ReviewMethods in molecular biology (Clifton, N.J.)2021
Accurate Imputation of Untyped Variants from Deep Sequencing Data.
Review in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- High performance imputation of structural and single nucleotide variants using low-coverage whole genome sequencing.Genetics, selection, evolution : GSE · 2025Article
- STICI: Split-Transformer with integrated convolutions for genotype imputation.Nature communications · 2025Article
- Machine learning-enhanced multi-trait genomic prediction for optimizing cannabinoid profiles in cannabis.The Plant journal : for cell and molecular biology · 2025Article
- Venous thromboembolic disease genetics: from variants to function.Journal of thrombosis and haemostasis : JTH · 2024Review
- Somatic Mutation Accumulations in Micropropagated Cannabis Are Proportional to the Number of Subcultures.Plants (Basel, Switzerland) · 2024Article
- The Genotypic Variability among Short-Season Soybean Cultivars for Nitrogen Fixation under Drought Stress.Plants (Basel, Switzerland) · 2023Article
- Identification of quantitative trait loci associated with seed quality traits between Canadian and Ukrainian mega-environments using genome-wide association study.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- An autoencoder-based deep learning method for genotype imputation.Frontiers in artificial intelligence · 2022Article
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Authors and funding
2 authors.
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Abstract
The quality, statistical power, and resolution of genome-wide association studies (GWAS) are largely dependent on the comprehensiveness of genotypic data. Over the last few years, despite the constant decrease in the price of sequencing, whole-genome sequencing (WGS) of association panels comprising a large number of samples remains cost-prohibitive. Therefore, most GWAS populations are still genotyped using low-coverage genotyping methods resulting in incomplete datasets. Imputation of untyped variants is a powerful method to maximize the number of SNPs identified in study samples, it increases the power and resolution of GWAS and allows to integrate genotyping datasets obtained from various sources. Here, we describe the key concepts underlying imputation of untyped variants, including the architecture of reference panels, and review some of the associated challenges and how these can be addressed. We also discuss the need and available methods to rigorously assess the accuracy of imputed data prior to their use in any genetic study.
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