Switchde: inference of switch-like differential expression along single-cell trajectories.

ABSTRACT: Pseudotime analyses of single-cell RNA-seq data have become increasingly common. Typically, a latent trajectory corresponding to a biological process of interest-such as differentiation or cell cycle-is discovered. However, relatively little attention has been paid to modelling the differential expression of genes along such trajectories.We present switchde , a statistical framework and accompanying R package for identifying switch-like differential expression of genes along pseudotemporal trajectories. Our method includes fast model fitting that provides interpretable parameter estimates corresponding to how quickly a gene is up or down regulated as well as where in the trajectory such regulation occurs. It also reports a P -value in favour of rejecting a constant-expression model for switch-like differential expression and optionally models the zero-inflation prevalent in single-cell data.The R package switchde is available through the Bioconductor project at https://bioconductor.org/packages/switchde [e-mail] data are available at Bioinformatics online.

SUBMITTER: Campbell KR 

PROVIDER: S-EPMC5408844 | biostudies-other | 2017 Apr

REPOSITORIES: biostudies-other