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MARV is based on a method that collapses rare variants within a genomic region and models the proportion of minor alleles in the rare variants on a linear combination of multiple phenotypes.

  • Enables analysis of both continuous and binary phenotypes, as well as genotyped, imputed or sequenced data

  • Analyses all phenotype combinations within one run and calculates Bayesian Information Criterion to facilitate model selection

  • Computationally efficient: Number of phenotypes has little effect both on running time and required memory (though size of gentic data does increase running time)

  • Uses command line interface, similar to widely-used GWAS software such as Plink and SNPTEST 

  • Demonstrated with analysis of triglycerides (TG), fasting insulin (FI) and waist-to-hip ratio (WHR) in 4,721 individuals from the Northern Finland Birth Cohort 1966. DOI:10.1186/s12859-017-1530-2

 Figure above from Ref 2


MARV can be downloaded via the following link (GitHub):




For more information on MARV, please see the following references:

1. Kaakinen et al. (2017) MARV: a tool of genome-wide multi-phenotype analysis of rare variants, BMC Bioinformatics 18:110, DOI:10.1186/s12859-017-1530-2

2. Kaakinen et al. (2017) A rare-variant test for high-dimensional data, Eur J Human Genetics 25:988-94, DOI: 10.1038/ejhg.2017.90


 Internal case number 8156



A tool for genome-wide multi-phenotype analysis of rare variants

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