After performing DESEQ2 on my data, I could able to plot MA, PCA, and EnhancedVolcano plots including a (.xlsx) file consisting of log fold change ratios, base mean values, and p- values adjusted, and normal p-values were obtained. I would like to now generate a heatmap.

This is my R-script until now:

countData <- read.table("gene_count_matrix.csv", header = TRUE, sep = ",", row.names = 1)

head(countData)

metaData <- read.table("phenodata.csv", header = TRUE, sep = ",")

head(metaData)

#Deseq2

library(DESeq2)

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

dds <- DESeq(dds)

dds 0]

res <- results(dds)

head(res)

summary(res)

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

head(res)

resSig <- res[ which(res$pvalue < 0.05)]

res_lfc 2)

head(res_lfc)

#MA plot

plotMA(res, ylim=c(-2,2))

#plot for PCA

log_dds<-rlog(dds)

plotPCAWithSampleNames(log_dds, intgroup="treatment", ntop=40000)

#volcano plot

library("EnhancedVolcano")

EnhancedVolcano(res,lab = rownames(res),x = 'log2FoldChange',y = 'pvalue',labSize = 0, pCutoff = 0.05,FCcutoff = 1,xlim=c(-30,12))

plot(EnhancedVolcano)



Source link