Skip to main content
Journal ArticleOPEN ACCESS

BiMM: Efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements

Bioinformatics (2017) 33(15) 2405-2407
DOI: 10.1093/bioinformatics/btx166
7Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

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.

Cite

CITATION STYLE

APA

Pirinen, M., Benner, C., Marttinen, P., Järvelin, M. R., Rivas, M. A., & Ripatti, S. (2017). BiMM: Efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements. Bioinformatics, 33(15), 2405–2407. https://doi.org/10.1093/bioinformatics/btx166

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free