| updog-package {updog} | R Documentation |
updog Flexible Genotyping for Polyploids
Description
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.
Details
The package is named updog for "Using
Parental Data for Offspring Genotyping" because
we originally developed the
method for full-sib populations, but it works
now for more general populations.
Our best competitor is probably the fitPoly package,
which you can check out at
https://cran.r-project.org/package=fitPoly. Though, we think
that updog returns better calibrated measures of uncertainty
when you have next-generation sequencing data.
If you find a bug or want an enhancement, please submit an issue at https://github.com/dcgerard/updog/issues.
updog Functions
flexdog()The main function that fits an empirical Bayes approach to genotype polyploids from next generation sequencing data.
multidog()A convenience function for running
flexdog()over many SNPs. This function provides support for parallel computing.format_multidog()Return arrayicized elements from the output of
multidog().filter_snp()Filter SNPs based on the output of
multidog()rgeno()simulate the genotypes of a sample from one of the models allowed in
flexdog().rflexdog()Simulate read-counts from the
flexdog()model.plot.flexdog()Plotting the output of
flexdog().plot.multidog()Plotting the output of
multidog().oracle_joint()The joint distribution of the true genotype and an oracle estimator.
oracle_plot()Visualize the output of
oracle_joint().oracle_mis()The oracle misclassification error rate (Bayes rate).
oracle_cor()Correlation between the true genotype and the oracle estimated genotype.
updog Datasets
snpdatA small example dataset for using
flexdog.uitdewilligenA small example dataset
Author(s)
David Gerard
References
Gerard, D., Ferrão, L. F. V., Garcia, A. A. F., & Stephens, M. (2018). Genotyping Polyploids from Messy Sequencing Data. Genetics, 210(3), 789-807. doi:10.1534/genetics.118.301468.
Gerard, David, and Luís Felipe Ventorim Ferrão. "Priors for genotyping polyploids." Bioinformatics 36, no. 6 (2020): 1795-1800. doi:10.1093/bioinformatics/btz852.