A new method for exploring gene–gene and gene–environment interactions in GWAS with tree ensemble methods and SHAP values

A new method for exploring gene–gene and gene–environment interactions in GWAS with tree ensemble methods and SHAP values

Background: The identification of gene–gene and gene–environment interactions in genome-wide association studies is challenging due to the unknown nature of the interactions and the overwhelmingly large number of possible combinations. Parametric regression models are suitable to look for prespecifi...

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Bibliographic Details
Main Authors: Cahill, M.E (Author), DeWan, A.T (Author), Johnsen, P.V (Author), Langaas, M. (Author), Riemer-Sørensen, S. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Association reactions
Biobanks
Clustering algorithms
Cross validation
Forestry
Gene-Environment Interaction
Gene–gene and gene–environment interactions
Genes
Genome-wide association studies
genome-wide association study
Genome-Wide Association Study
genotype environment interaction
GWAS
High dimensional data
Model explainability
Non-parametric model
Nutrition
Parametric regression
Polymorphism, Single Nucleotide
Regression analysis
SHAP
single nucleotide polymorphism
tree
Tree ensemble models
Tree ensembles
Trees
Trees (mathematics)
XGBoost
Online Access:View Fulltext in Publisher

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