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Analysis of germline-driven ancestry-associated gene expression in cancers
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 da...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9356164/ https://www.ncbi.nlm.nih.gov/pubmed/35942349 http://dx.doi.org/10.1016/j.xpro.2022.101586 |
Sumario: | 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). |
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