Identifying Cell Subpopulations and Their Genetic Drivers from Single-Cell RNA-Seq Data Using a Biclustering Approach.

ABSTRACT: Single-cell RNA-Seq (scRNA-Seq) has attracted much attention recently because it allows unprecedented resolution into cellular activity; the technology, therefore, has been widely applied in studying cell heterogeneity such as the heterogeneity among embryonic cells at varied developmental stages or cells of different cancer types or subtypes. A pertinent question in such analyses is to identify cell subpopulations as well as their associated genetic drivers. Consequently, a multitude of approaches have been developed for clustering or biclustering analysis of scRNA-Seq data. In this article, we present a fast and simple iterative biclustering approach called "BiSNN-Walk" based on the existing SNN-Cliq algorithm. One of BiSNN-Walk's differentiating features is that it returns a ranked list

SUBMITTER: Shi F 

PROVIDER: S-EPMC5510693 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature