HD: Simulated dataset of Hellinger divergences used in the...

In genomaths/MethylIT: Methylation Analysis Based on Signal Detection

Simulated dataset of Hellinger divergences used in the examples

Description

Each individuals sample includes 10000 cytosine positions

Usage

HD

Format

'hdiv is an object from class 'InfDiv' with GRanges-class as elements carrying in the meta-columns the following variables:

c1:

Methylated read counts from the reference sample.

t1:

Unmethylated read counts from the reference sample.

c2:

Methylated read counts from the treatment sample.

t2:

Unmethylated read counts from the treatment sample.

p1:

methylation level from the reference sample.

p2:

methylation level from the treatment sample.

TV:

the total variation distance (difference of methylation levels)

bay.TV:

TV computes with Bayesian correction for the methelation levels.

hdiv:

Hellinger divergence.

jdiv:

J divergence.

'HD' was obtained with function estimateDivergence.

Examples

## Load a dataset of simulated read counts.
data("HD", package = "MethylIT")

## Number of positions with Hellinger divergence values greater than
## the HD_95%
critical.val <- do.call(rbind, lapply(HD, function(x) {
  hd.95 = quantile(x$hdiv, 0.95)
  tv.95 = quantile(abs(x$bay.TV), 0.95)
  return(c(tv = tv.95, hd = hd.95, num.sites.hd95 = sum(x$hdiv > hd.95),
           num.sites.tv95 = sum(x$bay.TV > tv.95)))}))
critical.val

genomaths/MethylIT documentation built on Feb. 3, 2024, 1:24 a.m.