title: PSIKO2: a fast and versatile tool to infer population stratification on various levels in GWAS.
abstract: Genome-wide association studies are an invaluable tool for identifying genotypic loci linked with agriculturally important traits or certain diseases. The signal on which such studies rely upon can, however, be obscured by population stratification making it necessary to account for it in some way. Population stratification is dependent on when admixture happened and thus can occur at various levels. To aid in its inference at the genome level, we recently introduced psiko, and comparison with leading methods indicates that it has attractive properties. However, until now, it could not be used for local ancestry inference which is preferable in cases of recent admixture as the genome level tends to be too coarse to properly account for processes acting on small segments of a genome. To also bring the powerful ideas underpinning psiko to bear in such studies, we extended it to psiko2, which we introduce here.
  
  
  METHODS
  Source code, binaries and user manual are freely available at https://www.uea.ac.uk/computing/psiko.
  
  
  BACKGROUND
  Andrei-Alin.Popescu@uea.ac.uk or Katharina.Huber@cmp.uea.ac.uk
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.
authors.forename: Andrei-Alin
authors.initials: AA
authors.lastname: Popescu
authors.affiliation: School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.
authors.forename: Katharina T
authors.initials: KT
authors.lastname: Huber
mesh_terms: D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D006801:Humans; D044382:Population Groups / Q000235:genetics; D012984:Software