dpen_deps

The current sequencing error rate.

The mean of the logit of the sequencing error rate.

mu_eps

The variance of the logit of the sequencing error rate.

sigma2_eps

Derivative of $$-log(\epsilon(1 - \epsilon)) - (logit(\epsilon) - \mu_{\epsilon})^2 / (2\sigma_{\epsilon}^2)$$
with respect to $\epsilon$.

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

dpen_deps function

Derivative of $$-log(\epsilon(1 - \epsilon)) - (logit(\epsilon) - \mu_{\epsilon})^2 / (2\sigma_{\epsilon}^2)$$
with respect to $\epsilon$. — dpen_deps

dpen_deps: Derivative of $$-log(\epsilon(1 - \epsilon)) - (logit(\epsilon) - \mu_{\epsilon})^2 / (2\sigma_{\epsilon}^2)$$ with respect to \(\epsilon\).

Description

Usage

Arguments

Value

See Also