DiPhiSeq: robust comparison of expression levels on RNA-Seq data with large sample sizes.

ABSTRACT:

Motivation

In the analysis of RNA-Seq data, detecting differentially expressed (DE) genes has been a hot research area in recent years and many methods have been proposed. DE genes show different average expression levels in different sample groups, and thus can be important biological markers. While generally very successful, these methods need to be further tailored and improved for cancerous data, which often features quite diverse expression in the samples from the cancer group, and this diversity is much larger than that in the control group.

Results

We propose a statistical method that can detect not only genes that show different average expressions, but also genes that show different diversities of expressions in different groups. These 'differentially dispersed' gen

SUBMITTER: Li J 

PROVIDER: S-EPMC6596898 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature