Custom selected reference genes outperform pre-defined reference genes in transcriptomic analysis.

ABSTRACT:

Background

RNA sequencing allows the measuring of gene expression at a resolution unmet by expression arrays or RT-qPCR. It is however necessary to normalize sequencing data by library size, transcript size and composition, among other factors, before comparing expression levels. The use of internal control genes or spike-ins is advocated in the literature for scaling read counts, but the methods for choosing reference genes are mostly targeted at RT-qPCR studies and require a set of pre-selected candidate controls or pre-selected target genes.

Results

Here, we report an R-based pipeline to select internal control genes based solely on read counts and gene sizes. This novel method first normalizes the read counts to Transcripts per Million (TPM) and then excludes weakly expr

SUBMITTER: Dos Santos KCG 

PROVIDER: S-EPMC6954607 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature