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.