Effects of transcriptional noise on estimates of gene and transcript expression in RNA sequencing experiments.

ABSTRACT: RNA sequencing is widely used to measure gene expression across a vast range of animal and plant tissues and conditions. Most studies of computational methods for gene expression analysis use simulated data to evaluate the accuracy of these methods. These simulations typically include reads generated from known genes at varying levels of expression. Until now, simulations did not include reads from noisy transcripts, which might include erroneous transcription, erroneous splicing, and other processes that affect transcription in living cells. Here we examine the effects of realistic amounts of transcriptional noise on the ability of leading computational methods to assemble and quantify the genes and transcripts in an RNA sequencing experiment. We show that the inclusion of noise leads to

SUBMITTER: Varabyou A 

PROVIDER: S-EPMC7849408 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature