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Utilizing large pedigrees in linkage analysis is a computationally challenging task. The pedigree size limits applicability of the Lander-Green-Kruglyak algorithm for linkage analysis. A common solution is to split large pedigrees into smaller computable subunits. We present a pedigree-splitting method that, within a user supplied bit-size limit, identifies subpedigrees having the maximal number of subjects of interest (eg patients) who share a common ancestor. We compare our method with the maximum clique partitioning method using a large and complex human pedigree consisting of 50 patients with Alzheimer's disease ascertained from genetically isolated Dutch population. We show that under a bit-size limit our method can assign more patients to subpedigrees than the clique partitioning method, particularly when splitting deep pedigrees where the subjects of interest are scattered in recent generations and are relatively distantly related via multiple genealogic connections. Our pedigree-splitting algorithm and associated software can facilitate genome-wide linkage scans searching for rare mutations in large pedigrees coming from genetically isolated populations. The software package PedCut implementing our approach is available at http://mga.bionet.nsc.ru/soft/index.html.

Original publication

DOI

10.1038/ejhg.2008.24

Type

Journal article

Journal

European journal of human genetics : EJHG

Publication Date

07/2008

Volume

16

Pages

854 - 860

Addresses

Department of Epidemiology & Biostatistics, Erasmus MC, Rotterdam, The Netherlands.

Keywords

Humans, Alzheimer Disease, Pedigree, Lod Score, Algorithms, Genealogy and Heraldry, Software Design, Female, Male, Genetic Linkage