BGP: identifying gene-specific branching dynamics from single-cell data with a branching Gaussian process

BGP: identifying gene-specific branching dynamics from single-cell data with a branching Gaussian process

Blog Article

Abstract High-throughput single-cell gene expression experiments can be used to uncover branching dynamics in cell populations undergoing differentiation through pseudotime methods.We develop the branching Gaussian process (BGP), a non-parametric model that is able to identify branching dynamics for individual Ski de fond - Equipement - Bottes - Classic genes and provide an estimate of branching times for each gene with an associated credible region.We demonstrate the effectiveness of our method on simulated data, a single-cell RNA-seq haematopoiesis study and mouse embryonic Baskets stem cells generated using droplet barcoding.The method is robust to high levels of technical variation and dropout, which are common in single-cell data.