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

  1. Fred A. Van Eeuwijk
  2. Emilie J. Millet 1
  3. Martin P. Boer 1
  4. María Xosé Rodríguez Álvarez
  5. Diana Marcela Pérez Pérez
  1. 1 Wageningen University & Research
Libro:
Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain
  1. Itziar Irigoien (ed. lit.)
  2. Dae-Jin Lee (ed. lit.)
  3. Joaquín Martínez-Minaya (ed. lit.)
  4. María Xosé Rodríguez- Álvarez (ed. lit.)

Editorial: Servicio Editorial = Argitalpen Zerbitzua ; Universidad del País Vasco = Euskal Herriko Unibertsitatea

ISBN: 978-84-1319-267-3

Ano de publicación: 2020

Páxinas: 394-397

Congreso: International Workshop on Statistical Modelling (35. 2020. Bilbao)

Tipo: Achega congreso

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Resumo

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.

Fonte de datos: Dialnet