title: SNP-based linkage analysis in extended pedigrees: comparison between two alternative approaches.
abstract: BACKGROUND
  Linkage analysis on extended pedigrees is often challenged by the high computational demand of exact identity-by-descent (IBD) matrix reconstruction. When such an analysis becomes not feasible, two alternative solutions are contrasted: a full pedigree analysis based on approximate IBD estimation versus a pedigree splitting followed by exact IBD estimation. A multiple splitting (MS) approach, which combines linkage results across different splitting configurations, has been proposed to increase the power of single-split solutions.
  
  
  METHODS
  To assess whether MS can achieve a comparable power to a full pedigree analysis, we compared the power of linkage on a very large pedigree in both simulated and real-case scenarios, using variance components linkage analysis of a dense SNP array.
  
  
  RESULTS
  Our results confirm that the power to detect linkage is affected by the pedigree size. The MS approach showed higher power than the single-split analysis, but it was substantially less powerful than the full pedigree approach in both scenarios, at any level of significance and variance explained by a quantitative trait locus.
  
  
  CONCLUSIONS
  The MS approach should always be preferred to analyses based on a single split but, when adequate computational resources are available, a full pedigree analysis is better than the MS analysis. Rather than focusing on how to best split a pedigree, it might be more valuable to identify computational solutions that can make the IBD estimation of dense-marker maps practically feasible, thus allowing a full pedigree analysis.
authors: INSERM U1078, Etablissement Français du Sang, Brest, France.
authors: Aude
authors: A
authors: Saint-Pierre
authors: Yuri
authors: Y
authors: D'Elia
authors: Marina
authors: M
authors: Ciullo
authors: Peter P
authors: PP
authors: Pramstaller
authors: Cristian
authors: C
authors: Pattaro
mesh_terms: D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D005260:Female; D008040:Genetic Linkage; D005828:Genetics, Population / Q000379:methods; D005838:Genotype; D006801:Humans; D008126:Lod Score; D008297:Male; D008957:Models, Genetic; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci / Q000235:genetics