Improving Genotype Imputation in High-Dimensional Pharmacogenomics Using Multiple Imputation: Evaluation with Machine Learning Approaches.

Abstract excerpt

Multiple imputation is well-established for handling missing data, yet its use in high-dimensional genetic datasets remains limited. Using pharmacokinetic tuberculosis simulations and SNP data (1000 Genomes Project), we compared machine learning (ML) and traditional approaches (e.g., mean imputation and complete-case analysis) for imputation and covariate selection. We developed a multiple imputation framework...

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