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A Bayesian grouped mixture of regressions model capable of estimating SNP marker effect sizes for multiple outcomes simultaneously

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gmrm

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Welcome to the home of our gmrm software. The code is hybrid-parallel software for a Bayesian grouped mixture of regressions model for genome-wide association studies (GWAS). It is written in C++ using extensive optimisations and code vectorisation. It relies on plink's .bed format. It can analyse multiple traits simultaneously.

For an overview, help with compilation, and a documented workflow example please see our wiki: https://github.com/medical-genomics-group/gmrm/wiki

The software was developed by Etienne Orliac and Matthew R. Robinson. Funding was provided by a Swiss National Science Foundation Eccellenza Grant to MRR (PCEGP3-181181), and by core funding from the Institute of Science and Technology Austria.

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A Bayesian grouped mixture of regressions model capable of estimating SNP marker effect sizes for multiple outcomes simultaneously

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