Reproducibility of Methods to Detect Differentially Expressed Genes from Single-Cell RNA Sequencing.

ABSTRACT: Detection of differentially expressed genes is a common task in single-cell RNA-seq (scRNA-seq) studies. Various methods based on both bulk-cell and single-cell approaches are in current use. Due to the unique distributional characteristics of single-cell data, it is important to compare these methods with rigorous statistical assessments. In this study, we assess the reproducibility of 9 tools for differential expression analysis in scRNA-seq data. These tools include four methods originally designed for scRNA-seq data, three popular methods originally developed for bulk-cell RNA-seq data but have been applied in scRNA-seq analysis, and two general statistical tests. Instead of comparing the performance across all genes, we compare the methods in terms of the rediscovery rates (RDRs) of t

SUBMITTER: Mou T 

PROVIDER: S-EPMC6979262 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature