Analysis of germline-driven ancestry-associated gene expression in cancers
oleh: Nyasha Chambwe, Rosalyn W. Sayaman, Donglei Hu, Scott Huntsman, Anab Kemal, Samantha Caesar-Johnson, Jean C. Zenklusen, Elad Ziv, Rameen Beroukhim, Andrew D. Cherniack, Jian Carrot-Zhang, Ashton C. Berger, Seunghun Han, Matthew Meyerson, Jeffrey S. Damrauer, Katherine A. Hoadley, Ina Felau, John A. Demchok, Michael K.A. Mensah, Roy Tarnuzzer, Zhining Wang, Liming Yang, Theo A. Knijnenburg, A. Gordon Robertson, Christina Yau, Christopher Benz, Kuan-lin Huang, Justin Y. Newberg, Garrett M. Frampton, R. Jay Mashl, Li Ding, Alessandro Romanel, Francesca Demichelis, Wanding Zhou, Peter W. Laird, Hui Shen, Christopher K. Wong, Joshua M. Stuart, Alexander J. Lazar, Xiuning Le, Ninad Oak
| Format: | Article |
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| Diterbitkan: | Elsevier 2022-09-01 |
Deskripsi
Summary: Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort.For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.