Hi,

I am trying to plot heatmap on my counts from HTSeq. Here is my codes (partial).

`dds<-DESeq(ddsHTSeq)`

res<-results(dds)

res<-res[order(res$padj),]

rld <- rlogTransformation(dds, blind=TRUE)

vd <- varianceStabilizingTransformation(dds, blind=TRUE)

library("genefilter")

topVarGenes <- head(order(rowVars(assay(vd)),decreasing=TRUE),200)

mat <- assay(rld)[ topVarGenes, ]

mat <- mat - rowMeans(mat)

df <- as.data.frame(colData(rld)[,c("cond1","cond2, "cond3")])

pheatmap(mat, annotation_col=df, show_rownames=FALSE)

This is my summary of the results

out of 42075 with nonzero total read count

adjusted p-value < 0.1

LFC > 0 (up) : 4674, 11%

LFC < 0 (down) : 5123, 12%

outliers [1] : 0, 0%

low counts [2] : 11998, 29%

(mean count < 5.6)

This pheatmap results only for top 200 genes. My question is,

1) is it possible to heatmap based on threshold like above some p-value or fold change?

2) is it possible to use different colours for different conditions?

3) how can I force pheatmap to do the heatmap based on foldchange or adjusted p-value?

Thanks

J.