Question: deseq2: use blind=T or blind=F when find gene groups?
gravatar for salamandra
8 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 • 135 views
ADD COMMENTlink modified 8 months ago by Michael Love25k • written 8 months ago by salamandra0
Answer: deseq2: use blind=T or blind=F when find gene groups?
gravatar for Michael Love
8 months ago by
Michael Love25k
United States
Michael Love25k wrote:

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

ADD COMMENTlink written 8 months ago by Michael Love25k
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