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Title: On detection of population stratification in genotype samples using spacial clustering and non-linear optimization
Contributor(s): Boerner, Vinzent  (author)
Publication Date: 2018
Open Access: Yes
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Abstract: Accounting for population stratification in genotype samples is important to avoid false inference from genome wide association studies. It is usually quantified using model-based ancestry estimation (e.g. ADMIXTURE; Alexander et al. (2009)), which has disadvantages with regard to model assumptions and processing time. This article describes a two step procedure for estimating population stratification. In the first step a spacial cluster algorithm is used to detect clusters of genetically homogeneous animals. In a subsequent step genotypes are described as linear functions of within-cluster allele frequencies. The approach was tested on a cattle data set which consisted of 11,639 real genotypes from 11 breeds and 5,000 artificially generated cross-bred genotypes (F1 to F5). It outperformed results obtained from ADMIXTURE in terms of speed and accuracy.
Publication Type: Conference Publication
Conference Details: WCGALP 2018: 11th World Congress on Genetics Applied to Livestock Production, Auckland, New Zealand, 11th - 16th February, 2018
Source of Publication: Proceedings of the World Congress on Genetics Applied to Livestock Production, p. 24-27
Publisher: Massey University
Place of Publication: Palmerston North, New Zealand
Fields of Research (FoR) 2008: 060408 Genomics
060412 Quantitative Genetics (incl. Disease and Trait Mapping Genetics)
Fields of Research (FoR) 2020: 310509 Genomics
310506 Gene mapping
Socio-Economic Objective (SEO) 2008: 830301 Beef Cattle
830302 Dairy Cattle
830310 Sheep - Meat
Socio-Economic Objective (SEO) 2020: 100401 Beef cattle
100402 Dairy cattle
100412 Sheep for meat
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
Conference Publication

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