Cost effective, experimentally robust differential-expression analysis for human/mammalian, pathogen and dual-species transcriptomics.

ABSTRACT: As sequencing read length has increased, researchers have quickly adopted longer reads for their experiments. Here, we examine 14 pathogen or host-pathogen differential gene expression data sets to assess whether using longer reads is warranted. A variety of data sets was used to assess what genomic attributes might affect the outcome of differential gene expression analysis including: gene density, operons, gene length, number of introns/exons and intron length. No genome attribute was found to influence the data in principal components analysis, hierarchical clustering with bootstrap support, or regression analyses of pairwise comparisons that were undertaken on the same reads, looking at all combinations of paired and unpaired reads trimmed to 36, 54, 72 and 101 bp. Read pairing had the

SUBMITTER: Shetty AC 

PROVIDER: S-EPMC7067034 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature