Applications in Plant SciencesBioinformaticsPeer-reviewed journal article
nQuack: An R package for predicting ploidal level from sequence data using site-based heterozygosity
Michelle L. GaynoriD, Jacob B. LandisiD, Timothy K. O’ConnoriD, Robert G. LaportiD, Jeff J. DoyleiD, Douglas E. SoltisiD, José Miguel PoncianoiD, Pamela S. SoltisiD
Abstract
PremiseTraditional methods of ploidal level estimation are tedious; leveraging sequence data for cytotype estimation is an ideal alternative. Multiple statistical approaches to leverage DNA sequence data for ploidy prediction based on site-based heterozygosity have been developed. However, these approaches may require high-coverage sequence data, use improper 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 ResultsnQuack performs model selection for improved ploidy predictions. Here, we implement expected 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. ConclusionInferring ploidal level based on site-based heterozygosity alone is discouraged due to the low accuracy of pattern-based inference.
- Citations
- 14
- FWCI
- 3.66
- Field percentile
- top 7%
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