Variational inference for detecting differential translation in ribosome profiling studies.

ABSTRACT: Translational efficiency change is an important mechanism for regulating protein synthesis. Experiments with paired ribosome profiling (Ribo-seq) and mRNA-sequencing (RNA-seq) allow the study of translational efficiency by simultaneously quantifying the abundances of total transcripts and those that are being actively translated. Existing methods for Ribo-seq data analysis either ignore the pairing structure in the experimental design or treat the paired samples as fixed effects instead of random effects. To address these issues, we propose a hierarchical Bayesian generalized linear mixed effects model which incorporates a random effect for the paired samples according to the experimental design. We provide an analytical software tool, "riboVI," that uses a novel variational Bayesian algor

SUBMITTER: Walker DC 

PROVIDER: S-EPMC10326721 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature