log_sum_exp

Implements empirical Bayes approaches to genotype
polyploids from next generation sequencing data while
accounting for allelic bias, overdispersion, and sequencing
error. The main functions are flexdog() and multidog(),
which allow the specification
of many different genotype distributions. An experimental
function that takes into account varying levels of relatedness
is implemented in mupdog(). 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 (2019) <doi:10.1093/bioinformatics/btz852> for details
on the implemented methods.

David Gerard

log_sum_exp: Log-sum-exponential trick.

Description

Usage

Arguments

Value