person("Nikolai", "Ryzhkov", email="namezys@gmail.com", role=c("aut", "cre"), comment = c(ORCID = "0000-0003-4896-280X")),
Nikolai Ryzhkov [aut, cre] (<https://orcid.org/0000-0003-4896-280X>),

Title: The Pharmacokinetics (PK) of Multi-Component Drugs Using a
Author: Mengci Li, Shouli Wang, Guoxiang Xie, Tianlu Chen, Wei Jia
Description: Poly-PK strategy is a new strategy of pharmacokinetic analysis of multi-component drugs (Guoxiang Xie, Tianlu Chen, Wei Jia, et al. (2012)<doi:10.1021/pr300318m>; Ke Lan, Guoxiang Xie and Wei Jia. (2013)<doi:10.1155/2013/819147>). This package is the first implementation of the Poly-PK strategy with 10 easy-to-use functions.

Author: Mengci Li, Shouli Wang, Guoxiang Xie, Tianlu Chen and Wei Jia

Title: Genotype Calling with Uncertainty from Sequencing Data in
Authors@R: c(person("Lindsay V.", "Clark", email = "lvclark@illinois.edu",
person("U.S. National Science Foundation", role = "fnd"))
Author: Lindsay V. Clark [aut, cre] (<https://orcid.org/0000-0002-3881-9252>),
Maintainer: Lindsay V. Clark <lvclark@illinois.edu>
Imports: fastmatch, pcaMethods, methods, Rcpp
Suggests: rrBLUP, Rsamtools, GenomeInfoDb, Biostrings, GenomicRanges,
Description: Read depth data from genotyping-by-sequencing (GBS) or restriction
site-associated DNA sequencing (RAD-seq) are imported and used to make Bayesian
probability estimates of genotypes in polyploids or diploids.  The genotype
probabilities, or genotypes sampled from those probabilties, can then be exported
for downstream analysis.  'polyRAD' is described by Clark et al. (2018)

BiocGenerics, knitr, rmarkdown, GenomicFeatures, qqman

for downstream analysis.  'polyRAD' is described by Clark et al. (2019)

BiocGenerics, knitr, rmarkdown, GenomicFeatures, qqman, ggplot2
probabilities, posterior mean genotypes, or most probable genotypes can then
be exported for downstream analysis.  'polyRAD' is described by Clark et al.
(2019) <doi:10.1534/g3.118.200913>.  A variant calling pipeline for highly
duplicated genomes is also included and is described by Clark et al. (2020)