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Sort columns of of originalmatrixTake averages across rowsTake averages across rowsSet average as as value for forAll elements in in the the rowUnsort columns of ofmatrix to to original order⎡1 5 3 5⎤ ⎡1 1 1 5⎤⎢2 1 6 7⎥ ⎢2 2 2 6⎥⎢ ⎥ → ⎢ ⎥⎢3 2 2 6⎥ ⎢3 5 3 7⎥⎢ ⎥ ⎢ ⎥⎣4 6 1 8⎦ ⎣4 6 6 8⎦⎡1 1 1 5⎤ ⎡ 2 ⎤⎢2 2 2 6⎥ ⎢3⎥⎢ ⎥ → ⎢ ⎥⎢3 5 3 7⎥ ⎢4.5⎥⎢ ⎥ ⎢ ⎥⎣4 6 6 8⎦ ⎣ 6 ⎦⎡ 2 ⎤ ⎡ 2 2 2 2 ⎤⎢3⎥ ⎢3 3 3 3⎥⎢ ⎥ → ⎢ ⎥⎢4.5⎥ ⎢4.5 4.5 4.5 4.5⎥⎢ ⎥ ⎢ ⎥⎣ 6 ⎦ ⎣ 6 6 6 6 ⎦⎡ 2 2 2 2 ⎤ ⎡ 2 4.5 4.5 2 ⎤⎢3 3 3 3⎥ ⎢3 2 6 4.5⎥⎢ ⎥ → ⎢ ⎥⎢4.5 4.5 4.5 4.5⎥ ⎢4.5 3 3 3 ⎥⎢ ⎥ ⎢ ⎥⎣ 6 6 6 6 ⎦ ⎣ 6 6 2 6 ⎦
Why Quantile Normalization?• Quantile normalization found to performacceptably in reducing variance withoutdrastic bias effects• Quantile normalization is fast
Page 2 and 3:
Outline• What is Low-Level Analys
Page 4 and 5:
High-Level Analysis• Clustering/C
Page 6 and 7:
Brief TechnologyOverview• High de
Page 8 and 9:
Two Probe TypesPM: the Perfect Matc
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Focusing on a SingleGeneChip Cell L
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Hybridization to the Chip
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Chip dat file - checkered board - o
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Chip dat file - checkered board - c
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Constructing a geneexpression measu
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Background/SignalAdjustment• A me
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Normalization“Non-biological fact
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Summarization• Reduce the 11-20 p
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Affymetrix Spike-in Data• 59 chip
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Assessing Bias:Observed Expression
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Assessing Variability:M vs A plots
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Summary of Trade-offsBackgroundMeth
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Scaling is Not Sufficient
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Little effect on Spike-insMethodAll
Page 47 and 48: Comparing EstablishedExpression Mea
Page 49 and 50: General Probe LevelModelyij= f( X)+
Page 51 and 52: Fitting the PLM• Robust regressio
Page 53 and 54: Fold ChangeFC = X − XlmWhereXl=
Page 55 and 56: “Robust” t-statistict=Xlsnm2s2l
Page 57 and 58: Limma “ebayes” t-statistic• G
Page 59 and 60: Probe Level Model teststatisticstPL
Page 65: What Happens as the Numberof Arrays
Page 71 and 72: ResultsMethod Individual Models Sin
Page 75 and 76: What is going on here?• Examine r
Page 77 and 78: Low Non-Differential
Page 79 and 80: High Non-Differential
Page 81 and 82: GeneLogic Tonsil dataset
Page 83 and 84: ResultsMethod 3 vs 3 4 vs 4 5 vs 50
Page 86 and 87: Ongoing work in this area• Techno
Page 88 and 89: Additional Slides
Page 90 and 91: Original RMA Background• Convolut
Page 92 and 93: A Standard Curve AdjustmentBased on
Page 94 and 95: γRelates to Concentration
Page 96 and 97: The Two Curves Yield anAdjustment C
Page 100 and 101: RMA Model• To each probeset (k),
Page 102 and 103: Basic RMA modelLetthenyij= log N B2
Page 104 and 105: SlopeAllMidLowHighValue0.4930.6650.
Page 106 and 107: SlopeAllMidLowHighValue0.5890.7510.
Page 108 and 109: SlopeAllMidLowHighValue0.6950.820.5
Page 110 and 111: Slope: 0.484
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