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Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?

View ORCID ProfileVinícius Silva Junqueira, Daniela Lourenco, Yutaka Masuda, Fernando Flores Cardoso, Paulo Sávio Lopes, Fabyano Fonseca e Silva, Ignacy Misztal
doi: https://doi.org/10.1101/2022.01.19.476983
Vinícius Silva Junqueira
*Departamento de Zootecnia, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
2Breeding Research Department, Bayer Crop Science, Uberlândia, Minas Gerais, Brazil
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  • ORCID record for Vinícius Silva Junqueira
  • For correspondence: viniciussilva.junqueira@bayer.com
Daniela Lourenco
†Department of Dairy and Animal Science, University of Georgia, Athens, Georgia, United States
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Yutaka Masuda
†Department of Dairy and Animal Science, University of Georgia, Athens, Georgia, United States
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Fernando Flores Cardoso
‡Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Pecuária Sul, Bagé, Rio Grande do Sul, Brasil
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Paulo Sávio Lopes
*Departamento de Zootecnia, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
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Fabyano Fonseca e Silva
*Departamento de Zootecnia, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
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Ignacy Misztal
†Department of Dairy and Animal Science, University of Georgia, Athens, Georgia, United States
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Posted January 21, 2022.
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Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?
Vinícius Silva Junqueira, Daniela Lourenco, Yutaka Masuda, Fernando Flores Cardoso, Paulo Sávio Lopes, Fabyano Fonseca e Silva, Ignacy Misztal
bioRxiv 2022.01.19.476983; doi: https://doi.org/10.1101/2022.01.19.476983
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Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?
Vinícius Silva Junqueira, Daniela Lourenco, Yutaka Masuda, Fernando Flores Cardoso, Paulo Sávio Lopes, Fabyano Fonseca e Silva, Ignacy Misztal
bioRxiv 2022.01.19.476983; doi: https://doi.org/10.1101/2022.01.19.476983

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