High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype

High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype

This work addresses the problem of supervised classification for highly correlated high-dimensional data describing non-independent observations to identify SNPs related to a phenotype. We use a general penalized linear mixed model with a single random effect that performs simultaneous SNP selection...

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Bibliographic Details
Main Authors: Aboubacry Gaye, Abdou Ka Diongue, Lionel Nanguep Komen, Amadou Diallo, Seydou Nourou Sylla, Maryam Diarra, Cheikh Talla, Cheikh Loucoubar
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2023-12-01
Series:Infectious Disease Modelling
Subjects:
Non independence of observations
Correlated variables
High-dimensional supervised classification
SNP
Phenotype
Online Access:http://www.sciencedirect.com/science/article/pii/S2468042723000842

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http://www.sciencedirect.com/science/article/pii/S2468042723000842

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