VISUALIZATION by SY096G2

VIEWS: 8 PAGES: 26

									Visualization and analysis of
microarray and gene ontology
data with treemaps
Eric H Baehrecke, Niem Dang, Ketan Babaria and Ben Shneiderman


                        Presenter: Priya
    Outline of the presentation

•   Background
•   Demo
•   Results and Discussion
•   Summary
Background
Challenges in visualization in
Bioinformatics
• Nature of data

• Limited computer monitor views of data complexity

• Limitations of typical browser presentation restrict data access

• Restrictions in viewing both qualitative (gene families or biological
  function) and quantitative (such as RNA level, p-value) information
  simultaneously.

• Need for an ideal platform to visualize multiple attributes
  simultaneously while allowing dynamic queries of data in the context
  of the GO classification.
Previous programs
• Visualize and query microarray data
  Spotfire
  Genespring
• Studies of GO
  FatiGO
  GoMiner
  MAPPFinder
  GoSurfer

  Severe lack in the ability to see patterns and obtain
  results on demand.
The solution – Treemap
• Treemaps facilitate visualization of both
  hierarchical and quantitative information.
• Treemaps are a space-filling visualization
  technique for hierarchical structures
• Show attributes of leaf nodes by size and
  color-coding
• Fills a critical void for genome researchers
  who want to integrate and query GO
  information with various quantitative data
Demo
Treemap Video Tutorial

• http://www.cs.umd.edu/hcil/treemap/doc4.
  1/toc.html

• http://www.cs.umd.edu/hcil/treemap/doc4.
  1/Video/TotalWithBuffer.html
Results and Discussion
Treemaps enable visual overviews of
complex genome data with details on
demand
Treemap allows access to data details
without leaving the overview of the data
Display regions and facts
• The data display and query window on the left
• The details of selected node on the top right
•  The control panel on the bottom right
• Data display and query window uses area to
  convey quantitative information
• One of the greatest strengths of treemaps, is
  that they provide an overview of the data while
  allowing details-on-demand with rapid updates
Overviews of genome data can be
rapidly obtained using Treemaps
Tools that facilitate visualization
and queries of genome data

• Size and color are two attributes that can
  be used to display quantitative differences
  in data using treemaps.
• Labels can also be assigned to different
  gene attributes.
• Users can zoom in and zoom out details
  on an area of interest.
Size, color, zoom
Color, size, label Demo

• http://www.cs.umd.edu/hcil/treemap/doc4.
  1/Video/ColorSizeLabelAttribute.html
Zoom
Zoom Demo

• http://www.cs.umd.edu/hcil/treemap/doc4.
  1/Video/Zooming.html
Treemaps allows users to query data in the
context of the entire GO classification with
little loss of time
Filters allow Treemap users to rapidly identify
genes of interest based on quantitative
attributes.
Hide Filters
Filter Demo

• http://www.cs.umd.edu/hcil/treemap/doc4.
  1/Video/Filtering.html
Genes can be displayed in distinct categories
based on quantitative attributes in Treemap
Useful research features
• Genome researchers require rapid access to details
  about genes such as map position within the genome,
  nucleotide and protein sequence, and literature
  published to name a few examples.
• Treemap 4.0 was adapted to contain a direct link to
  organism-specific websites within the main window of
  the lower right control panel.
• Any queried file that is selected while holding the control
  key will be saved to a tab-delimited file that can then be
  used in other software such as hierarchical clustering.
Summary – The Best Part of
Treemap
• Available open source code
• Excellent documentation
• Well-defined User Interface
• Helps make sense of the flood of
  information contained in the microarray
  data
• Increases the chances of understanding
  interesting patterns

								
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