Dividing out quantification uncertainty allows efficient assessment of differential transcript expression with edgeR.

ABSTRACT: Differential expression analysis of RNA-seq is one of the most commonly performed bioinformatics analyses. Transcript-level quantifications are inherently more uncertain than gene-level read counts because of ambiguous assignment of sequence reads to transcripts. While sequence reads can usually be assigned unambiguously to a gene, reads are very often compatible with multiple transcripts for that gene, particularly for genes with many isoforms. Software tools designed for gene-level differential expression do not perform optimally on transcript counts because the read-to-transcript ambiguity (RTA) disrupts the mean-variance relationship normally observed for gene level RNA-seq data and interferes with the efficiency of the empirical Bayes dispersion estimation procedures. The pseudoaligne

SUBMITTER: Baldoni PL 

PROVIDER: S-EPMC10853777 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature