airpart

AirPart is a software tool that analyzes allelic expression data from single-cell RNA sequencing experiments. It identifies differentially expressed genes based on their allelic ratios and provides insights into cis-regulatory mechanisms of genetic variation. The tool uses a statistical method called airpart to identify cell type-specific, spatial, or time-dependent AI signals. It outputs discrete partitions of data, highlighting groups of genes and cells under common mechanisms of cis-genetic regulation. To account for low counts in single-cell data, AirPart uses a Generalized Fused Lasso with Binomial likelihood for partitioning groups of cells by AI signal and a hierarchical Bayesian model for AI statistical inference.