I respectfully would like to get your feedback(tutorial) on the following questions.
I have gene expression data from the same Biological replicates of two tissues of the brain(cortex and cerebellum)
I want to know if Cortex and Cerebellum genes have similarities in their expression/co-expressed/ for the condition I am studying. I did data normalization using DESeq2. Then, I break the data into two(cortex and cerebellum) for correlation analysis.
Now, my question is:
(1) How could I extract a cluster of correlated genes between the cortex and cerebellum from the two-dimensional hierarchically clustered heatmap for further analysis?
(2) How I could assign color bars for the different clusters of genes in the rows and columns-here theoretically asking color assignment for each cluster in the rows and columns as indicated in WGCNA approach.
Here simulated the data as follow.
## Cortex expression profile set.seed(123) cortex = matrix(rnorm(1000, 2), 100, 10) rownames(cortex) = paste0("gene_", 1:100) colnames(cortex) = LETTERS[1:10] ## cerebellum expression profile set.seed(177) cerebellam = matrix(rnorm(1000, 2), 100, 10) rownames(cerebellam) = paste0("gen_", 1:100) colnames(cerebellam) = LETTERS[1:10] ## similarity measure Tissue_corrlation = cor(t(cortex), t(cerebellam)) ##Heatmap library(ComplexHeatmap) Heatmap(Tissue_corrlation ,cluster_rows = as.dendrogram(hclust(dist(Tissue_corrlation))), cluster_columns = as.dendrogram(hclust(dist(t(Tissue_corrlation )))))