Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/28984
Title: How much extra information is gained using imputed genotype data?
Contributor(s): Clark, S  (author)orcid ; Duijvesteijn, N  (author); van der Werf, J H J  (author)orcid 
Publication Date: 2018
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/28984
Open Access Link: http://www.wcgalp.org/proceedings/2018/how-much-extra-information-gained-using-imputed-genotype-data
Abstract: Genotype imputation has been discussed widely as a tool to increase the statistical power associated with genome wide association studies (GWAS) and genomic prediction. Previous studies have examined the performance of imputation by evaluating how well a validation set has been predicted. The aim of this study was to examine the amount of extra information added by utilising genotype imputation. The number of new haplotype combinations, between adjacent loci, were estimated for multiple genotype densities from an Australian Sheep dataset. In our example, using genotypes from OAR6, imputation increased the number of haplotypes for 81% of the regions when imputing from 12k to 50k. Large distances between adjacent low density markers resulted in higher numbers of new haplotypes. This also corresponded to a greater proportion of low frequency haplotypes. When imputing from HD to WGS no information was added for 50% of the regions and there was a greater proportion of haplotypes with only 1 observation. Estimating the number of new haplotypes from imputation provides an understanding about the value of imputation and can be utilised to help design of reference genotype datasets.
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, v.11, p. 1-5
Publisher: Massey University
Place of Publication: Palmerston North, New Zealand
Fields of Research (FoR) 2008: 070201 Animal Breeding
060412 Quantitative Genetics (incl. Disease and Trait Mapping Genetics)
060408 Genomics
Fields of Research (FoR) 2020: 300305 Animal reproduction and breeding
310506 Gene mapping
310509 Genomics
Socio-Economic Objective (SEO) 2008: 830399 Livestock Raising not elsewhere classified
Socio-Economic Objective (SEO) 2020: 100407 Insects
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Publisher/associated links: http://www.wcgalp.org/proceedings/2018
Appears in Collections:Conference Publication
School of Environmental and Rural Science

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