SNPMace - A meta-analysis to estimate SNP effects across countries

Authors

  • Dr Jighly
  • Dr Benhajali Interbull Center
  • Dr Liu
  • Dr Goddard

Abstract

The accuracy of genomic prediction could be improved by combining datasets across countries, but it is not always possible to combine the individual animal data. This project has tested a meta-analysis, called SNPMace, that mimics the combined analysis but requires only summary statistics, such as estimated SNP effects, from participating countries. The method uses the genetic correlation between a trait measured in different countries to produce country specific estimated SNP effects. We tested this method on data from 6 countries on the protein yield of Brown Swiss cattle and on the milk, fat and protein yields of Australian Holstein and Jersey cattle. In both cases the meta-analysis generated estimated breeding values that had a correlation with those obtained by analyzing the raw data in the range 0.99 to 1. The method is implemented in software called MetaGS which also converts data on a subset of SNPs to a common SNP set for analysis.

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Published

2020-01-28