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. |
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| 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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