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Background/SignalAdjustment• A method which does some or all of thefollowing– Corrects for background noise, processing effects– Adjusts for cross hybridization– Adjust estimated expression values to fall onproper scale• Probe intensities are used in backgroundadjustment to compute correction (unlikecDNA arrays where area surrounding spotmight be used)
Background Methods• Affymetrix– Location dependent– Ideal mismatch• RMA– Convolution model• Other– Standard curve adjustment– GCRMA (Wu et al 2003)+ =
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
Page 10 and 11: Focusing on a SingleGeneChip Cell L
Page 12 and 13: Hybridization to the Chip
Page 14 and 15: Chip dat file - checkered board - o
Page 16 and 17: Chip dat file - checkered board - c
Page 18 and 19: Constructing a geneexpression measu
Page 22 and 23: Normalization“Non-biological fact
Page 24 and 25: Summarization• Reduce the 11-20 p
Page 26 and 27: Affymetrix Spike-in Data• 59 chip
Page 28 and 29: Assessing Bias:Observed Expression
Page 30: 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
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Low Non-Differential
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High Non-Differential
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GeneLogic Tonsil dataset
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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
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The Two Curves Yield anAdjustment C
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Sort columns of of originalmatrixTa
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RMA Model• To each probeset (k),
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Basic RMA modelLetthenyij= log N B2
Page 104 and 105:
SlopeAllMidLowHighValue0.4930.6650.
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SlopeAllMidLowHighValue0.5890.7510.
Page 108 and 109:
SlopeAllMidLowHighValue0.6950.820.5
Page 110 and 111:
Slope: 0.484
Page 112 and 113:
Slope: 0.583
Page 114 and 115:
Slope: 0.692
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