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Analytical protocol to identify local ancestry-associated molecular features in cancer

People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the “local” ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to i...

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Autores principales: Carrot-Zhang, Jian, Han, Seunghun, Zhou, Wanding, Damrauer, Jeffrey S., Kemal, Anab, Cherniack, Andrew D., Beroukhim, Rameen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456058/
https://www.ncbi.nlm.nih.gov/pubmed/34585150
http://dx.doi.org/10.1016/j.xpro.2021.100766
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author Carrot-Zhang, Jian
Han, Seunghun
Zhou, Wanding
Damrauer, Jeffrey S.
Kemal, Anab
Cherniack, Andrew D.
Beroukhim, Rameen
author_facet Carrot-Zhang, Jian
Han, Seunghun
Zhou, Wanding
Damrauer, Jeffrey S.
Kemal, Anab
Cherniack, Andrew D.
Beroukhim, Rameen
author_sort Carrot-Zhang, Jian
collection PubMed
description People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the “local” ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).
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spelling pubmed-84560582021-09-27 Analytical protocol to identify local ancestry-associated molecular features in cancer Carrot-Zhang, Jian Han, Seunghun Zhou, Wanding Damrauer, Jeffrey S. Kemal, Anab Cherniack, Andrew D. Beroukhim, Rameen STAR Protoc Protocol People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the “local” ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020). Elsevier 2021-09-20 /pmc/articles/PMC8456058/ /pubmed/34585150 http://dx.doi.org/10.1016/j.xpro.2021.100766 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Carrot-Zhang, Jian
Han, Seunghun
Zhou, Wanding
Damrauer, Jeffrey S.
Kemal, Anab
Cherniack, Andrew D.
Beroukhim, Rameen
Analytical protocol to identify local ancestry-associated molecular features in cancer
title Analytical protocol to identify local ancestry-associated molecular features in cancer
title_full Analytical protocol to identify local ancestry-associated molecular features in cancer
title_fullStr Analytical protocol to identify local ancestry-associated molecular features in cancer
title_full_unstemmed Analytical protocol to identify local ancestry-associated molecular features in cancer
title_short Analytical protocol to identify local ancestry-associated molecular features in cancer
title_sort analytical protocol to identify local ancestry-associated molecular features in cancer
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456058/
https://www.ncbi.nlm.nih.gov/pubmed/34585150
http://dx.doi.org/10.1016/j.xpro.2021.100766
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