title: ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data.
abstract: OBJECTIVE
  There is increasing evidence that rare variants play a role in some complex traits, but their analysis is not straightforward. Locus-based tests become necessary due to low power in rare variant single-point association analyses. In addition, variant quality scores are available for sequencing data, but are rarely taken into account. Here, we propose two locus-based methods that incorporate variant quality scores: a regression-based collapsing approach and an allele-matching method.
  
  
  METHODS
  Using simulated sequencing data we compare 4 locus-based tests of trait association under different scenarios of data quality. We test two collapsing-based approaches and two allele-matching-based approaches, taking into account variant quality scores and ignoring variant quality scores. We implement the collapsing and allele-matching approaches accounting for variant quality in the freely available ARIEL and AMELIA software.
  
  
  RESULTS
  The incorporation of variant quality scores in locus-based association tests has power advantages over weighting each variant equally. The allele-matching methods are robust to the presence of both protective and risk variants in a locus, while collapsing methods exhibit a dramatic loss of power in this scenario.
  
  
  CONCLUSIONS
  The incorporation of variant quality scores should be a standard protocol when performing locus-based association analysis on sequencing data. The ARIEL and AMELIA software implement collapsing and allele-matching locus association analysis methods, respectively, that allow the incorporation of variant quality scores.
authors.affiliation: Wellcome Trust Sanger Institute, Hinxton, UK.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Asimit
authors.forename: Aaron G
authors.initials: AG
authors.lastname: Day-Williams
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Morris
authors.forename: Eleftheria
authors.initials: E
authors.lastname: Zeggini
mesh_terms: D000483:Alleles; D003198:Computer Simulation; D056726:Genetic Association Studies; D014644:Genetic Variation; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D012984:Software