Effect of genotype and pedigree error on detection of recombination events, sire imputation and haplotype inference using the HSPhase algorithm

Title
Effect of genotype and pedigree error on detection of recombination events, sire imputation and haplotype inference using the HSPhase algorithm
Publication Date
2013
Author(s)
Ferdosi, Mohammad H
( author )
OrcID: https://orcid.org/0000-0001-5385-4913
Email: mferdos3@une.edu.au
UNE Id une-id:mferdos3
Kinghorn, Brian P
( author )
OrcID: https://orcid.org/0000-0002-3778-7615
Email: bkinghor@une.edu.au
UNE Id une-id:bkinghor
Van Der Werf, Julius H J
( author )
OrcID: https://orcid.org/0000-0003-2512-1696
Email: jvanderw@une.edu.au
UNE Id une-id:jvanderw
Gondro, Cedric
( author )
OrcID: https://orcid.org/0000-0003-0666-656X
Email: cgondro2@une.edu.au
UNE Id une-id:cgondro2
Editor
Editor(s): Nicolas Lopez Villalobos
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
Association for the Advancement of Animal Breeding and Genetics (AAABG)
Place of publication
Armidale, Australia
UNE publication id
une:14353
Abstract
HSPhase is a fast and accurate algorithm for detection of recombination events, sire imputation and haplotype inference of half-sib families. It can be used on data for half-sib families with as few as 4 individuals in a family. The robustness of this algorithm in relation to genotype and pedigree errors was evaluated. If there were more than 20 half-sibs in a family, the performance of the algorithm with 5% pedigree or genotyping errors was still reliable with the accuracy of phasing and imputation above 0.87. These error rates are above those commonly observed in industry data which indicates the algorithm is sufficiently robust for deployment in real world settings. An R package implementing the method is freely available and includes a function to generate diagnostic plots which are very useful to rapidly identify problems in the dataset.
Link
Citation
Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.20, p. 546-549
ISSN
1328-3227
ISBN
9780473260569
Start page
546
End page
549

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