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

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 Anal...

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Autores principales: Chevalier, Aaron, Yang, Shiyi, Khurshid, Zainab, Sahelijo, Nathan, Tong, Tong, Huggins, Jonathan H., Yajima, Masanao, Campbell, Joshua D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8639789/
https://www.ncbi.nlm.nih.gov/pubmed/34625425
http://dx.doi.org/10.1158/0008-5472.CAN-21-0899
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author Chevalier, Aaron
Yang, Shiyi
Khurshid, Zainab
Sahelijo, Nathan
Tong, Tong
Huggins, Jonathan H.
Yajima, Masanao
Campbell, Joshua D.
author_facet Chevalier, Aaron
Yang, Shiyi
Khurshid, Zainab
Sahelijo, Nathan
Tong, Tong
Huggins, Jonathan H.
Yajima, Masanao
Campbell, Joshua D.
author_sort Chevalier, Aaron
collection PubMed
description 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. SIGNIFICANCE: 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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spelling pubmed-86397892022-06-01 The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures Chevalier, Aaron Yang, Shiyi Khurshid, Zainab Sahelijo, Nathan Tong, Tong Huggins, Jonathan H. Yajima, Masanao Campbell, Joshua D. Cancer Res Resource Report 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. SIGNIFICANCE: 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. American Association for Cancer Research 2021-12-01 2021-10-08 /pmc/articles/PMC8639789/ /pubmed/34625425 http://dx.doi.org/10.1158/0008-5472.CAN-21-0899 Text en ©2021 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.
spellingShingle Resource Report
Chevalier, Aaron
Yang, Shiyi
Khurshid, Zainab
Sahelijo, Nathan
Tong, Tong
Huggins, Jonathan H.
Yajima, Masanao
Campbell, Joshua D.
The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures
title The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures
title_full The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures
title_fullStr The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures
title_full_unstemmed The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures
title_short The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures
title_sort mutational signature comprehensive analysis toolkit (musicatk) for the discovery, prediction, and exploration of mutational signatures
topic Resource Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8639789/
https://www.ncbi.nlm.nih.gov/pubmed/34625425
http://dx.doi.org/10.1158/0008-5472.CAN-21-0899
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