Analysis of germline-driven ancestry-associated gene expression in cancers.
washington; isb; seattle; genomics
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).
Chambwe, Nyasha; Sayaman, Rosalyn W; Hu, Donglei; Huntsman, Scott; Analysis Network, Cancer Genome; Kemal, Anab; Caesar-Johnson, Samantha; Zenklusen, Jean C; Ziv, Elad; Beroukhim, Rameen; and Cherniack, Andrew D, "Analysis of germline-driven ancestry-associated gene expression in cancers." (2022). Articles, Abstracts, and Reports. 6394.