American Association for Cancer Research
can-21-0899_supplemental_file_1_suppsd1.pdf (210.04 kB)

Supplemental File 1 from The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures

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journal contribution
posted on 2023-04-03, 22:23 authored by Aaron Chevalier, Shiyi Yang, Zainab Khurshid, Nathan Sahelijo, Tong Tong, Jonathan H. Huggins, Masanao Yajima, Joshua D. Campbell

Plate diagram and derivation of bayesian prediction algorithm


National Cancer Institute (NCI)

United States Department of Health and Human Services

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National Institute of General Medical Sciences (NIGMS)

United States Department of Health and Human Services

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Mutational signatures are patterns of somatic alterations in the genome caused by carcinogenic exposures or aberrant cellular processes. To provide a comprehensive workflow for preprocessing, analysis, and visualization of mutational signatures, we created the Mutational Signature Comprehensive Analysis Toolkit (musicatk) package. musicatk enables users to select different schemas for counting mutation types and to easily combine count tables from different schemas. Multiple distinct methods are available to deconvolute signatures and exposures or to predict exposures in individual samples given a pre-existing set of signatures. Additional exploratory features include the ability to compare signatures to the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, embed tumors in two dimensions with uniform manifold approximation and projection, cluster tumors into subgroups based on exposure frequencies, identify differentially active exposures between tumor subgroups, and plot exposure distributions across user-defined annotations such as tumor type. Overall, musicatk will enable users to gain novel insights into the patterns of mutational signatures observed in cancer cohorts. The musicatk package empowers researchers to characterize mutational signatures and tumor heterogeneity with a comprehensive set of preprocessing utilities, discovery and prediction tools, and multiple functions for downstream analysis and visualization.

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