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heatmap using DESeq2

I am trying to generate a heat map of the top differentially expressed genes between two samples. I have used DESeq2 to identify these. My code is

library(DESeq2)

countData = read.csv("data.txt",header = T,sep = "\t")

colData = DataFrame(condition = factor(c("female","female","female","male","male","male")))

dds <- DESeqDataSetFromMatrix(countData = countData,colData = colData,design = ~ condition)

dds <- dds[ rowSums(counts(dds)) > 1, ]

dds <- DESeq(dds)

res <- results(dds,contrast=c("condition","male","female"))

summary(res)

I am not sure how to get a heatmap from the dds or res objects. Please help. Thanks

rna-seq
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updated by cpad0112 cpad0112 • written by sumithrasank75 sumithrasank75

3 answers

Please visit "Data quality assessment by sample clustering and visualization" section in below page: https://www.bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html

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written by cpad0112 cpad0112

You can extract FPKM values or Count value (If you are using htseq-count) of top differentially expressed gene. by this FPKM matrix you can plot heatmap using pheatmap library or heatmap.2(ggplot lib).

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written by Kritika Kritika

Create a matrix of DEG counts then use corrplot or ggplot2.

Matrix example:

                  sample1        sample2        sample3 
sample1              0             567            545                
sample2             123             0             234
sample3             345            34              0

Corrplot is very very very easy. ggplot2 gives more control but is more complicated and will require first converting the matrix to long format using the melt function of reshape package. Did I mention how easy corrplot is?

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written by BioinfGuru BioinfGuru

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