Integrative modeling identifies genetic ancestry-associated molecular correlates in human cancer.
Journal: STAR Protocols
Published:
Abstract
Cellular and molecular aberrations contribute to the disparity of human cancer incidence and etiology between ancestry groups. Multiomics profiling in The Cancer Genome Atlas (TCGA) allows for querying of the molecular underpinnings of ancestry-specific discrepancies in human cancer. Here, we provide a protocol for integrative associative analysis of ancestry with molecular correlates, including somatic mutations, DNA methylation, mRNA transcription, miRNA transcription, and pathway activity, using TCGA data. This protocol can be generalized to analyze other cancer cohorts and human diseases. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).
Authors
A Robertson, Christina Yau, Jian Carrot Zhang, Jeffrey Damrauer, Theo Knijnenburg, Nyasha Chambwe, Katherine Hoadley, Anab Kemal, Jean Zenklusen, Andrew Cherniack, Rameen Beroukhim, Wanding Zhou