biMM : efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements
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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 |
| Contributor organization: | Department of Mathematics and Statistics Institute for Molecular Medicine Finland Biostatistics Helsinki University of Helsinki Helsinki Institute for Information Technology Clinicum Department of Public Health Samuli Olli Ripatti / Principal Investigator Complex Disease Genetics Statistical and population genetics |
| 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 |
| Peer reviewed: | Yes |
| Rights: | cc_by |
| Usage restriction: | openAccess |
| Self-archived version: | publishedVersion |
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