SEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty

Author:

Wu Euphy Y.,Singh Noor P.,Choi Kwangbom,Zakeri Mohsen,Vincent Matthew,Churchill Gary A.,Ackert-Bicknell Cheryl L.,Patro Rob,Love Michael I.ORCID

Abstract

AbstractDetecting allelic imbalance at the isoform level requires accounting for inferential uncertainty, caused by multi-mapping of RNA-seq reads. Our proposed method, SEESAW, uses Salmon and Swish to offer analysis at various levels of resolution, including gene, isoform, and aggregating isoforms to groups by transcription start site. The aggregation strategies strengthen the signal for transcripts with high uncertainty. The SEESAW suite of methods is shown to have higher power than other allelic imbalance methods when there is isoform-level allelic imbalance. We also introduce a new test for detecting imbalance that varies across a covariate, such as time.

Funder

National Human Genome Research Institute

National Science Foundation

Division of Cancer Prevention, National Cancer Institute

National Institute of General Medical Sciences

Publisher

Springer Science and Business Media LLC

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1. Challenges and best practices in omics benchmarking;Nature Reviews Genetics;2024-01-12

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