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Application of imputation methods to genomic selection in Chinese Holstein cattle

摘要Missing genotypes are a common feature of high density SNP datasets obtained using SNP chip technology and this is likely to decrease the accuracy of genomic selection.This problem can be circumvented by imputing the missing genotypes with estimated genotypes.When implementing imputation,the criteria used for SNP data quality control and whether to perform imputation before or after data quality control need to consider.In this paper,we compared six strategies of imputation and quality control using different imputation methods,different quality control criteria and by changing the order of imputation and quality control,against a real dataset of milk production traits in Chinese Holstein cattle.The results demonstrated that,no matter what imputation method and quality control criteria were used,strategies with imputation before quality control performed better than strategies with imputation after quality control in terms of accuracy of genomic selection.The different imputation methods and quality control criteria did not significantly influence the accuracy of genomic selection.We concluded that performing imputation before quality control could increase the accuracy of genomic selection,especially when the rate of missing genotypes is high and the reference population is small.

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作者单位 Key Laboratory of Animal Genetics Breeding and Reproduction,Ministry of Agriculture,College of Animal Science and Technology,China Agricultural University,Beijing,China [1]
分类号 S823
栏目名称 ANIMAL GENETICS
DOI 10.1186/2049-1891-3-6
发布时间 2012-10-29
基金项目
The National Natural Science Foundation of China The State High-Tech Development Plan of China The Recommend International Advanced Agricultural Science and Technology Plan of China
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