title: Rapid genotype refinement for whole-genome sequencing data using multi-variate normal distributions.
abstract: Whole-genome low-coverage sequencing has been combined with linkage-disequilibrium (LD)-based genotype refinement to accurately and cost-effectively infer genotypes in large cohorts of individuals. Most genotype refinement methods are based on hidden Markov models, which are accurate but computationally expensive. We introduce an algorithm that models LD using a simple multivariate Gaussian distribution. The key feature of our algorithm is its speed.
  
  
  
  Our method is hundreds of times faster than other methods on the same data set and its scaling behaviour is linear in the number of samples. We demonstrate the performance of the method on both low- and high-coverage samples.
  
  
  
  The source code is available at https://github.com/illumina/marvin
  
  
  
  rarthur@illumina.com
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Illumina Cambridge Ltd, Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.
authors.forename: Rudy
authors.initials: R
authors.lastname: Arthur
authors.affiliation: Illumina Cambridge Ltd, Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.
authors.forename: Jared
authors.initials: J
authors.lastname: O'Connell
authors.affiliation: Illumina Cambridge Ltd, Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.
authors.forename: Ole
authors.initials: O
authors.lastname: Schulz-Trieglaff
authors.affiliation: Illumina Cambridge Ltd, Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.
authors.forename: Anthony J
authors.initials: AJ
authors.lastname: Cox
mesh_terms: D000465:Algorithms; D005838:Genotype; D006801:Humans; D015810:Linkage Disequilibrium; D016011:Normal Distribution; D012984:Software