Preparation and Curation of Multiyear, Multilocation, Multitrait Datasets

Published Date
June 01, 2022
Type
Book Chapter
Preparation and Curation of Multiyear, Multilocation, Multitrait Datasets
Authors:
Amina Abed
Zakaria Kehel

Genome-wide association studies (GWAS) are a powerful approach to dissect genotype-phenotype associations and identify causative regions. However, this power is highly influenced by the accuracy of the phenotypic data. To obtain accurate phenotypic values, the phenotyping should be achieved through multienvironment trials (METs). In order to avoid any technical errors, the required time needs to be spent on exploring, understanding, curating and adjusting the phenotypic data in each trial before combining them using an appropriate linear mixed model (LMM). The LMM is chosen to minimize as much as possible any effect that can lead to misestimation of the phenotypic values. The purpose of this chapter is to explain a series of important steps to explore and analyze data from METs used to characterize an association panel. Two datasets are used to illustrate two different scenarios.

Citation:
Amina Abed, Zakaria Kehel. (1/6/2022). Preparation and Curation of Multiyear, Multilocation, Multitrait Datasets, in "Genome-Wide Association Studies. Methods in Molecular Biology, vol 2481". United States of America: Humana New York.
Keywords:
multienvironment trials
descriptive statistics
adjusted phenotype per trial
analysis of residuals
combined phenotype across trials
design diagnostics
genotype × environment
genotype–phenotype association
linear mixed model
outliers
aw phenotype per trial
experimental design