학술논문
Analytical protocol to identify local ancestry-associated molecular features in cancer
Document Type
article
Author
Jian Carrot-Zhang; Seunghun Han; Wanding Zhou; Jeffrey S. Damrauer; Anab Kemal; Andrew D. Cherniack; Rameen Beroukhim; Ashton C. Berger; Matthew Meyerson; Katherine A. Hoadley; Ina Felau; Samantha Caesar-Johnson; John A. Demchok; Michael K.A. Mensah; Roy Tarnuzzer; Zhining Wang; Liming Yang; Jean C. Zenklusen; Nyasha Chambwe; Theo A. Knijnenburg; A. Gordon Robertson; Christina Yau; Christopher Benz; Kuan-lin Huang; Justin Newberg; Garret Frampton; R. Jay Mashl; Li Ding; Alessandro Romanel; Francesca Demichelis; Rosalyn W. Sayaman; Elad Ziv; Peter W. Laird; Hui Shen; Christopher K. Wong; Joshua M. Stuart; Alexander J. Lazar; Xiuning Le; Ninad Oak
Source
STAR Protocols, Vol 2, Iss 4, Pp 100766- (2021)
Subject
Language
English
ISSN
2666-1667
Abstract
Summary: 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).