GWAPP

GWAPP performs genome-wide association studies (GWAS) in Arabidopsis thaliana to analyze natural phenotypic variation across 1386 publicly available ecotypes using linear mixed models.

Key Features:

• Linear mixed model: Efficient implementation of a linear mixed model for association testing.
• Ecotype dataset: Analysis of traits measured across 1386 publicly available Arabidopsis thaliana ecotypes.
• Cofactor modelling: Ability to incorporate candidate polymorphisms into the model as cofactors.
• Visualization outputs: Generation of Manhattan plots and linkage disequilibrium plots for locus identification and LD inspection.
• Exploratory analysis: Functionalities supporting exploratory analysis of phenotype–genotype relationships.
• Performance: Rapid association mapping, with analyses often completed within minutes.

Scientific Applications:

• Genetic locus identification: Mapping loci associated with phenotypic traits in Arabidopsis thaliana.
• Natural variation studies: Systematic investigation of natural genetic variation across ecotypes.
• Candidate polymorphism evaluation: Testing effects of candidate polymorphisms by including them as cofactors in association models.
• Linkage disequilibrium analysis: Characterization of local LD patterns to aid interpretation of association signals.

Methodology:

Association mapping applies an efficient linear mixed model to trait data from 1386 ecotypes; candidate polymorphisms can be added as cofactors and results are summarized with Manhattan plots and linkage disequilibrium plots.