Empirical versus estimated accuracy of imputation: optimising filtering thresholds for sequence imputation
This study provides an empirically derived approach to apply customised software-specific Rsq<sub>soft</sub> thresholds for downstream analyses of imputed variants, such as needed for a meta-GWAS. The very poor empirical imputation accuracy for variants on the PAR when starting from low density genotypes demonstrates that this region should be imputed starting from a higher density of real genotypes.
Authors
- Coralie M. Reich
- Sunduimijid Bolormaa (ORCID: https://orcid.org/0000-0003-2700-5437)
- Amanda J. Chamberlain (ORCID: https://orcid.org/0000-0002-9395-1299)
- Iona M. MacLeod
- Hans D. Daetwyler (ORCID: https://orcid.org/0000-0002-3018-3640)
- Christy J. Vander Jagt (ORCID: https://orcid.org/0000-0002-1107-7463)
- Tuan V. Nguyen (ORCID: https://orcid.org/0000-0003-0415-0623)
Institutions
- La Trobe University (AU)
- Agriculture Victoria (AU)
- AgriBio (AU)
Publication Details
- Journal
- Genetics Selection Evolution
- Published
- 2024-11-15
- DOI
- https://doi.org/10.1186/s12711-024-00942-2
- Citations
- 12
- Primary Topic
- Genetic and phenotypic traits in livestock
- Type
- article
- Field-Weighted Citation Impact
- 6.60
Funders
- Gardiner Foundation
- Agriculture Victoria