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Population Substructure Has Implications in Validating Next-Generation Cancer Genomics Studies with TCGA

In the era of large genetic and genomic datasets, it has become crucially important to validate results of individual studies using data from publicly available sources, such as The Cancer Genome Atlas (TCGA). However, how generalizable are results from either an independent or a large public datase...

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Detalles Bibliográficos
Autores principales: Miller, Marina D., Devor, Eric J., Salinas, Erin A., Newtson, Andreea M., Goodheart, Michael J., Leslie, Kimberly K., Gonzalez-Bosquet, Jesus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6429328/
https://www.ncbi.nlm.nih.gov/pubmed/30857229
http://dx.doi.org/10.3390/ijms20051192
Descripción
Sumario:In the era of large genetic and genomic datasets, it has become crucially important to validate results of individual studies using data from publicly available sources, such as The Cancer Genome Atlas (TCGA). However, how generalizable are results from either an independent or a large public dataset to the remainder of the population? The study presented here aims to answer that question. Utilizing next generation sequencing data from endometrial and ovarian cancer patients from both the University of Iowa and TCGA, genomic admixture of each population was analyzed using STRUCTURE and ADMIXTURE software. In our independent data set, one subpopulation was identified, whereas in TCGA 4–6 subpopulations were identified. Data presented here demonstrate how different the genetic substructures of the TCGA and University of Iowa populations are. Validation of genomic studies between two different population samples must be aware of, account for and be corrected for background genetic substructure.