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

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 compatibi...

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Bibliographic Details
Published in:	Life science alliance 2019-02, Vol.2 (1), p.e201800175
Main Authors:	Soneson, Charlotte, Love, Michael I, Patro, Rob, Hussain, Shobbir, Malhotra, Dheeraj, Robinson, Mark D
Format:	Article
Language:	eng
Subjects:	3' Untranslated Regions - genetics Data Accuracy Exons - genetics Genes - genetics Genome, Human - genetics Genomic Library Humans Introns - genetics Protein Isoforms - genetics Reproducibility of Results Research Design RNA Precursors - genetics RNA-Seq Transcriptome - genetics
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Summary:	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 score, which provides a way to evaluate the reliability of transcript-level abundance estimates and 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 although 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.
ISSN:	2575-1077 2575-1077