HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes

MOTIVATION: Existing methods for simulating synthetic genotype and phenotype datasets have limited scalability, constraining their usability for large-scale analyses. Moreover, a systematic approach for evaluating synthetic data quality and a benchmark synthetic dataset for developing and evaluating...

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Detalles Bibliográficos
Autores principales: Wharrie, Sophie, Yang, Zhiyu, Raj, Vishnu, Monti, Remo, Gupta, Rahul, Wang, Ying, Martin, Alicia, O’Connor, Luke J, Kaski, Samuel, Marttinen, Pekka, Palamara, Pier Francesco, Lippert, Christoph, Ganna, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493177/
https://www.ncbi.nlm.nih.gov/pubmed/37647640
http://dx.doi.org/10.1093/bioinformatics/btad535

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493177/
https://www.ncbi.nlm.nih.gov/pubmed/37647640
http://dx.doi.org/10.1093/bioinformatics/btad535

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