updog: Flexible Genotyping for Polyploids

Implements empirical Bayes approaches to genotype polyploids from next generation sequencing data while accounting for allele bias, overdispersion, and sequencing error. The main functions are flexdog() and multidog(), which allow the specification of many different genotype distributions. Also provided are functions to simulate genotypes, rgeno(), and read-counts, rflexdog(), as well as functions to calculate oracle genotyping error rates, oracle_mis(), and correlation with the true genotypes, oracle_cor(). These latter two functions are useful for read depth calculations. Run browseVignettes(package = "updog") in R for example usage. See Gerard et al. (2018) <doi:10.1534/genetics.118.301468> and Gerard and Ferrao (2020) <doi:10.1093/bioinformatics/btz852> for details on the implemented methods.

Version: 2.1.5
Depends: R (≥ 3.4.0)
Imports: Rcpp (≥ 0.12.16), RcppArmadillo, assertthat, ggplot2, reshape2, foreach, future, doFuture, doRNG, methods, iterators
LinkingTo: Rcpp, RcppArmadillo
Suggests: covr, testthat, SuppDists, knitr, rmarkdown, VariantAnnotation, GenomicRanges, S4Vectors, IRanges
Published: 2023-11-29
DOI: 10.32614/CRAN.package.updog
Author: David Gerard ORCID iD [aut, cre]
Maintainer: David Gerard <gerard.1787 at gmail.com>
BugReports: https://github.com/dcgerard/updog/issues
License: GPL-3
URL: https://github.com/dcgerard/updog/
NeedsCompilation: yes
Citation: updog citation info
Materials: README NEWS
CRAN checks: updog results


Reference manual: updog.pdf
Vignettes: Genotyping Many SNPs with multidog()
Oracle Calculations
Simulate Next-Generation Sequencing Data
Example Use of Updog


Package source: updog_2.1.5.tar.gz
Windows binaries: r-devel: updog_2.1.5.zip, r-release: updog_2.1.5.zip, r-oldrel: updog_2.1.5.zip
macOS binaries: r-release (arm64): updog_2.1.5.tgz, r-oldrel (arm64): updog_2.1.5.tgz, r-release (x86_64): updog_2.1.5.tgz, r-oldrel (x86_64): updog_2.1.5.tgz
Old sources: updog archive

Reverse dependencies:

Reverse imports: hwep
Reverse suggests: ldsep, mappoly, polymapR


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