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Affymetrix GeneChip Data Analysis

Affymetrix GeneChip Data Analysis. Chip concepts and array design Improving intensity estimation from probe pairs level Clustering Motif discovering and preliminary result. How is Affymetrix Gene Chip made?. fragmented. Affymetrix Gene Chip Procedure. Target preparation

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Affymetrix GeneChip Data Analysis

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  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. fragmented Affymetrix Gene Chip Procedure • Target preparation Isolate mRNA cDNA  cRNA 35~200 base fragments • Target Hybridization: 200ml cocktail probe array chip  hybridization (16 hours at 40~60°C) • Washing and Staining • Probe array scan, Data analysis, and Interpretation (12-15ug) biotinylated

  4. PM MM Probe pair Probe set Concepts of Array Design PM to maximize hybridization MMto 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) arraysoutlier (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 1.3e+01 7.9e-04 3.2e-03 153 GGT-TGGWT 8.6e+00 5.5e-01 4.4e-03 27 GR---AGAA---G 7.0e+00 5.5e-02 1.2e-03 159 G-G-R--G--GRA 6.5e+00 1.1e-02 2.2e-02 460 AGATCCA 5.7e+00 6.8e-01 7.2e-03 538 C-AA-C-AAA 1.9e+00 9.0e-02 1.5e-02 174 CWTTGGG • Functional category refer to MIPSor TIGR or Gene Ontologyweb site • Exhaustive search result fetch all possible patterns within a cluster compare motif frequency among random sampling and functional group (applying M. Eisen’s Cluster/Treeview)

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

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