# tissue cross talk using gene expression data

I am studying about tissue cross-talk using gene expression data. My first goal is to identify the genes responsible for communication signaling(cross talk). Let say the tissues are fat and muscle. One thing that came to my mind was doing correlation analysis and visualizing using a heatmap. Here I would like to get your help with the following points: How to extract the one where both tissues showing a possible correlation from the four possible quadrants of the correlation matrix? How best I can visualize that quadrant using heatmap or any other plotting methods. Here I simulated the data as follows. Rows are genes and columns as samples.

set.seed(1)
A <- data.frame(rnorm(100),
rnorm(100),
rnorm(100),
rnorm(100),
rnorm(100))
row.names(A) <- paste0("G_", 1:100)
colnames(A) <- paste0("S_", 1:5)

set.seed(42)
B <- data.frame(rnorm(100),
rnorm(100),
rnorm(100),
rnorm(100),
rnorm(100))
row.names(B) <- paste0("G_", 1:100)
colnames(B) <- paste0("S_", 1:5)


Tank you!

• Is there any evidence that gene expression can inform about crosstalk? I mean we are talking about some kind of ligand-receptor interaction here, or receptor-receptor interaction. That is the realm of proteins and protein modifications, signaling cascades etc. I am not sure that looking at the transcriptome will give you any information here. – ATpoint Oct 16 at 9:27
• @ATpoint; I know it is tricky. I plan to do proteomics, but this is to get an idea for proteomics experiments. – DowithR Oct 16 at 9:49