title: Multilocus linkage analysis of affected sib pairs.
abstract: OBJECTIVE
  The conventional affected sib pair methods evaluate the linkage information at a locus by considering only marginal information. We describe a multilocus linkage method that uses both the marginal information and information derived from the possible interactions among several disease loci, thereby increasing the significance of loci with modest effects.
  
  
  METHODS
  Our method is based on a statistic that quantifies the linkage information contained in a set of markers. By a marker selection-reduction process, we screen a set of polymorphisms and select a few that seem linked to disease.
  
  
  RESULTS
  We test our approach on genome scan data for inflammatory bowel disease (InfBD) and on simulated data. On real data we detect 6 of the 8 known InfBD loci; on simulated data we obtain improvements in power of up to 40% compared to a conventional single-locus method.
  
  
  CONCLUSIONS
  Our extensive simulations and the results on real data show that our method is in general more powerful than single-locus methods in detecting disease loci responsible for complex traits. A further advantage of our approach is that it can be extended to make use of both the linkage and the linkage disequilibrium between disease loci and nearby markers.
authors.affiliation: Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, USA. ionita@cs.nyu.edu
authors.forename: Iuliana
authors.initials: I
authors.lastname: Ionita
authors.forename: Shaw-Hwa
authors.initials: SH
authors.lastname: Lo
mesh_terms: D008040:Genetic Linkage / Q000235:genetics*; D005819:Genetic Markers; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D015212:Inflammatory Bowel Diseases / Q000235:genetics*; D008957:Models, Genetic; D040641:Quantitative Trait Loci / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods
chemical_list: D005819:Genetic Markers