
                steps as before.
Analysis: Change data set name
                  Change the name of
                  this set to “Normalized
                  Data” using the same
                  steps as before.
Analysis: Change data set name
                  Change the name of
                  this set to “Normalized
                  Data” using the same
                  steps as before.
Analysis: Filter Setup




                 Set up the filter as
                 indicated, hit
                 Add/Update on the
                 Gene filter, then hit
                 Accept and select the
                 resulting data set.
Analysis: Useful Data
Analysis: Useful Data
MA Plots: Raw Myd88 Data
MA Plots: Raw Myd88 Data
MA Plots: Raw Myd88 Data
MA Plots: Raw Myd88 Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Norm. Corr. Factor
MA Plots: Norm. Corr. Factor
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
Analysis: Useful Data
Analysis: Useful Data
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Change list name
Analysis: Change list name
Analysis: Change list name
                  Change the name of
                  this list as indicated
                  here.
Analysis: Change list name
                  Change the name of
                  this list as indicated
                  here.
Analysis: Change list name
Analysis: Change list name
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: t-test Setup
Analysis: t-test Setup
Analysis: t-test Setup
Analysis: t-test Setup
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: Change list name




                  Change the name of
                  this set to “myd88 p-
                  value” using the same
                  steps as before.
Analysis: Change list name




                  Change the name of
                  this set to “myd88 p-
                  value” using the same
                  steps as before.
Analysis: Change list name




                  Change the name of
                  this set to “myd88 p-
                  value” using the same
                  steps as before.
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: Experiment Explorer
Analysis: Experiment Explorer
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
                  Fill out the table as
                  indicated, then hit
                  Add/Update.
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: NCBI Links
EExplore: Gene List View
                  This additional row
                  will restrict hits to P
                  values of 5% or less.
EExplore: Gene List View
                  This additional row
                  will restrict hits to P
                  values of 5% or less.
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Gene List View
EExplore: Gene List View


                   Open MS Excel and tell
                   it to open the file you
                   downloaded (typically
                   called base.tsv).
EExplore: Gene List View


                   Open MS Excel and tell
                   it to open the file you
                   downloaded (typically
                   called base.tsv).
Have Fun!

 The rest of the analysis is largely driven
  by your biological understanding of the
  genes indicated in these lists. We
  cannot help much in the interpretation of
  this data.
 Don’t forget to go back to the raw data
  sets and repeat this entire analysis for
  any other slide groupings.
Acknowledgements
                                  MGH Microarray Core
                                  Glenn Short
 MGH Lipid Metabolism Unit        Jocelyn Burke
 Mason Freeman                    Najib El Messadi
 Harry Bjorkbacka                 Jason Frietas
                                  Zhiyong Ren


                             LUND (Sweden) Dept. Theoretical
MGH Molecular Biology        Physics & Dept. Oncology
Bioinformatics Group         Carl Troein
Chuck Cooper                 Lao H. Saal
Xiaowei Wang                 Johan Vallon-Christersson
                             Sofia Gruvberger
Harvard School of Public     Åke Borg
Health Biostatistics         Carsten Peterson
Xiaoman Li

				
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