ArticleGenetics2015
Genotype-Frequency Estimation from High-Throughput Sequencing Data.
Article in Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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
17 citing papers in PubMed.
- What can we infer about mutation calling by using time-series mutation accumulation data and a Bayesian Mutation Finder?Ecology and evolution · 2024Article
- The genome-wide signature of short-term temporal selection.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Evolutionary Insights from a Large-Scale Survey of Population-Genomic Variation.Molecular biology and evolution · 2023Article
- Evolutionary Genomics of Sister Species Differing in Effective Population Sizes and Recombination Rates.Genome biology and evolution · 2023Article
- Evolutionary Insights from a Large-scale Survey of Population-genomic Variation.bioRxiv : the preprint server for biology · 2023Article
- The Linkage-Disequilibrium and Recombinational Landscape in Daphnia pulex.Genome biology and evolution · 2022Article
- Evolutionary Genomics of a Subdivided Species.Molecular biology and evolution · 2022Article
- Genetic variation for tolerance to the downy mildew pathogen Peronospora variabilis in genetic resources of quinoa (Chenopodium quinoa).BMC plant biology · 2021Article
- The Limits to Estimating Population-Genetic Parameters with Temporal Data.Genome biology and evolution · 2020Article
- Association Mapping Analysis for Fruit Quality Traits inFrontiers in plant science · 2018Article
- Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions.Bioinformatics (Oxford, England) · 2017Article
- LinkImputeR: user-guided genotype calling and imputation for non-model organisms.BMC genomics · 2017Article
- Genotype Calling from Population-Genomic Sequencing Data.G3 (Bethesda, Md.) · 2017Article
- Population Genomics ofGenetics · 2017Article
- Article
- Optimized Next-Generation Sequencing Genotype-Haplotype Calling for Genome Variability Analysis.Evolutionary bioinformatics online · 2017Article
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Rapidly improving high-throughput sequencing technologies provide unprecedented opportunities for carrying out population-genomic studies with various organisms. To take full advantage of these methods, it is essential to correctly estimate allele and genotype frequencies, and here we present a maximum-likelihood method that accomplishes these tasks. The proposed method fully accounts for uncertainties resulting from sequencing errors and biparental chromosome sampling and yields essentially unbiased estimates with minimal sampling variances with moderately high depths of coverage regardless of a mating system and structure of the population. Moreover, we have developed statistical tests for examining the significance of polymorphisms and their genotypic deviations from Hardy-Weinberg equilibrium. We examine the performance of the proposed method by computer simulations and apply it to low-coverage human data generated by high-throughput sequencing. The results show that the proposed method improves our ability to carry out population-genomic analyses in important ways. The software package of the proposed method is freely available from https://github.com/Takahiro-Maruki/Package-GFE.
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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.