Imputation Error Analysis
Imputation Error Analysis is a methodological framework within genotype imputation studies that systematically evaluates the accuracy and sources of discrepancies between imputed and true genotypes to assess the reliability of imputation results.
118
Publications
17.2K
Citations
619
Authors
283
Institutions
Publications per year
2017–2026
37
Parents
118
MissForest—non-parametric missing value imputation for mixed-type data
Daniel J. Stekhoven, Peter Bühlmann · Bioinformatics · 2011 · 6.1K citations · Full text
A new multipoint method for genome-wide association studies by imputation of genotypes
Jonathan Marchini, Bryan Howie, Simon Myers et al. · Nature Genetics · 2007 · 2.7K citations
Comparison of imputation methods for missing laboratory data in medicine
Akbar K. Waljee, Ashin Mukherjee, Amit G. Singal et al. · BMJ Open · 2013 · 500 citations · Full text
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283
National Institutes of Health
Bethesda, United States
5 h-index
18 publications
2.2K citations
University of Michigan
Ann Arbor, United States
5 h-index
18 publications
5.2K citations
Massachusetts General Hospital
Boston, United States
5 h-index
14 publications
828 citations

Broad Institute
Cambridge, United States
5 h-index
15 publications
518 citations

Johns Hopkins University
Baltimore, United States
4 h-index
15 publications
807 citations

Aarhus University
Aarhus, Denmark
4 h-index
11 publications
461 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
19 publications
1.9K citations
University of Wisconsin–Madison
Madison, United States
4 h-index
6 publications
104 citations
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JDS · 9 publications · 401 citations
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5 publications · 300 citations
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4 publications · 68 citations
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4 publications · 6.4K citations
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GSE · 3 publications · 216 citations
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