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

Title: Analytical protocol to identify local ancestry-associated molecular features in cancer
Authors: Carrot-Zhang, Jian; Han, Seunghun; Zhou, Wanding; Damrauer, Jeffrey S; Kemal, Anab; Berger, Ashton C; Meyerson, Matthew; Hoadley, Katherine A; Felau, Ina; Caesar-Johnson, Samantha; Demchok, John A; Mensah, Michael Ka; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C; Chambwe, Nyasha; Knijnenburg, Theo A; Robertson, A Gordon; Yau, Christina; Benz, Christopher; Huang, Kuan-Lin; Newberg, Justin; Frampton, Garret; Mashl,R Jay; Ding, Li; Romanel, Alessandro; Demichelis, Francesca; Sayaman, Rosalyn W; Ziv, Elad; Laird, Peter W; Shen, Hui; Wong, Christopher K; Stuart, Joshua M; Lazar, Alexander J; Le, Xiuning; Oak, Ninad; Cherniack, Andrew D; Beroukhim, Rameen
Contributors: Carrot-Zhang, Jian; Han, Seunghun; Zhou, Wanding; Damrauer, Jeffrey S; Kemal, Anab; Berger, Ashton C; Meyerson, Matthew; Hoadley, Katherine A; Felau, Ina; Caesar-Johnson, Samantha; Demchok, John A; Mensah, Michael Ka; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C; Chambwe, Nyasha; Knijnenburg, Theo A; Robertson, A Gordon; Yau, Christina; Benz, Christopher; Huang, Kuan-Lin; Newberg, Justin; Frampton, Garret; Mashl, R Jay; Ding, Li; Romanel, Alessandro; Demichelis, Francesca; Sayaman, Rosalyn W; Ziv, Elad; Laird, Peter W; Shen, Hui; Wong, Christopher K; Stuart, Joshua M; Lazar, Alexander J; Le, Xiuning; Oak, Ninad; Cherniack, Andrew D; Beroukhim, Rameen
Publisher Information: USA
Publication Year: 2021
Collection: Università degli Studi di Trento: CINECA IRIS
Subject Terms: Bioinformatic; Cancer; Genomics
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 etal. (2020).
Document Type: article in journal/newspaper
Language: English
Relation: info:eu-repo/semantics/altIdentifier/pmid/34585150; info:eu-repo/semantics/altIdentifier/wos/WOS:001052433300005; volume:2; issue:4; firstpage:10076601; lastpage:10076615; numberofpages:15; journal:STAR PROTOCOLS; https://hdl.handle.net/11572/319802; https://www.sciencedirect.com/science/article/pii/S266616672100472X?via=ihub
DOI: 10.1016/j.xpro.2021.100766
Availability: https://hdl.handle.net/11572/319802; https://doi.org/10.1016/j.xpro.2021.100766; https://www.sciencedirect.com/science/article/pii/S266616672100472X?via=ihub
Rights: info:eu-repo/semantics/openAccess ; license:Creative commons ; license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/
Accession Number: edsbas.37CE101F
Database: BASE