AgResearch
Browse
- No file added yet -

Assessing imputation accuracy using a 15K low density panel in a multi-breed New Zealand sheep population

Download (454.24 kB)
journal contribution
posted on 2023-05-03, 19:46 authored by R. V. Ventura, Michael Lee, Stephen Miller, Shannon ClarkeShannon Clarke, John McEwanJohn McEwan
Imputation has enabled genomic selection in commercial livestock, taking advantage of a more cost effective Low Density (LD) panel, increasing the number of genotyped animals and hence adoption. A 5K LD panel has been employed commercially in New Zealand. This study investigated the accuracy of imputation using a new 15K panel being developed by the International Sheep Genomics Consortium in four scenarios across two multi-breed New Zealand sheep populations. The prototype panel resulted in higher values of imputation accuracy compared with the current LD panel (5K), which will benefit the implementation of genomic selection for the sheep industry in New Zealand.

History

Rights statement

© Association for the Advancement of Animal Breeding and Genetics, 2015. All rights reserved except under the conditions described in the Australian Copyright Act 1968 and subsequent amendments, no part of this publication may be reproduced, stored in a retrieval system or be transmitted in any form, or by any means, electronic, mechanical, photocopying, recording, duplicating, or otherwise, without prior permission of the copyright owner.

Language

  • English

Does this contain Māori information or data?

  • No

Publisher

Association for the Advancement of Animal Breeding and Genetics

Journal title

Proceedings of the Association for the Advancement of Animal Breeding and Genetics

ISSN

1328-3227

ISBN

9780646945545

Citation

Ventura, R. V., Lee, M., Miller, S. P., Clarke, S. M., & McEwan, J. C. (2015). Assessing imputation accuracy using a 15K low density panel in a multi-breed New Zealand sheep population. Proceedings of the Association for the Advancement of Animal Breeding and Genetics, 21, 302-305.

Contract number

A19127

Job code

51160

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC