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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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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). |
format | Online Article Text |
id | pubmed-8456058 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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