A novel nonlinear dimension reduction approach to infer population structure for low-coverage sequencing data

BACKGROUND: Low-depth sequencing allows researchers to increase sample size at the expense of lower accuracy. To incorporate uncertainties while maintaining statistical power, we introduce MCPCA_PopGen to analyze population structure of low-depth sequencing data. RESULTS: The method optimizes the ch...

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Detalles Bibliográficos
Autores principales: Zhang, Miao, Liu, Yiwen, Zhou, Hua, Watkins, Joseph, Zhou, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236193/
https://www.ncbi.nlm.nih.gov/pubmed/34174829
http://dx.doi.org/10.1186/s12859-021-04265-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236193/
https://www.ncbi.nlm.nih.gov/pubmed/34174829
http://dx.doi.org/10.1186/s12859-021-04265-7

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