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What about the treatmenteffect model?• The limma ebayes test statistic seems to beoutperforming the PLM test statistics in theAUC statistic. Closer examination of ROCcurve shows it exceeding all other methodsbetween 0.25% and 2.5% false positives.• Try the Treatment effect model with–PLM.2– PLM.2 with a simple moderation
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Outline• What is Low-Level Analys
Page 4 and 5:
High-Level Analysis• Clustering/C
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Brief TechnologyOverview• High de
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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
Page 38 and 39: Summary of Trade-offsBackgroundMeth
Page 43 and 44: Scaling is Not Sufficient
Page 45 and 46: 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: ResultsMethod 3 vs 3 4 vs 4 5 vs 50
Page 87 and 88: Acknowledgements• Terry Speed (UC
Page 89 and 90: Background Signal Methods• Affyme
Page 91 and 92: Convolution Model• O = S + N- O i
Page 93 and 94: What About Non Spike-ins?• We don
Page 95 and 96: Establishing a RelationshipγBetwee
Page 97 and 98: Quantile Normalization• Normalize
Page 99 and 100: Why Quantile Normalization?• Quan
Page 101 and 102: Probe Level Models are• RMA metho
Page 103 and 104: Advantages/Disadvantages of RMA/Med
Page 105 and 106: SlopeAllMidLowHighValue0.630.7840.3
Page 107 and 108: SlopeAllMidLowHighValue0.690.820.52
Page 109 and 110: SlopeAllMidLowHighValue0.8561.0410.
Page 111 and 112: Slope: 0.624
Page 113 and 114: Slope: 0.683
Page 115: Slope: 0.847
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