Uncovering pseudotemporal trajectories with covariates from single cell and bulk expression data

摘要

Cross-sectional omic data often have non-homogeneous genetic, phenotypic, or environmental backgrounds. Here, the authors develop a statistical framework to infer pseudotime trajectories in the presence of such factors as well as their interactions in both single-cell and bulk gene expression analysis