uni_obj

pivec

A vector of weights. Each element of <code>weight_vec</code> corresponds
to a column of <code>lmat</code>.

weight_vec

A matrix of inner weights. The columns are the "individuals" and the rows are the "classes."

lmat

The penalty on the pi's. Should be greater than 0 and really really small.

lambda

Objective function optimized by <code><a rd-options="" href="/link/uni_em?package=updog&version=1.2.0" data-mini-rdoc="updog::uni_em">uni_em</a></code>.

internal

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

updog

Flexible Genotyping for Polyploids

uni_obj function

Objective function optimized by <code><a rd-options='' href='uni_em'>uni_em</a></code>.

Objective function optimized by <code><a rd-options='' href='uni_em'>uni_em</a></code>. — uni_obj

Objective function optimized by <code><a rd-options='' href='uni_em'>uni_em</a></code>.

Objective function optimized by <code><a rd-options="" href="/link/uni_em?package=updog&version=1.2.0" data-mini-rdoc="updog::uni_em">uni_em</a></code>.

uni_obj: Objective function optimized by `uni_em`.

Description

Usage

Arguments

Value