ArticleApplications in plant sciences
nQuack: An R package for predicting ploidal level from sequence data using site-based heterozygosity.
Article in Applications in plant sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
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- Forecasts of climate-driven habitat suitability distribution are complicated by taxonomic and cytogenetic complexity inAoB PLANTS · 2026Article
- Development of a low-coverage whole genome sequencing screen for apomixis using a diverse set of Malus germplasm.PLoS genetics · 2026Article
- Tyrosine kinase targeting uncovers oncogenic pathway plasticity in Tasmanian devil transmissible cancers.The EMBO journal · 2026Article
- Patterns of Interploidy Admixture in Polyploid Complexes: Insights From Thymus Sect. Mastichina (Lamiaceae).Molecular ecology · 2026Article
- The frequency and importance of polyploidy in tropical rainforest tree radiations.The New phytologist · 2026Article
- Whole-Genome Sequence of Potamopyrgus antipodarum-A Model System for the Maintenance of Sexual Reproduction-Reveals a Recent Whole-Genome Duplication.Genome biology and evolution · 2025Article
- Exploring chromosomal variations in garden roses: Insights from high-density SNP array data and a new tool, Qploidy.The plant genome · 2025Article
- Harnessing Genomics for BreedingInternational journal of molecular sciences · 2025Article
- Ancient polyploidization events influence the evolution of the ginseng family (Araliaceae).Frontiers in plant science · 2025Article
- nQuack: An R package for predicting ploidal level from sequence data using site-based heterozygosity.Applications in plant sciencesArticle
- Variant calling in polyploids for population and quantitative genetics.Applications in plant sciencesArticle
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Authors and funding
8 authors.
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Abstract
Premise: Traditional methods of ploidal-level estimation are tedious; using DNA sequence data for cytotype estimation is an ideal alternative. Multiple statistical approaches to leverage sequence data for ploidy inference based on site-based heterozygosity have been developed. However, these approaches may require high-coverage sequence data, use inappropriate probability distributions, or have additional statistical shortcomings that limit inference abilities. We introduce nQuack, an open-source R package that addresses the main shortcomings of current methods. Methods and Results: nQuack performs model selection for improved ploidy predictions. Here, we implement expectation maximization algorithms with normal, beta, and beta-binomial distributions. Using extensive computer simulations that account for variability in sequencing depth, as well as real data sets, we demonstrate the utility and limitations of nQuack. Conclusions: Inferring ploidy based on site-based heterozygosity alone is difficult. Even though nQuack is more accurate than similar methods, we suggest caution when relying on any site-based heterozygosity method to infer ploidy.
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