Review of Array Express - PowerPoint PPT Presentation

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Review of Array Express

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Collection of microarray data published or unpublished. ... Supplemental data. Thank You. Georgia Tech. Dr. Wang. The Stokster. Ricky. Malcolm Thomas ... – PowerPoint PPT presentation

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Title: Review of Array Express


1
Review of Array Express
  • Thomas, M.D.
  • Georgia Institute of Technology
  • 21 June, 2006

2
What is a Microarray Database?
  • Collection of microarray data published or
    unpublished.
  • Includes cel files, samples, raw data, author,
    paper title, platform.

3
Ideal Database
  • Simple Ignorant Usage
  • Clearly presented features i.e. cel files,
    normalization, Q.C.
  • Large pool of organisms and platforms
  • Links to paper, author, and institution,
    citations
  • Probe locations

4
What do we use it for?
  • Create PADRE images
  • Compare complexities between more/less complex
    organisms
  • Over all goal Invalidate results

5
What is Array Express?
  • Public repository for microarray data
  • Objective Store-house for data, platforms
  • Has been used especially for yeast data collection

6
Array Express For Dummies
  • Select what organism you want to search on the
    left.
  • Yeast is the queried term in this aspect.

7
Viewing Search Results
  • Use chip platform selection tab to get desirable
    platform.
  • After your search several results will pop up.

8
Process of Selection
  • Select a data set.
  • Bunch of samples.
  • Chip and AE link figures to get cel files.
  • All information is listed below your selection.

9
Gathering Data
  • Click on AE link, then click on retrieve data.
  • Cel files are at the bottom of the page.

10
Further Supplemental Data
  • Further data found on initial search page
  • Author, article, publication information

11
MAGE ML
  • Microarray Gene Expression- Markup Language
  • Based on XML
  • Describes Microarray data and history
  • User- friendly tools providing web form interface

12
MAGE ML in Array Express
  • After AE link
  • Used to organize data

13
What it Looks Like
14
Draw Backs
  • No quality control information
  • Database is limited
  • Not efficient time consuming trial and error
  • Cant find published papers
  • No accession numbers
  • No probe locations

15
Positive Features
  • Sample size view
  • Cel files
  • Diverse database (Platforms, Organisms)
  • Publication Info.
  • Author, article info
  • Supplemental data

16
Thank You
  • Georgia Tech
  • Dr. Wang
  • The Stokster
  • Ricky
  • Malcolm Thomas
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