Detecting differentially expressed circular RNAs from multiple quantification methods using a generalized linear mixed model.

ABSTRACT: Finding differentially expressed circular RNAs (circRNAs) is instrumental to understanding the molecular basis of phenotypic variation between conditions linked to circRNA-involving mechanisms. To date, several methods have been developed to identify circRNAs, and combining multiple tools is becoming an established approach to improve the detection rate and robustness of results in circRNA studies. However, when using a consensus strategy, it is unclear how circRNA expression estimates should be considered and integrated into downstream analysis, such as differential expression assessment. This work presents a novel solution to test circRNA differential expression using quantifications of multiple algorithms simultaneously. Our approach analyzes multiple tools' circRNA abundance count data

SUBMITTER: Buratin A 

PROVIDER: S-EPMC9136258 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature