biMM: efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements

SUMMARY: Genetic research utilizes a decomposition of trait variances and covariances into genetic and environmental parts. Our software package biMM is a computationally efficient implementation of a bivariate linear mixed model for settings where hundreds of traits have been measured on partially...

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Detalles Bibliográficos
Autores principales: Pirinen, Matti, Benner, Christian, Marttinen, Pekka, Järvelin, Marjo-Riitta, Rivas, Manuel A, Ripatti, Samuli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860115/
https://www.ncbi.nlm.nih.gov/pubmed/28369165
http://dx.doi.org/10.1093/bioinformatics/btx166
Descripción
Sumario:SUMMARY: Genetic research utilizes a decomposition of trait variances and covariances into genetic and environmental parts. Our software package biMM is a computationally efficient implementation of a bivariate linear mixed model for settings where hundreds of traits have been measured on partially overlapping sets of individuals. AVAILABILITY AND IMPLEMENTATION: Implementation in R freely available at www.iki.fi/mpirinen. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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