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

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http://hdl.handle.net/10138/209967

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Pirinen , M , Benner , C , Marttinen , P , Jarvelin , M-R , Rivas , M A & Ripatti , S 2017 , ' biMM : efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements ' , Bioinformatics , vol. 33 , no. 15 , pp. 2405-2407 . https://doi.org/10.1093/bioinformatics/btx166

Title: biMM : efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements
Author: Pirinen, Matti; Benner, Christian; Marttinen, Pekka; Jarvelin, Marjo-Riitta; Rivas, Manuel A.; Ripatti, Samuli
Other contributor: University of Helsinki, Department of Mathematics and Statistics
University of Helsinki, Clinicum
University of Helsinki, Helsinki Institute for Information Technology
University of Helsinki, Clinicum









Date: 2017-08-01
Language: eng
Number of pages: 3
Belongs to series: Bioinformatics
ISSN: 1367-4803
DOI: https://doi.org/10.1093/bioinformatics/btx166
URI: http://hdl.handle.net/10138/209967
Abstract: 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.
Subject: LINEAR MIXED-MODEL
ASSOCIATION
DISEASES
TRAITS
3111 Biomedicine
1184 Genetics, developmental biology, physiology
1182 Biochemistry, cell and molecular biology
1183 Plant biology, microbiology, virology
111 Mathematics
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