Annaïg De Walsche

ORCID: 0000-0003-0603-1716
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About
Contact & Profiles
Research Areas
  • Genetic Mapping and Diversity in Plants and Animals
  • Genetic and phenotypic traits in livestock
  • Genetics and Plant Breeding
  • Genetic Associations and Epidemiology
  • Gene expression and cancer classification
  • Advanced Database Systems and Queries
  • Data Management and Algorithms
  • Bioinformatics and Genomic Networks
  • Statistical Methods in Clinical Trials

AgroParisTech
2023-2025

Université Paris-Saclay
2023-2025

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
2023-2025

Centre National de la Recherche Scientifique
2023-2025

Génétique Quantitative et Évolution Le Moulon
2023-2025

Elucidating the genetic components of plant genotype-by-environment interactions is key importance in context increasing climatic instability, diversification agricultural practices and pest pressure due to phytosanitary treatment limitations. The genotypic response environmental stresses can be investigated through multi-environment trials (METs). However, genome-wide association studies (GWAS) MET data are significantly more complex than that single environments. In this context, we...

10.1371/journal.pgen.1011553 article EN cc-by PLoS Genetics 2025-01-10

Abstract Composite Hypothesis Testing (CHT) based on summary statistics has become a popular strategy to assess the effect of same marker (or gene) jointly across multiple traits or at different omics levels. Although significant efforts have been made develop efficient CHT procedures, most approaches face scalability constraints in terms number traits/omics and markers handle, fail account for potential correlations efficiently. Methods relying mixture models partially circumvent these...

10.1101/2024.03.17.585412 preprint EN cc-by-nc bioRxiv (Cold Spring Harbor Laboratory) 2024-03-17

Abstract Dissecting the genetic components of Genotype-by-Environment interactions is key importance in context increasing instability and plant competition due to climate change phytosanitary treatment limitations. It widely addressed plants using Multi-Environment Trials (MET), which statistical modelling for genome-wide association studies (GWAS) promising but significantly more complex than single-environment studies. In this context, we introduce metaGE, a flexible computationally...

10.1101/2023.03.01.530237 preprint EN cc-by-nd bioRxiv (Cold Spring Harbor Laboratory) 2023-03-02
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