Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models

BACKGROUND: Numerous approaches have been proposed for the detection of epistatic interactions within GWAS datasets in order to better understand the drivers of disease and genetics. METHODS: A selection of state-of-the-art approaches were assessed. These included the statistical tests, fast-epistas...

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Detalles Bibliográficos
Autores principales: Russ, Dominic, Williams, John A., Cardoso, Victor Roth, Bravo-Merodio, Laura, Pendleton, Samantha C., Aziz, Furqan, Acharjee, Animesh, Gkoutos, Georgios V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856572/
https://www.ncbi.nlm.nih.gov/pubmed/35180244
http://dx.doi.org/10.1371/journal.pone.0263390

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856572/
https://www.ncbi.nlm.nih.gov/pubmed/35180244
http://dx.doi.org/10.1371/journal.pone.0263390

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