Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated

Principal Component Analysis (PCA) is a multivariate analysis that reduces the complexity of datasets while preserving data covariance. The outcome can be visualized on colorful scatterplots, ideally with only a minimal loss of information. PCA applications, implemented in well-cited packages like E...

Descripción completa

Detalles Bibliográficos
Autor principal: Elhaik, Eran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424212/
https://www.ncbi.nlm.nih.gov/pubmed/36038559
http://dx.doi.org/10.1038/s41598-022-14395-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424212/
https://www.ncbi.nlm.nih.gov/pubmed/36038559
http://dx.doi.org/10.1038/s41598-022-14395-4

Ejemplares similares