title: A pragmatic suggestion for dealing with results for candidate genes obtained from genome wide association studies.
abstract: BACKGROUND
  Researchers may embark on a genome-wide association study before fully investigating candidate regions which have been reported to produce evidence to suggest that they harbour susceptibility loci. If the genome wide study had not been carried out then results which demonstrated only modest statistical significance from candidate regions would be judged to be of interest and would stimulate further investigation. However if hundreds of thousands of markers are typed then inevitably very large numbers of such results will occur by chance and those from candidate regions may attract no special attention.
  
  
  RESULTS
  An approach is proposed in which differential treatment is afforded to markers from candidate regions and from those that are routinely typed in the context of a genome wide scan. Different prior probabilities are assigned to the two types of marker. A likelihood ratio is derived from the reported p value for each marker, calculated as LR = echiinv(1,p)/2, and the posterior odds in favour of a true positive association are obtained. These odds can be used to rank the markers with a view to suggesting the regions in which further genotyping is indicated. We suggest that prior probabilities be specified such that a candidate marker significant at p = 0.01 and a routine marker significant at p = 0.00001 will yield similar values for the posterior odds. We show that this can be achieved by setting a value for prior probability of association to 0.1 for candidate markers and to 0.00018 for routine markers.
  
  
  CONCLUSIONS
  It is essential that formal procedures be adopted in order to avoid modestly positively results from candidate regions being swamped by the huge number of nominally significant results which will be obtained when very many markers are genotyped. Software to carry out the conversion from p values to posterior odds is available from http://www.mds.qmul.ac.uk/statgen/grpsoft.html.
authors.affiliation: Centre for Psychiatry, Queen Mary's School of Medicine and Dentistry, London, UK. david.curtis@qmul.ac.uk
authors.forename: David
authors.initials: D
authors.lastname: Curtis
authors.forename: Anna E
authors.initials: AE
authors.lastname: Vine
authors.forename: Jo
authors.initials: J
authors.lastname: Knight
mesh_terms: D001499:Bayes Theorem; D005189:False Positive Reactions; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D015894:Genome, Human; D006801:Humans; D016013:Likelihood Functions
chemical_list: D005819:Genetic Markers