Question: deseq2: use blind=T or blind=F when find gene groups?
gravatar for salamandra
10 months ago by
salamandra0 wrote:


I'm using reduced model to get genes that vary over different conditions and using degPaterns() to split those genes into groups according to their expression pattern (code bellow). What want to know is in this case, should we use parameter blind=T or blind=F in rlog() ?

Table <- data.frame(sampleName = sampleNames, fileName = sampleFiles, time = time, celltype = celltype, condition=condition)
dds <- DESeqDataSetFromHTSeqCount(sampleTable = Table, design= ~ condition)
ddsHTSeq <- dds[rowSums(counts(dds)) > 1, ]
rld <- rlog(ddsHTSeq, blind=F)

dds_lrt <- DESeq(ddsHTSeq, test="LRT", reduced = ~ 1)

dds_res <- results(dds_lrt, alpha = value)

ddsdatres <-
ddsdatres <- ddsdatres[!$padj),]
res.sig <- ddsdatres[ddsdatres$padj < value,]
res.sig <- res.sig[order(res.sig$padj),]
rld_mat <- assay(rld)
cluster_rlog <-subset(rld_mat, row.names(rld_mat)%in%row.names(res.sig))
rownames(Table) <- Table[,1]
meta <-
clustersA <- degPatterns(cluster_rlog, metadata = meta, time = "condition", col=NULL)

png(paste0(outdir,cell,'.genegroupsA', pvalue,'.png'), res = 300, height = 20*300, width = 20*300, bg = "white")



deseq2 rlog transformation • 151 views
ADD COMMENTlink modified 10 months ago by Michael Love26k • written 10 months ago by salamandra0
Answer: deseq2: use blind=T or blind=F when find gene groups?
gravatar for Michael Love
10 months ago by
Michael Love26k
United States
Michael Love26k wrote:

I tend to use blind=FALSE,  because it avoids overestimating the dispersion.

ADD COMMENTlink written 10 months ago by Michael Love26k
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