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IPED: Inheritance Path-based Pedigree Reconstruction Algorithm Using Genotype Data

Cited 7 time in Web of Science Cited 8 time in Scopus
Authors

He, Dan; Wang, Zhanyong; Han, Buhm; Parida, Laxmi; Eskin, Eleazar

Issue Date
2013-10
Publisher
Mary Ann Liebert Inc.
Citation
Journal of Computational Biology, Vol.20 No.10, pp.780-791
Abstract
The problem of inference of family trees, or pedigree reconstruction, for a group of individuals is a fundamental problem in genetics. Various methods have been proposed to automate the process of pedigree reconstruction given the genotypes or haplotypes of a set of individuals. Current methods, unfortunately, are very time-consuming and inaccurate for complicated pedigrees, such as pedigrees with inbreeding. In this work, we propose an efficient algorithm that is able to reconstruct large pedigrees with reasonable accuracy. Our algorithm reconstructs the pedigrees generation by generation, backward in time from the extant generation. We predict the relationships between individuals in the same generation using an inheritance path-based approach implemented with an efficient dynamic programming algorithm. Experiments show that our algorithm runs in linear time with respect to the number of reconstructed generations, and therefore, it can reconstruct pedigrees that have a large number of generations. Indeed it is the first practical method for reconstruction of large pedigrees from genotype data.
ISSN
1066-5277
URI
https://hdl.handle.net/10371/191618
DOI
https://doi.org/10.1089/cmb.2013.0080
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  • College of Medicine
  • Department of Medicine
Research Area Bioinformatics, Computational Biology, Genomics, Human Leukocyte Antigen, Statistical Genetics

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