Hello guy, I have use DEseq2 got the heat map based on unigenes’ readcounts. The command lines I have used are:
colData <- read.table("colData.txt") countData <- read.table("countData_DEGs(count_larger_1).txt")
rownames(colData) <- sub("fb","",rownames(colData)) all(rownames(colData) %in% colnames(countData))
countData <- countData[, rownames(colData)] all(rownames(colData) == colnames(countData))
dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design =~ condition)
pheatmap(log2.norm.counts, cluster_rows=TRUE, show_rownames=FALSE, cluster_cols=TRUE, annotation_col=df)
dev.print(pdf, 'countData_DEGs(count_larger_1_heatmap_include_cluster.pdf')
But I want to know detailed information like which unigenes clustered together. And if I could get this cluster result in tabular format would be great. How can I do that? I am very new at R language. any suggestion would be appreciated.
hi @e.rempel,
could not cut the tree, and reported this error:
Hi Kurban,
the error message implies that there is something wrong with cluster.object$tree_col: an object of class hclust. Can you have a look at cluster.object$tree_col$merge?