Document Type
Article
Publication Date
7-12-2023
Original Citation
Wu E,
Singh N,
Choi K,
Zakeri M,
Vincent M,
Churchill G,
Ackert-Bicknell C,
Patro R,
Love M.
SEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty. Genome Biol. 2023;24(1):165.
Keywords
JMG, Uncertainty, Allelic Imbalance, Protein Isoforms, RNA-Seq, Transcription Initiation Site
JAX Source
Genome Biol. 2023;24(1):165.
ISSN
1474-760X
PMID
37438847
DOI
https://doi.org/10.1186/s13059-023-03003-x
Grant
• NSF CCF‐1750472 and CNS‐1763680: Rob Patro, Noor P Singh, Mohsen Zakeri. • NIH R01 HG009937: Rob Patro, Noor P Singh, Mohsen Zakeri, Michael I Love. • NIH T32 CA106209: Euphy Wu. • NIH R01 GM070683: Gary A Churchill, Matthew Vincent.
Abstract
Detecting 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.
Comments
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