Detection of high variability in gene expression from single-cell RNA-seq profiling.

ABSTRACT:

Background

The advancement of the next-generation sequencing technology enables mapping gene expression at the single-cell level, capable of tracking cell heterogeneity and determination of cell subpopulations using single-cell RNA sequencing (scRNA-seq). Unlike the objectives of conventional RNA-seq where differential expression analysis is the integral component, the most important goal of scRNA-seq is to identify highly variable genes across a population of cells, to account for the discrete nature of single-cell gene expression and uniqueness of sequencing library preparation protocol for single-cell sequencing. However, there is lack of generic expression variation model for different scRNA-seq data sets. Hence, the objective of this study is to develop a gene expression varia

SUBMITTER: Chen HI 

PROVIDER: S-EPMC5001205 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature