ArticleAmerican journal of human genetics2022
MagicalRsq: Machine-learning-based genotype imputation quality calibration.
Article in American journal of human genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00037765 (Gene Modifiers of Cystic Fibrosis Lung Disease), which is not on this map. Cited by 16 papers.
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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.
Gene Modifiers of Cystic Fibrosis Lung Disease
Who cites it
16 citing papers in PubMed.
- ALGI: Sparse Convolutional Denoising Autoencoder Utilizing Local Genomic Information for Genotype Imputation.Animals : an open access journal from MDPI · 2026Article
- MetaGLIMPSE: Meta-imputation of low-coverage sequencing data for modern and ancient genomes.American journal of human genetics · 2026Article
- Sharing approaches in predictive genomics across animals, plants and humans.Nature genetics · 2026Review
- Advances in haplotype phasing and genotype imputation.Nature reviews. Genetics · 2026Review
- Recommendations for responsible use of population descriptors in polygenic risk score development.Nature genetics · 2025Review
- Aggregating single nucleotide polymorphisms improves filtering for false-positive associations postimputation.G3 (Bethesda, Md.) · 2025Article
- Polygenic Scores of Cardiometabolic Risk Factors in American Indian Adults.JAMA network open · 2025Article
- Empirical versus estimated accuracy of imputation: optimising filtering thresholds for sequence imputation.Genetics, selection, evolution : GSE · 2024Article
- A genome-wide association study of alloimmunization in the TOPMed OMG-SCD cohort identifies a locus on chromosome 12.Transfusion · 2024Article
- MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.American journal of human genetics · 2024Article
- Imputation accuracy across global human populations.American journal of human genetics · 2024Article
- A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.NPJ genomic medicine · 2024Article
- Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI.Nature communications · 2024Article
- A rapid and reference-free imputation method for low-cost genotyping platforms.Scientific reports · 2023Article
- Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels.Briefings in bioinformatics · 2023Article
- Imputation Accuracy Across Global Human Populations.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Whole-genome sequencing (WGS) is the gold standard for fully characterizing genetic variation but is still prohibitively expensive for large samples. To reduce costs, many studies sequence only a subset of individuals or genomic regions, and genotype imputation is used to infer genotypes for the remaining individuals or regions without sequencing data. However, not all variants can be well imputed, and the current state-of-the-art imputation quality metric, denoted as standard Rsq, is poorly calibrated for lower-frequency variants. Here, we propose MagicalRsq, a machine-learning-based method that integrates variant-level imputation and population genetics statistics, to provide a better calibrated imputation quality metric. Leveraging WGS data from the Cystic Fibrosis Genome Project (CFGP), and whole-exome sequence data from UK BioBank (UKB), we performed comprehensive experiments to evaluate the performance of MagicalRsq compared to standard Rsq for partially sequenced studies. We found that MagicalRsq aligns better with true R
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