Evaluation of imputation strategies for multi-centre studies: Application to a large clinical pathology dataset.

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Title: Evaluation of imputation strategies for multi-centre studies: Application to a large clinical pathology dataset.
Authors: Grigoroff L; Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Australia., Masuda R; Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Australia., Lindon J; Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, London, United Kingdom., Kadyrov J; Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Australia., Nicholson JK; Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Australia.; Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, London, United Kingdom., Holmes E; Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Australia.; Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom., Wist J; Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Australia.; Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom.; Chemistry Department, Universidad del Valle, Cali, Colombia.
Source: PloS one [PLoS One] 2025 Nov 20; Vol. 20 (11), pp. e0335852. Date of Electronic Publication: 2025 Nov 20 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1932-6203
DOI:10.1371/journal.pone.0335852