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exploRase

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Instead of working to confirm a single hypothesis, we approach ... Allows GUI's to be written in R and integrated with GGobi's GUI via Rggobi2. Systems Biology ... – PowerPoint PPT presentation

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Title: exploRase


1
exploRase
  • Exploratory Data Analysis Software for Systems
    Biology

Michael Lawrence Co-Major Professors Di Cook and
Eve Wurtele
2
Outline
  • Background
  • Exploratory Data Analysis
  • Software Foundation
  • Systems Biology
  • Introduction to exploRase
  • Explore some data (demo)
  • The Future
  • Acknowledgments

explo R ase
3
Exploratory Data Analysis
  • Exploratory Data Analysis (EDA) is the art of
    being a data detective.
  • Instead of working to confirm a single
    hypothesis, we approach the data with a loose set
    of questions and/or suspicions and remain open to
    the unexpected.
  • We look for trends and patterns, as well as
    deviations from those expected.
  • Interactive graphics facilitate fluid data
    exploration and link different views of the data
    by visual cues.

4
Software Foundation
  • R Platform for statistical computing. Provides
    flexible data analysis via scripts.
  • GGobi Leading open-source interactive graphics
    software. Mature and actively developed. Based on
    the GTK toolkit.
  • Rggobi2 Link between R and GGobi. R's scripted
    analysis meets GGobi's interactive graphics.
    Overhaul of previous version.
  • RGtk2 Binding between R and GTK (open-source
    GUI toolkit). Allows GUI's to be written in R and
    integrated with GGobi's GUI via Rggobi2.

5
Systems Biology
  • The highly computational study of biology as a
    complex (biochemical) system.
  • Based on the analysis and modeling of metabolic,
    regulatory, and protein interaction networks.
  • Networks are often inferred from or analyzed in
    conjunction with high-throughput data
    (transcriptomics, proteomics, metabolomics)
    describing system states.

6
exploRase is...
  • An RGtk2-based graphical user interface that
    makes advanced statistical tools like R and GGobi
    more accessible to a systems biologist.
  • Facilitates loading of experimental data into R
    and GGobi.
  • Will serve as a front-end to BioConductor (R
    software for Bioinformatics).

7
Let's go exploring...
  • Dataset Arabidopsis transcriptomic data from 8k
    Affymetrix chips.
  • 2 Genotypes WT and bio1 (deficient in biotin
    synth)
  • Half of samples given biotin, total of 4
    treatments.
  • 2 replicates
  • Data Source Basil Nikolau's lab

8
The Future
  • Integrate with an interactive network
    visualization tool (for example Cytoscape)
  • Add more analysis methods and data aggregation
    utilities, with emphasis on interactivity
  • Refine user interface
  • Context sensitive help and wizards
  • Integration with other MetNet tools

9
Acknowledgments
  • GGobi Debby Swayne (ATT), Di Cook, Duncan
    Temple Lang (UC-Davis), Andreas Buja (Wharton),
    Heike Hofmann, Michael Lawrence, Hadley Wickham
  • Rggobi2 Hadley Wickham (R), Michael Lawrence
    (C), Original Duncan Temple Lang, Debby Swayne
  • RGtk2 Michael Lawrence, Original Duncan Temple

Money MGET Fellowship, NSF Arabidopsis 2010
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