Strategies for detecting and identifying biological signals amidst the variation commonly found in RNA sequencing data.

ABSTRACT:

Background

RNA sequencing analysis focus on the detection of differential gene expression changes that meet a two-fold minimum change between groups. The variability present in RNA sequencing data may obscure the detection of valuable information when specific genes within certain samples display large expression variability. This paper develops methods that apply variance and dispersion estimates to intra-group data to identify genes with expression values that diverge from the group envelope. STRING database analysis of the identified genes characterize gene affiliations involved in physiological regulatory networks that contribute to biological variability. Individuals with divergent gene groupings within network pathways can thereby be identified and judiciously evaluated prior

SUBMITTER: Wilfinger WW 

PROVIDER: S-EPMC8091537 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature