A Bayesian model for unsupervised detection of RNA splicing based subtypes in cancers

David Wang; Mathieu Quesnel-Vallieres; San Jewell; Moein Elzubeir; Kristen Lynch; Andrei Thomas-Tikhonenko; Yoseph Barash

doi:10.1038/s41467-022-35369-0

Nature Communications (Jan 2023)

A Bayesian model for unsupervised detection of RNA splicing based subtypes in cancers

David Wang,
Mathieu Quesnel-Vallieres,
San Jewell,
Moein Elzubeir,
Kristen Lynch,
Andrei Thomas-Tikhonenko,
Yoseph Barash

Affiliations

David Wang: Department of Genetics, Perelman School of Medicine, University of Pennsylvania
Mathieu Quesnel-Vallieres: Department of Genetics, Perelman School of Medicine, University of Pennsylvania
San Jewell: Department of Genetics, Perelman School of Medicine, University of Pennsylvania
Moein Elzubeir: Department of Genetics, Perelman School of Medicine, University of Pennsylvania
Kristen Lynch: Department of Genetics, Perelman School of Medicine, University of Pennsylvania
Andrei Thomas-Tikhonenko: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania
Yoseph Barash: Department of Genetics, Perelman School of Medicine, University of Pennsylvania

DOI: https://doi.org/10.1038/s41467-022-35369-0
Journal volume & issue: Vol. 14, no. 1
pp. 1 – 15

Abstract

Read online

RNA splicing variations could help identify cancer subtypes, but this task is computationally challenging. Here, the authors develop CHESSBOARD, a Bayesian tile finding algorithm for splicing data which identifies patterns in the form of tiles and can discover leukemia subgroups associated with therapeutic response.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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