ArticleGenetics2016
Imputing Genotypes in Biallelic Populations from Low-Coverage Sequence Data.
Article in Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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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
35 citing papers in PubMed.
- Article
- Article
- Evaluation of Low-Coverage Sequencing Strategies for Whole-Genome Imputation in Pacific AbaloneInternational journal of molecular sciences · 2025Article
- Rapid change in red cell blood group systems after the main Out of Africa of Homo sapiens.Scientific reports · 2025Article
- Fast and accurate imputation of genotypes from noisy low-coverage sequencing data in bi-parental populations.PloS one · 2025Article
- A genome-wide association study using MyanmarBreeding science · 2024Article
- Single- and multiple-trait quantitative trait locus analyses for seed oil and protein contents of soybean populations with advanced breeding line background.Molecular breeding : new strategies in plant improvement · 2024Article
- Genotyping of SNPs in bread wheat at reduced cost from pooled experiments and imputation.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Integration of genetic and genomics resources in einkorn wheat enables precision mapping of important traits.Communications biology · 2023Article
- Whole-genome analysis of recombinant inbred rice lines reveals a quantitative trait locus on chromosome 3 with genotype-by-environment interaction effects.G3 (Bethesda, Md.) · 2023Article
- Reliable genotyping of recombinant genomes using a robust hidden Markov model.Plant physiology · 2023Article
- GBScleanR: robust genotyping error correction using a hidden Markov model with error pattern recognition.Genetics · 2023Article
- Disentangling the complex gene interaction networks between rice and the blast fungus identifies a new pathogen effector.PLoS biology · 2023Article
- Hybridization is strongly constrained by salinity during secondary contact between silverside fishes (Odontesthes, Atheriniformes).Heredity · 2022Article
- Genotype imputation for soybean nested association mapping population to improve precision of QTL detection.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Genetic mapping of loci involved in oil tocopherol composition control in Russian sunflower (Helianthus annuus L.) lines.G3 (Bethesda, Md.) · 2022Article
- Genome-wide imputation using the practical haplotype graph in the heterozygous crop cassava.G3 (Bethesda, Md.) · 2022Article
- Genotyping, the Usefulness of Imputation to Increase SNP Density, and Imputation Methods and Tools.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy.GigaScience · 2021Article
- RIL-StEp: epistasis analysis of rice recombinant inbred lines reveals candidate interacting genes that control seed hull color and leaf chlorophyll content.G3 (Bethesda, Md.) · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Low-coverage next-generation sequencing methodologies are routinely employed to genotype large populations. Missing data in these populations manifest both as missing markers and markers with incomplete allele recovery. False homozygous calls at heterozygous sites resulting from incomplete allele recovery confound many existing imputation algorithms. These types of systematic errors can be minimized by incorporating depth-of-sequencing read coverage into the imputation algorithm. Accordingly, we developed Low-Coverage Biallelic Impute (LB-Impute) to resolve missing data issues. LB-Impute uses a hidden Markov model that incorporates marker read coverage to determine variable emission probabilities. Robust, highly accurate imputation results were reliably obtained with LB-Impute, even at extremely low (<1×) average per-marker coverage. This finding will have implications for the design of genotype imputation algorithms in the future. LB-Impute is publicly available on GitHub at https://github.com/dellaporta-laboratory/LB-Impute.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.