Candidate Data Sets - PowerPoint PPT Presentation

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Candidate Data Sets

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SELDI protein patterns for prostate cancer. Hundreds of spectra, each file a few MB ... MSA for bladder cancer. 300 cases, 200 controls ... – PowerPoint PPT presentation

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Title: Candidate Data Sets


1
Candidate Data Sets
  • Mark Thornquist
  • 2005 EDRN Informatics Meeting
  • 2 November 2005

2
Validation Studies
  • SELDI protein patterns for prostate cancer
  • Hundreds of spectra, each file a few MB
  • Raw data, processed data, peaks, intensities
  • DCP for hepatic cancer
  • 450 patients (190 early-stage), 450 controls
  • Extensive epidemiological data, single time point
    for cases, two time points for controls

3
Validation Studies
  • MSA for bladder cancer
  • 300 cases, 200 controls
  • Panel of markers tested (15-20 microsatellite
    locations)
  • Longitudinal data (up to 9 observations over 2
    years for cases)
  • Intellectual property owned by for-profit company

4
Validation Studies
  • Ovarian cancer biomarkers
  • Joint collaboration between EDRN and ovarian
    cancer SPOREs
  • Multiple markers will be tested, and a panel of
    markers is the likely outcome
  • If early phases successful, marker panel will be
    tested in PLCO specimens

5
Standard Specimen Reference Sets
  • Multiple sets in planning stages
  • Lung, ovarian, prostate, colon, breast
  • Typical design
  • Rapid pre-validation and validation sets
  • Several hundred specimens
  • Tens to hundreds of identical sets per reference
    set
  • Extensive associated epidemiological data

6
High-Dimensional Data for Discovery
  • Proteomics spectra
  • SELDI spectra from EVMS
  • Microarrays
  • 2-D gels
  • Images

7
Other Categories
  • Data supporting publications
  • Access restricted until publication appears
  • Multi-site collaborative studies
  • Access restricted to collaborators until final
    release

8
Issues to be Addressed
  • Human subjects requirements
  • Data security
  • Authorization and authentication
  • Database structure
  • Finding useful data subsets
  • Uploading/downloading huge data sets
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