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Original Paper

Free Access

Haplotyping Methods for Pedigrees

Gao G.a · Allison D.B.a · Hoeschele I.b

Author affiliations

aDepartment of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Ala., bVirginia Bioinformatics Institute and Department of Statistics, Virginia Tech, Blacksburg, Va., USA

Corresponding Author

Ina Hoeschele

Virginia Bioinformatics Institute, Virginia Tech

Blacksburg, VA 24061-0477 (USA)

Tel. +1 540 231 3135, Fax +1 540 231 2606

E-Mail inah@vbi.vt.edu

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Hum Hered 2009;67:248–266

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Haplotypes provide valuable information in the study of diseases, complex traits, population histories, and evolutionary genetics. With the dramatic increase in the number of available single nucleotide polymorphism (SNP) markers, haplotype inference (haplotyping) using observed genotype data has become an important component of genetic studies in general and of statistical gene mapping in particular. Existing haplotyping methods include (1) population-based methods, (2) methods for pooled DNA samples, and (3) methods for family and pedigree data. The methods and computer programs for population data and pooled DNA samples were reviewed recently in the literature. As several authors noted, family and pedigree datasets are abundant and have unique advantages. In the past twenty years, many haplotyping methods for family and pedigree data have been developed. Therefore, in this contribution we review haplotyping methods and the corresponding computer programs suitable for family and pedigree data and discuss their applications and limitations. We explore the connections among these methods, and describe the challenges that remain to be addressed.

© 2009 S. Karger AG, Basel


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Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: January 31, 2008
Accepted: August 08, 2008
Published online: January 27, 2009
Issue release date: March 2009

Number of Print Pages: 19
Number of Figures: 1
Number of Tables: 2

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

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