A junction coverage compatibility score to quantify the reliability of transcript abundance estimates and annotation catalogs

Charlotte Soneson, Michael I. Love, Rob Patro, Shobbir Hussain, Dheeraj Malhotra, Mark D. Robinson

Research output: Contribution to journalArticlepeer-review

12 Citations (SciVal)

Abstract

Most methods for statistical analysis of RNA-seq data take a matrix of abundance estimates for some type of genomic features as their input, and consequently the quality of any obtained results is directly dependent on the quality of these abundances. Here, we present the junction coverage compatibility (JCC) score, which provides a way to evaluate the reliability of transcript-level abundance estimates as well as the accuracy of transcript annotation catalogs. It works by comparing the observed number of reads spanning each annotated splice junction in a genomic region to the predicted number of junction-spanning reads, inferred from the estimated transcript abundances and the genomic coordinates of the corresponding annotated transcripts. We show that while most genes show good agreement between the observed and predicted junction coverages, there is a small set of genes that do not. Genes with poor agreement are found regardless of the method used to estimate transcript abundances, and the corresponding transcript abundances should be treated with care in any downstream analyses.
Original languageEnglish
Article numbere201800175
JournalLife Science Alliance
Volume2
Issue number1
Early online date17 Jan 2019
DOIs
Publication statusPublished - 1 Feb 2019

Bibliographical note

© 2019 Soneson et al.

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