OrganChat: inferring organ-organ communication through single-cell data

OrganChat is a computational method that uses single-cell multi-modal data together with a newly constructed long-range signal (LS)-mediated communication database (OrganChatDB) to infer organ-organ communications.

Installation

You can install the development version of OrganChat from GitHub with:

# install.packages("devtools")
devtools::install_github("ChanghanGitHub/OrganChat")

Overview

OrganChatDB integrates LS-receptor signaling, receptor-SE interactions, and SE-target regulations for both human and mouse, as well as a dictionary linking HMDB IDs to metabolite synonyms. In total, the database catalogs 777 and 801 distinct LS molecules – encompassing metabolites, peptide and nonpeptide hormones, and cytokines – for human and mouse, respectively (Fig. 1a-b). The standard OrganChat workflow consists of three key modules: (1) Data processing module; (2) OOC inference module; (3) Multi-scale analysis module.

All processed data and some saved OrganChat objects can be download from: https://doi.org/10.5281/zenodo.19042679.

Examples

Application to a five-organ communication system for immune-mediated diseases: link to the folder

1. Processing the original data and inferring metabolite flux.

2. Comparison analysis via OrganChat between conditions for: joint and muscle; joint and spleen; muscle and spleen; skin and muscle.

3. Multi-organ OrganChat (MOOC) Analysis of OrganChat between conditions for: joint, muscle, lung, skin, spleen.

OrganChat reveals cross-organ communication for human multiple-disease systems: link to the folder

1. Processing the original data.

2. Inferring metabolite flux data.

3. Multi-organ OrganChat analysis between spleen, small intestine, lymph node, lung, and vasculature.

4. Comparison analysis between two donors for: small intestine and vasculature, lung and vasculature, lymph node and vasculature, respectively.