title: minimac2: faster genotype imputation.
abstract: Genotype imputation is a key step in the analysis of genome-wide association studies. Upcoming very large reference panels, such as those from The 1000 Genomes Project and the Haplotype Consortium, will improve imputation quality of rare and less common variants, but will also increase the computational burden. Here, we demonstrate how the application of software engineering techniques can help to keep imputation broadly accessible. Overall, these improvements speed up imputation by an order of magnitude compared with our previous implementation.
  
  
  METHODS
  minimac2, including source code, documentation, and examples is available at http://genome.sph.umich.edu/wiki/Minimac2
authors.affiliation: Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA and 23andMe, Inc., Mountain View, CA, USA.
authors.forename: Christian
authors.initials: C
authors.lastname: Fuchsberger
authors.affiliation: Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA and 23andMe, Inc., Mountain View, CA, USA.
authors.forename: Gonçalo R
authors.initials: GR
authors.lastname: Abecasis
authors.affiliation: Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA and 23andMe, Inc., Mountain View, CA, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Hinds
mesh_terms: D019295:Computational Biology / Q000379:methods*; D055106:Genome-Wide Association Study; D005838:Genotype; D006239:Haplotypes / Q000235:genetics; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D011381:Programming Languages; D012984:Software