Package: MRCCC 0.99.4

MRCCC: Bayesian Mendelian Randomization for Causal Cell-Cell Communication

Implements MR-CCC, a Bayesian Mendelian randomization framework for inferring causal ligand-receptor signalling between cell types from population-scale single-cell expression and genotype data. For each ligand-receptor-pathway triplet, cis-eQTL genotypes instrument ligand expression in the sender cell type and receptor expression in the receiver cell type, and a working model with a ligand-by-receptor interaction is fitted to downstream pathway activity by a blocked Gibbs sampler. A spike-and-slab prior on the causal block yields a posterior inclusion probability that serves as the communication score, and the retained draws support credible intervals, sign probabilities, the receptor level at which the ligand effect reverses sign, and Bayesian false discovery rate control across many triplets.

Authors:Bitan Sarkar [aut, cre], Yang Ni [aut]