Ontology highlight
ABSTRACT: Background
There is growing interest in retained introns in a variety of disease contexts including cancer and aging. Many software tools have been developed to detect retained introns from short RNA-seq reads, but reliable detection is complicated by overlapping genes and transcripts as well as the presence of unprocessed or partially processed RNAs.Results
We compared introns detected by 8 tools using short RNA-seq reads with introns observed in long RNA-seq reads from the same biological specimens. We found significant disagreement among tools (Fleiss' [Formula: see text]) such that 47.7% of all detected intron retentions were not called by more than one tool. We also observed poor performance of all tools, with none achieving an F1-score greater than 0.26, and qualitatively different behaviors between general-purpose alternative splicing detection tools and tools confined to retained intron detection.Conclusions
Short-read tools detect intron retention with poor recall and precision, calling into question the completeness and validity of a large percentage of putatively retained introns called by commonly used methods.
SUBMITTER: David JK
PROVIDER: S-EPMC9652823 | biostudies-literature | 2022 Nov
REPOSITORIES: biostudies-literature
David Julianne K JK Maden Sean K SK Wood Mary A MA Thompson Reid F RF Nellore Abhinav A
Genome biology 20221111 1
<h4>Background</h4>There is growing interest in retained introns in a variety of disease contexts including cancer and aging. Many software tools have been developed to detect retained introns from short RNA-seq reads, but reliable detection is complicated by overlapping genes and transcripts as well as the presence of unprocessed or partially processed RNAs.<h4>Results</h4>We compared introns detected by 8 tools using short RNA-seq reads with introns observed in long RNA-seq reads from the same ...[more]