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| Item Type: | Preprint |
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| Title: | LIMIX: genetic analysis of multiple traits |
| Creators Name: | Lippert, C. and Casale, F.P. and Rakitsch, B. and Stegle, O. |
| Abstract: | Multi-trait mixed models have emerged as a promising approach for joint analyses of multiple traits. In principle, the mixed model framework is remarkably general. However, current methods implement only a very specific range of tasks to optimize the necessary computations. Here, we present a multi-trait modeling framework that is versatile and fast: LIMIX enables to exibly adapt mixed models for a broad range of applications with different observed and hidden covariates, and variable study designs. To highlight the novel modeling aspects of LIMIX we performed three vastly different genetic studies: joint GWAS of correlated blood lipid phenotypes, joint analysis of the expression levels of the multiple transcript-isoforms of a gene, and pathway-based modeling of molecular traits across environments. In these applications we show that LIMIX increases GWAS power and phenotype prediction accuracy, in particular when integrating stepwise multi-locus regression into multi-trait models, and when analyzing large numbers of traits. An open source implementation of LIMIX is freely available at: https://github.com/PMBio/limix. |
| Source: | bioRxiv |
| Publisher: | Cold Spring Harbor Laboratory Press |
| Article Number: | 003905 |
| Date: | 22 May 2014 |
| Official Publication: | https://doi.org/10.1101/003905 |
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