Abstract:
:Dense sets of hundreds of thousands of markers have been developed for genome-wide association studies. These marker sets are also beneficial for linkage analysis of large, deep pedigrees containing distantly related cases. It is impossible to analyse jointly all genotypes in large pedigrees using the Lander-Green Algorithm, however, as marker density increases it becomes less crucial to analyse all individuals' genotypes simultaneously. In this report, an approximate multipoint non-parametric technique is described, where large pedigrees are split into many small pedigrees, each containing just two cases. This technique is demonstrated, using phased data from the International Hapmap Project to simulate sets of 10,000, 50,000 and 250,000 markers, showing that it becomes increasingly accurate as more markers are genotyped. This method allows routine linkage analysis of large families with dense marker sets and represents a more easily applied alternative to Monte Carlo Markov Chain methods.
journal_name
Hum Genetjournal_title
Human geneticsauthors
Thomson R,Quinn S,McKay J,Silver J,Bahlo M,FitzGerald L,Foote S,Dickinson J,Stankovich Jdoi
10.1007/s00439-007-0323-5subject
Has Abstractpub_date
2007-05-01 00:00:00pages
459-68issue
3-4eissn
0340-6717issn
1432-1203journal_volume
121pub_type
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