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Efficient haplotype inference algorithms in one whole genome scan for pedigree data with non-genotyped founders

Efficient haplotype inference algorithms in one whole genome scan for pedigree data with... An efficient rule-based algorithm is presented for haplotype inference from general pedigree genotype data, with the assumption of no recombination. This algorithm generalizes previous algorithms to handle the cases where some pedigree founders are not genotyped, provided that for each nuclear family at least one parent is genotyped and each non-genotyped founder appears in exactly one nuclear family. The importance of this generalization lies in that such cases frequently happen in real data, because some founders may have passed away and their genotype data can no longer be collected. The algorithm runs in O(m 3 n 3) time, where m is the number of single nucleotide polymorphism (SNP) loci under consideration and n is the number of genotyped members in the pedigree. This zero-recombination haplotyping algorithm is extended to a maximum parsimoniously haplotyping algorithm in one whole genome scan to minimize the total number of breakpoint sites, or equivalently, the number of maximal zero-recombination chromosomal regions. We show that such a whole genome scan haplotyping algorithm can be implemented in O(m 3 n 3) time in a novel incremental fashion, here m denotes the total number of SNP loci along the chromosome. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Mathematicae Applicatae Sinica Springer Journals

Efficient haplotype inference algorithms in one whole genome scan for pedigree data with non-genotyped founders

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References (26)

Publisher
Springer Journals
Copyright
Copyright © 2009 by Institute of Applied Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences and Springer-Verlag GmbH
Subject
Mathematics; Applications of Mathematics; Math Applications in Computer Science; Theoretical, Mathematical and Computational Physics
ISSN
0168-9673
eISSN
1618-3932
DOI
10.1007/s10255-008-8821-3
Publisher site
See Article on Publisher Site

Abstract

An efficient rule-based algorithm is presented for haplotype inference from general pedigree genotype data, with the assumption of no recombination. This algorithm generalizes previous algorithms to handle the cases where some pedigree founders are not genotyped, provided that for each nuclear family at least one parent is genotyped and each non-genotyped founder appears in exactly one nuclear family. The importance of this generalization lies in that such cases frequently happen in real data, because some founders may have passed away and their genotype data can no longer be collected. The algorithm runs in O(m 3 n 3) time, where m is the number of single nucleotide polymorphism (SNP) loci under consideration and n is the number of genotyped members in the pedigree. This zero-recombination haplotyping algorithm is extended to a maximum parsimoniously haplotyping algorithm in one whole genome scan to minimize the total number of breakpoint sites, or equivalently, the number of maximal zero-recombination chromosomal regions. We show that such a whole genome scan haplotyping algorithm can be implemented in O(m 3 n 3) time in a novel incremental fashion, here m denotes the total number of SNP loci along the chromosome.

Journal

Acta Mathematicae Applicatae Sinica – Springer Journals

Published: May 29, 2009

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