Affymetrix GeneChip Data Analysis - PowerPoint PPT Presentation

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Affymetrix GeneChip Data Analysis

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... GeneChip Data Analysis. Chip concepts and array design. Improving intensity estimation from probe ... Concepts of Array Design. PM to maximize hybridization ... – PowerPoint PPT presentation

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Title: Affymetrix GeneChip Data Analysis


1
Affymetrix GeneChip Data Analysis
  • Chip concepts and array design
  • Improving intensity estimation from probe pairs
    level
  • Clustering
  • Motif discovering and preliminary result

2
How is Affymetrix Gene Chip made?
3
Affymetrix Gene Chip Procedure
  • Target preparation
  • Isolate mRNA ?cDNA ? cRNA? 35200 base
    fragments
  • Target Hybridization
  • 200ml cocktail ? probe array chip ?
    hybridization
  • (16 hours at 4060C)
  • Washing and Staining
  • Probe array scan, Data analysis, and
    Interpretation

(12-15ug)
biotinylated
4
Concepts of Array Design
  • PM to maximize hybridization
  • MM to ascertain the degree of
    cross-hybridization

5
Signal Intensity Estimation
  • Absolute analysis
  • average difference ?(PM-MM) / pairs
    used
  • Comparison analysis
  • experimental subtract baseline average
    difference
  • Probe pairs variation
  • probe pairs outlier (cross-hybridization)
  • arrays outlier (image contamination)
  • Probe pairs level adjustment
  • Wing Wong Lab dChip least square fitting model
    built from multiple chips
  • Affymetrix MAS 5.0 imputation

6
Clustering
  • Affymetrix DMT
  • examine the SOM, are the clusters tight ?
  • experiment primarily with "Number of Epochs",
  • "Alpha_i" and "Sigma_i" parameters to reduce
    error.
  • multiple level clustering
  • examine filtering parameters to adjust min
    and max value.
  • (default is 20 and 20000)
  • Wing H. Wong Lab dChip
  • from image file to outlier detection and
    clustering
  • MIT Whitehead Institute GeneCluster
  • Stanford Cluster and Treeview
  • two way clustering (genes and/or arrays)
  • find profile pattern not found in SOM clustering

7
Motif discovering
  • Motif discovery and matching tools
  • Basic assumption a cluster of co-regulated
    genes is regulated by the same transcription
    factors and the genes of a given cluster share
    common regulatory motifs
  • Gibbs Motif Sampler
  • Neuwald et al. 1995
  • AlignACE
  • based on Gibbs Sampling, optimized for
    finding multiple motifs and for both strands
  • RSA-tools
  • motif finding among non-coding regions in
    cress, yeast, fly, worm
  • PlantCARE
  • search known motifs among 417 different plant
    transcription sites
  • TFSEARCH
  • search known motifs in vertebrate,
    arthropod, plant, yeast

8
Motif discovering result
  • AlignACE motif finding result for a specific
    clustered genes
  • 1.3e01 7.9e-04 3.2e-03 153 GGT-TGGWT
  • 8.6e00 5.5e-01 4.4e-03 27 GR---AGAA---G
  • 7.0e00 5.5e-02 1.2e-03 159 G-G-R--G--GRA
  • 6.5e00 1.1e-02 2.2e-02 460 AGATCCA
  • 5.7e00 6.8e-01 7.2e-03 538 C-AA-C-AAA
  • 1.9e00 9.0e-02 1.5e-02 174 CWTTGGG
  • Functional category
  • refer to MIPS or TIGR or Gene Ontology web site
  • Exhaustive search result
  • fetch all possible patterns within a cluster
  • compare motif frequency among
  • random sampling and functional group
  • (applying M. Eisens Cluster/Treeview)

9
Supportive Information
  • Schroeder lab (UCSD)
  • sequence retrieval and direct MEME motif finding
  • Gene Microarray Pathway Profiler
  • genechip array statistical consideration
  • MIT CCR HHMI Biopolymers Laboratory  
  • Databases and software tools for gene expression
  • software, databases, mail lists
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