Choice of library size normalization and statistical methods for differential gene expression analysis in balanced two-group comparisons for RNA-seq studies.

ABSTRACT: BACKGROUND:High-throughput RNA sequencing (RNA-seq) has evolved as an important analytical tool in molecular biology. Although the utility and importance of this technique have grown, uncertainties regarding the proper analysis of RNA-seq data remain. Of primary concern, there is no consensus regarding which normalization and statistical methods are the most appropriate for analyzing this data. The lack of standardized analytical methods leads to uncertainties in data interpretation and study reproducibility, especially with studies reporting high false discovery rates. In this study, we compared a recently developed normalization method, UQ-pgQ2, with three of the most frequently used alternatives including RLE (relative log estimate), TMM (Trimmed-mean M values) and UQ (upper quartile no

SUBMITTER: Li X 

PROVIDER: S-EPMC6986029 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature