Question: deseq2: use blind=T or blind=F when find gene groups?
0
gravatar for salamandra
10 weeks 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 10 weeks ago by Michael Love22k • written 10 weeks ago by salamandra0
Answer: deseq2: use blind=T or blind=F when find gene groups?
1
gravatar for Michael Love
10 weeks ago by
Michael Love22k
United States
Michael Love22k wrote:

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

ADD COMMENTlink written 10 weeks ago by Michael Love22k
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