Entering edit mode
Wu, Xiwei
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350
@wu-xiwei-1102
Last seen 9.7 years ago
Dear list,
I did a search in the mail achive, and did not find anyone reporting
the
same issue below.
I was looking at some cDNA array data using Limma 2.0.2 with
R2.1.1patched under Windows2000. I have three different contrasts.
When
I looked at the topTables generated from each contrasts, the A
(average
intensity) for all the genes are the same across the three contrasts.
I
also observed the same thing using another dataset. Is that what is
supposed to happen, or is there anything wrong with my code? Any help
will be highly appreciated.
Xiwei Wu, MD, PhD
Assistant Research Scientist
Department of Biomedical Informatics
Beckman Research Insitute
City of Hope National Medical Center
Duarte, CA 91010
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> library(limma)
> targets <- readTargets()
> targets
SlideNumber
FileName Cy3 Cy5
2005-07-06_04J12 HsKGV_17_(Pos_vs_Neg) 1 2005-07-06_04J12
HsKGV_17_(Pos_vs_Neg).gpr V C1
2005-07-06_04J12 HsKGV_18_(36A_vs_Neg) 2 2005-07-06_04J12
HsKGV_18_(36A_vs_Neg).gpr RZ1 C1
2005-07-06_04J12 HsKGV_19_(36B_vs_Neg) 3 2005-07-06_04J12
HsKGV_19_(36B_vs_Neg).gpr RZ2 C1
2005-07-06_04J12 HsKGV_20_(Neg_vs_Pos) 4 2005-07-06_04J12
HsKGV_20_(Neg_vs_Pos).gpr C1 V
2005-07-06_04J12 HsKGV_22_(Neg_vs_36A) 5 2005-07-06_04J12
HsKGV_22_(Neg_vs_36A).gpr C1 RZ1
2005-07-06_04J12 HsKGV_23_(Neg_vs_36B) 6 2005-07-06_04J12
HsKGV_23_(Neg_vs_36B).gpr C1 RZ2
> myfun <- function(x) as.numeric(x$Flags > -49.5)
> RG <- read.maimages(targets$FileName, source="genepix",
wt.fun=myfun)
> RGb <- backgroundCorrect(RG, method="normexp", offset=50)
> MA <- normalizeWithinArrays(RGb, layout=getLayout(RG$genes))
> MA2 <- normalizeBetweenArrays(MA, method="scale")
> design <- modelMatrix(targets, ref="C1")
Found unique target names:
C1 RZ1 RZ2 V
> design
RZ1 RZ2 V
2005-07-06_04J12 HsKGV_17_(Pos_vs_Neg) 0 0 -1
2005-07-06_04J12 HsKGV_18_(36A_vs_Neg) -1 0 0
2005-07-06_04J12 HsKGV_19_(36B_vs_Neg) 0 -1 0
2005-07-06_04J12 HsKGV_20_(Neg_vs_Pos) 0 0 1
2005-07-06_04J12 HsKGV_22_(Neg_vs_36A) 1 0 0
2005-07-06_04J12 HsKGV_23_(Neg_vs_36B) 0 1 0
> fit <- lmFit(MA2, design)
> cont <- makeContrasts(RZvsV = (RZ1+RZ2)/2-V, VvsC = V, RZvsC =
(RZ1+RZ2)/2, levels=design)
> cont
RZvsV VvsC RZvsC
RZ1 0.5 0 0.5
RZ2 0.5 0 0.5
V -1.0 1 0.0
> fit2 <- contrasts.fit(fit, cont)
> fit2 <- eBayes(fit2)
> RZvsV <- topTable(fit2, coef=1, adj="none", n=15360)
> VvsC <- topTable(fit2, coef=2, adj="none", n=15360)
> RZvsC <- topTable(fit2, coef=3, adj="none", n=15360)
> RZvsV_sort <- SortMat(RZvsV, Sort=c(1,2,3))
> VvsC_sort <- SortMat(VvsC, Sort=c(1,2,3))
> RZvsC_sort <- SortMat(RZvsC, Sort=c(1,2,3))
#Below shows that all As are the same
> RZvsV_sort[1:5,]
Block Row Column ID Name
M A t P.Value B
1 1 1 1 Inf arylsulfatase B
NA 6.627838 NA NA NA
2 1 1 2 Inf epimorphin
NA 6.213439 NA NA NA
3 1 1 3 Inf parathyroid hormone-like hormone
0.11716600 8.375271 0.4991073 0.6311222 -4.696798
4 1 1 4 Inf 5-hydroxytryptamine (serotonin) receptor 2C
NA 6.599125 NA NA NA
5 1 1 5 Inf 2,3-bisphosphoglycerate mutase
0.07083349 9.614017 0.2325365 0.8219533 -4.721694
> VvsC_sort[1:5,]
Block Row Column ID Name
M A t P.Value B
1 1 1 1 Inf arylsulfatase B
NA 6.627838 NA NA NA
2 1 1 2 Inf epimorphin
NA 6.213439 NA NA NA
3 1 1 3 Inf parathyroid hormone-like hormone
-0.03414736 8.375271 -0.1781538 0.8630258 -4.681857
4 1 1 4 Inf 5-hydroxytryptamine (serotonin) receptor 2C
NA 6.599125 NA NA NA
5 1 1 5 Inf 2,3-bisphosphoglycerate mutase
0.09565185 9.614017 0.3845843 0.7105558 -4.671349
> RZvsC_sort[1:5,]
Block Row Column ID Name
M A t P.Value B
1 1 1 1 Inf arylsulfatase B
NA 6.627838 NA NA NA
2 1 1 2 Inf epimorphin
NA 6.213439 NA NA NA
3 1 1 3 Inf parathyroid hormone-like hormone
0.08301864 8.375271 0.6125316 0.5571728 -5.722139
4 1 1 4 Inf 5-hydroxytryptamine (serotonin) receptor 2C
NA 6.599125 NA NA NA
5 1 1 5 Inf 2,3-bisphosphoglycerate mutase
0.16648534 9.614017 0.9466494 0.3714985 -5.471472
"EMF <coh.org>" made the following annotations.
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