Evidence map›Paper›PMID 34957440›Full record

ArticleJournal of animal science and technology2021

Accuracy of genotype imputation based on reference population size and marker density in Hanwoo cattle.

DooHo Lee, Yeongkuk Kim, Yoonji Chung, Dongjae Lee, Dongwon Seo, Tae Jeong Choi, Dajeong Lim, Duhak Yoon, Seung Hwan Lee

Abstract read
In one paragraph

Article in Journal of animal science and technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

DooHo LeeDivision of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-2174-7897
Yeongkuk KimDivision of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-6530-2304
Yoonji ChungDivision of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-6906-6468
Dongjae LeeDivision of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-8140-014X
Dongwon SeoDivision of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0003-0548-7068
Tae Jeong ChoiNational Institute of Animal Science, Cheonan 31000, Korea.ORCID https://orcid.org/0000-0002-8299-9342
Dajeong LimAnimal Genomics and Bioinformatics Division, National Institute of Animal Science, Wanju 55365, Korea.ORCID https://orcid.org/0000-0003-3966-9150
Duhak YoonDepartment of Animal Science & Biotechnology, Kyungpook National University, Sangju 37224, Korea.ORCID https://orcid.org/0000-0002-3983-9757
Seung Hwan LeeDivision of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0003-1508-4887

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, the cattle genome sequence has been completed, followed by developing a commercial single nucleotide polymorphism (SNP) chip panel in the animal genome industry. In order to increase statistical power for detecting quantitative trait locus (QTL), a number of animals should be genotyped. However, a high-density chip for many animals would be increasing the genotyping cost. Therefore, statistical inference of genotype imputation (low-density chip to high-density) will be useful in the animal industry. The purpose of this study is to investigate the effect of the reference population size and marker density on the imputation accuracy and to suggest the appropriate number of reference population sets for the imputation in Hanwoo cattle. A total of 3,821 Hanwoo cattle were divided into reference and validation populations. The reference sets consisted of 50k (38,916) marker data and different population sizes (500, 1,000, 1,500, 2,000, and 3,600). The validation sets consisted of four validation sets (Total 889) and the different marker density (5k [5,000], 10k [10,000], and 15k [15,000]). The accuracy of imputation was calculated by direct comparison of the true genotype and the imputed genotype. In conclusion, when the lowest marker density (5k) was used in the validation set, according to the reference population size, the imputation accuracy was 0.793 to 0.929. On the other hand, when the highest marker density (15k), according to the reference population size, the imputation accuracy was 0.904 to 0.967. Moreover, the reference population size should be more than 1,000 to obtain at least 88% imputation accuracy in Hanwoo cattle.

Indexed as

Hanwoo cattleImputationMarker densityReference population sizeSingle nucleotide polymorphism (SNP)

Identifiers

PMID34957440
PMCPMC8672260

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.