Dear list,

I am comparing cells with a gene knockdown with wildtype cells to find genes
differentially regulated in response to the knockdown using Illumina bead
arrays. I plan to compare genes regulated by CPT stimulation in knockdown
and wildtype cells. For that, I used a Venn Diagram, and export a list of
the genes of the knockdown only category.
However, whatever I enter for lfc in the decideTests function, the numbers
of genes in the resulting diagram stay the same, whilst from manual
comparison of the data, they should not. Does anyone know what I am doing
wrong?

Many thanks,

Moritz (Fellow, University of Bonn, Germany)



I did the following, largely following the beadarray tutorial.

library(beadarray)
dataFile = "data.txt"
BSData = readBeadSummaryData(dataFile = dataFile, dec=",", qcFile = NULL,
skip = 0, qc.skip = 0)
BSData.quantile = normaliseIllumina(BSData, method = "quantile", transform =
"log2")
BSData.genes = BSData.quantile[which(fData(BSData)$Status == "Gene"), ]
expressed = apply(Detection(BSData.genes) < 0.05, 1, any)
BSData.filt = BSData.genes[expressed,]
library(limma)
samples = c(rep("con_veh",3), rep("con_cpt",3), rep("kd_veh",3),
rep("kd_cpt",3) )
samples
samples = as.factor(samples)
design=model.matrix(~0 + samples)
colnames(design) = levels(samples)
fit = lmFit(exprs(BSData.filt), design)
cont.matrix=makeContrasts(diff_con=con_veh - con_cpt, diff_kd=kd_veh -
kd_cpt, levels=design)
fit=contrasts.fit(fit, cont.matrix)
fit$genes=fData(BSData.filt)
ebFit=eBayes(fit)
veh=topTable(ebFit, coef=1, number=500)
cpt=topTable(ebFit, coef=2, number=500)
write.table(veh, file="diff_exp_wt.txt", sep="\t")
write.table(cpt, file="diff_exp_kd.txt", sep="\t")
decideTests(ebFit,method="separate",adjust.method="BH",p.value=0.05,lfc=1)
results=decideTests(ebFit)
a <- vennCounts(results)
print(a)
vennDiagram(a)
only_kd <- which(results[,1] == 0 & results[,2] == 1)

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