Rxivist logo

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

By Matti Pirinen, Christian Benner, Pekka Marttinen, Marjo-Riitta Järvelin, Manuel A. Rivas, Samuli Ripatti

Posted 15 Nov 2016
bioRxiv DOI: 10.1101/087932 (published DOI: 10.1093/bioinformatics/btx166)

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. Implementation in R freely available at www.iki.fi/mpirinen.

Download data

  • Downloaded 504 times
  • Download rankings, all-time:
    • Site-wide: 30,887 out of 89,138
    • In genetics: 1,859 out of 4,612
  • Year to date:
    • Site-wide: 86,049 out of 89,138
  • Since beginning of last month:
    • Site-wide: 85,351 out of 89,138

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)