Spatio-temporal and hierarchical modelling of high-throughput phenotypic data

• Fred A. Van Eeuwijk ; Emilie J. Millet ^[1] ; Martin P. Boer ^[1] ; María Xosé Rodríguez Álvarez ; Diana Marcela Pérez Pérez
  1. [1] Wageningen University & Research
• Localización: Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain / Itziar Irigoyen Garbizu (ed. lit.), Dae-Jin Lee (ed. lit.), Joaquín Martínez Minaya (ed. lit.), María Xosé Rodríguez Álvarez (ed. lit.), 2020, ISBN 978-84-1319-267-3, págs. 394-397
• Idioma: inglés
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• Resumen

  • We present a full spatio-temporal and hierarchical data modelling approach for the analysis of high-throughput phenotypic data. We use the recently proposed SpATS approach as the base model, and extend it to the spatiotemporal case, also considering a three-level hierarchical data model (plants nested in genotypes, nested in populations). We illustrate our approach using data from a high-throughput phenotypic platform.