Hello Dear Biostars,

I have RNAseq data from four groups(A, B, C, and D). Each group represents patients with a particular disease (liver, kidney, heart, and diabetes). My objective is to study if there is a possible cross-talk between two tissues(tissue A and Tissue B) in all groups. The goal is to identify genes responsible for the cross-talk. Based, on that I would like to go deeper into proteomics experiments to get an idea for ligand-receptor interaction of the two tissues of the four groups. The total number of genes detected in the experiment is 20,000 which is common for all groups. Therefore, I am interested to know how to approach to identify a cross-talk present in tissue A and B of group A, B, C, and D? How to compare them in a heatmap or with some network graph?

There are 3 papers showing cross-talk analysis using ingenuity Pathways Analysis (IPA). However, I am not sure If IPA is implemented in R and it is a robust way to do so?. Here are the articles.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2890563/

https://journals.plos.org/plosone/article/figure?id=10.1371/journal.pone.0173082.g002

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0157480

Best, Amare