title: ASSIMILATOR: a new tool to inform selection of associated genetic variants for functional studies.
abstract: BACKGROUND
  Fine-mapping experiments from genome-wide association studies (GWAS) are underway for many complex diseases. These are likely to identify a number of putative causal variants, which cannot be separated further in terms of strength of genetic association due to linkage disequilibrium. The challenge will be selecting which variant to prioritize for subsequent expensive functional studies. A wealth of functional information generated from wet lab experiments now exists but cannot be easily interrogated by the user. Here, we describe a program designed to quickly assimilate this data called ASSIMILATOR and validate the method by interrogating two regions to show its effectiveness.
  
  
  BACKGROUND
  http://www.medicine.manchester.ac.uk/musculoskeletal/research/arc/genetics/bioinformatics/assimilator/.
authors.affiliation: Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK. paul.martin-2@manchester.ac.uk
authors.forename: Paul
authors.initials: P
authors.lastname: Martin
authors.forename: Anne
authors.initials: A
authors.lastname: Barton
authors.forename: Stephen
authors.initials: S
authors.lastname: Eyre
mesh_terms: D055106:Genome-Wide Association Study; D020641:Polymorphism, Single Nucleotide; D012984:Software