Tempora: Cell trajectory inference using time-series single-cell RNA sequencing data.

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) can map cell types, states and transitions during dynamic biological processes such as tissue development and regeneration. Many trajectory inference methods have been developed to order cells by their progression through a dynamic process. However, when time series data is available, most of these methods do not consider the available time information when ordering cells and are instead designed to work only on a single scRNA-seq data snapshot. We present Tempora, a novel cell trajectory inference method that orders cells using time information from time-series scRNA-seq data. In performance comparison tests, Tempora inferred known developmental lineages from three diverse tissue development time series data sets, beating state of the art methods in

SUBMITTER: Tran TN 

PROVIDER: S-EPMC7505465 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature