[BioC] decideTests and topTable

[Humberto Ortiz Zuazaga]

I've got some Agilent microarray data for 3 different groups, and am trying to 
use limma to select differentially expressed genes.

Here's the steps I've taken so far:

> allone <-function (qta)
+ {
+      1
+ }
> targets <- readTargets("new-cort-targets.txt")
> RG <- read.maimages(targets$FileName,source="agilent",wt.fun=allone)
Read 1/Cort(N-C)2.txt 
Read 2/cort(N-E)2.txt 
Read 2/cort(N-E)3.txt 
Read 5/dye swap/cort(C-N).txt 
Read 5/dye swap/Cort(E-N).txt 
> types <- readSpotTypes("spottype.txt")
> status <- controlStatus(types, RG)
Matching patterns for: ControlType 
Found 22393 other 
Found 913 Positive 
Found 162 Negative 
Found 21318 gene 
Setting attributes: values Color ID Name 
> RG$genes$Status <- status
> RG <- backgroundCorrect(RG, method="none")
> weights <- modifyWeights(RG$weights, status,
+                          values=c("Positive","Negative"),multipliers=0)
> MA <- normalizeWithinArrays(RG,method="loess",weights=weights)
> MA.b <- normalizeBetweenArrays(MA,method="scale")
> design <- modelMatrix(targets, ref="Naive")
Found unique target names:
 Control Enriched Naive 
> fit <- lmFit(MA.b,design,weights=weights)
> fit.b <- eBayes(fit)
> table <- topTable(fit.b,coef=1,number=100)
> write.table(table,file="table.txt", sep="\t", col.names = NA)

> calls.strict <- decideTests(fit.b,adjust.method="fdr")
> write.fit(fit.b,results=calls.strict,file="fit.txt",digits=3)

My question is, when I look at the top table, my best candidate is

""	"Row"	"Col"	"ProbeUID"	"ControlType"	"ProbeName"	"GeneName"	"Description"	
"Status"	"M"	"A"	"t"	"P.Value"	"B"
"10984"	 52	106	10181	0	"A_51_P443387"	"AJ276707"	"Mus musculus partial mRNA 
for WTAP protein"	"gene"	-0.9176259	 9.403058	-11.262342	0.2490771	-2.218647

Which has an adjusted p value of 0.2490771

The fit object also has a p-value column, and it is adjusted in write.fit, but 
the corresponding line from the fit is:

A	Control	Enriched	Control	Enriched	Control	Enriched	Control	Enriched	Row	Col	
ProbeUID	ControlType	ProbeName	GeneName	Description	Status
 9.40	-0.918	-0.267	-11.26	-4.02	0.00001	0.00533	-1	 0	 52	106	10181	 0	
A_51_P443387	AJ276707	Mus musculus partial mRNA for WTAP protein	gene

The p value for contrast 1 is 0.00001.

Why are the p values so different?

Can I say this gene is or is not differentially expressed? Note that the 
decideTests result for contrast 1 is -1, so I understand that decideTests 
thinks it is differentially expressed. Looking at the topTable output, 
however,  makes it unlikely to be differentially expressed.

-- 
Humberto Ortiz Zuazaga
Programmer-Archaeologist
High Performance Computing facility
University of Puerto Rico
http://www.hpcf.upr.edu/~humberto/