Question: deseq2: use blind=T or blind=F when find gene groups?
0
gravatar for salamandra
17 days ago by
salamandra0
salamandra0 wrote:

Hi,

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)
Table
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 <- as.data.frame(dds_res)
ddsdatres <- ddsdatres[!is.na(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))
library('DEGreport')
rownames(Table) <- Table[,1]
meta <- as.data.frame(colData(dds_lrt))
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")

print(clustersA$plot)

dev.off()

 

ADD COMMENTlink modified 16 days ago by Michael Love21k • written 17 days ago by salamandra0
Answer: deseq2: use blind=T or blind=F when find gene groups?
1
gravatar for Michael Love
16 days ago by
Michael Love21k
United States
Michael Love21k wrote:

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

ADD COMMENTlink written 16 days ago by Michael Love21k
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