get_kl_divergences: Get Kullback-Leibler Divergences

In andrewGhazi/malacoda: Bayesian Analysis of High-Throughput Genomic Assays

Description

Assess the prior improvement using Kullback-Leibler divergence

Usage

get_kl_divergences(mpra_data, cond_prior, marg_prior, n_cores, verbose = TRUE)

Arguments

mpra_data	a data frame of mpra data
cond_prior	a conditional prior (see fit_cond_prior())
marg_prior	a marginal prior (see fit_marg_prior())
n_cores	number of cores for parallelization
verbose	logical indicating whether to print messages

Value

a data frame giving the KL between the observed normalized counts and the two priors for each allele of each variant_id

Note

The KL divergences are approximations because gamma kernel density estimation is used to obtain the empirical distribution of the normalized counts.

andrewGhazi/malacoda documentation built on Aug. 2, 2020, 12:54 a.m.