Fitting Statistical models to data with many more variables than ...

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St Judes Leukemia data - Probes and genesAffy chips collect data for 500,000 probesProbes are collected into “probe sets” of11-14 probes to give “gene expression”values
Example 1: St Jude’s Leukaemia datap = 44,000 “genes” or >500,000 probes(Affymetrix U133A/B) n = 104 samples 6 leukaemia subtypesResults44,000 “genes” 6-gene classification model Cross-validated error < 5%500,000 probes 5–probe classification model Cross-validated error < 4%
Page 2: Talk outline1. Introduction, motiva
Page 5: IntroductionResponse ModellingEach
Page 9 and 10: Some issues1. Artefacts - apparent
Page 11 and 12: Cross validationBoxplotC ross valid
Page 13 and 14: Parameters in the modelsThe models
Page 15 and 16: The prior - special casesk=1 (Lasso
Page 21 and 22: An EM algorithmWant to find (local)
Page 23 and 24: E- step continuedThe conditional ex
Page 25 and 26: CommentsStructure can be used to ma
Page 27 and 28: GeneRave in Action
Page 29: Êÿëáÿúÿð ÿðàçèñèíä
Page 33 and 34: Single Nucleotide PolymorphismsSNPA
Page 35 and 36: Data and modelWe fit a sparse “ma
Page 37 and 38: Two SNP race classifierafd0860639
Page 39 and 40: Independent validation of resultsTh
Page 41 and 42: CodeR Library available for downloa

Fitting Statistical models to data with many more variables than ...

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