hierarchical_clustering_HM

countDF <- read.table("Count_expression_matrix.txt", sep="\t", header=TRUE)
countDF2 <- countDF[,-1]
names <- countDF$X
rownames(countDF2) = make.names(names, unique=TRUE)
countDF3 <- subset(countDF2, select=c())
countDF4 <- countDF3[rowSums(countDF3[,-1]^2) > 0, ]
df[-row(df)[df == 0],]

library(systemPipeR)
targets <- read.delim("targets.txt", comment.char = "#")

library(DESeq2)
colData <- data.frame(row.names=targets$SampleName, condition=targets$Factor)
dds <- DESeqDataSetFromMatrix(countData = countDF4, colData = colData, design = ~ condition)
names <- rownames(countDF4)

library(pheatmap)
y <- assay(rlog(dds))[names, ]

pdf("heatmap1.pdf")
pheatmap(y, scale="row", clustering_distance_rows="correlation", clustering_distance_cols="correlation")
dev.off()