ArticleGenetic epidemiology2019
On the differences between mega- and meta-imputation and analysis exemplified on the genetics of age-related macular degeneration.
Article in Genetic epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease.BMC medical genomics · 2020Pooled it
- Removing array-specific batch effects in GWAS mega-analyses by applying a two-step imputation workflow.Bioinformatics advances · 2026Article
- Diverse-Ancestry GWAS of Age-Related Macular Degeneration on 16,108 Examined Cases and 18,038 Controls.Investigative ophthalmology & visual science · 2025Article
- Article
- On the differences between mega- and meta-imputation and analysis exemplified on the genetics of age-related macular degeneration.Genetic epidemiology · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
While current genome-wide association analyses often rely on meta-analysis of study-specific summary statistics, individual participant data (IPD) from multiple studies increase options for modeling. When multistudy IPD is available, however, it is unclear whether this data is to be imputed and modeled across all participants (mega-imputation and mega-analysis) or study-specifically (meta-imputation and meta-analysis). Here, we investigated different approaches toward imputation and analysis using 52,189 subjects from 25 studies of the International Age-related Macular Degeneration (AMD) Genomics Consortium including, 16,144 AMD cases and 17,832 controls for association analysis. From 27,448,454 genetic variants after 1,000-Genomes-based imputation, mega-imputation yielded ~400,000 more variants with high imputation quality (mostly rare variants) compared to meta-imputation. For AMD signal detection (P < 5 × 10
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Registered trials
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