Question: heatmap using DESeq2
1
gravatar for sumithrasank75
2.5 years ago by
United States
sumithrasank75130 wrote:

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 • 2.5k views
ADD COMMENTlink modified 2.5 years ago by cpad011212k • written 2.5 years ago by sumithrasank75130

This guideline contains code for making DESeq2 heatmaps, and also the DESeq2 manual does. Using google to find this wasn't too hard!

ADD REPLYlink written 2.5 years ago by WouterDeCoster42k
2
gravatar for cpad0112
2.5 years ago by
cpad011212k
India
cpad011212k wrote:

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

ADD COMMENTlink written 2.5 years ago by cpad011212k
0
gravatar for Kritika
2.5 years ago by
Kritika260
India
Kritika260 wrote:

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).

ADD COMMENTlink modified 2.5 years ago • written 2.5 years ago by Kritika260

Follow this https://cran.rstudio.com/web/packages/pheatmap/pheatmap.pdf

ADD REPLYlink written 2.5 years ago by Kritika260
0
gravatar for YaGalbi
2.5 years ago by
YaGalbi1.4k
Biocomputing, MRC Harwell Institute, Oxford, UK
YaGalbi1.4k wrote:

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?

ADD COMMENTlink modified 2.5 years ago • written 2.5 years ago by YaGalbi1.4k
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