grad_for_weighted_lnorm

A vector of length 2. The first term is the current mean of the
underlying normal. The second term is the current standard deviation
(not variance) of the normal.

parvec

ploidy

A vector of length <code>ploidy + 1</code> that contains the weights
for each component beta-binomial.

weight_vec

Gradient for <code><a rd-options="" href="/link/obj_for_weighted_lnorm?package=updog&version=1.1.3" data-mini-rdoc="updog::obj_for_weighted_lnorm">obj_for_weighted_lnorm</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 function is flexdog(), which allows 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

grad_for_weighted_lnorm function

Gradient for <code><a rd-options='' href='obj_for_weighted_lnorm'>obj_for_weighted_lnorm</a></code>.

Gradient for <code><a rd-options='' href='obj_for_weighted_lnorm'>obj_for_weighted_lnorm</a></code>. — grad_for_weighted_lnorm

Gradient for <code><a rd-options='' href='obj_for_weighted_lnorm'>obj_for_weighted_lnorm</a></code>.

Gradient for <code><a rd-options="" href="/link/obj_for_weighted_lnorm?package=updog&version=1.1.3" data-mini-rdoc="updog::obj_for_weighted_lnorm">obj_for_weighted_lnorm</a></code>.

grad_for_weighted_lnorm: Gradient for `obj_for_weighted_lnorm`.

Description

Usage

Arguments

Value