hilbert_curve_methylation_difference: Visualize methylation difference by Hilbert curve

In jokergoo/epik: Integrative Analysis and Visualization of Epigenomic Sequencing Data

Description

Visualize methylation difference by Hilbert curve

Usage

hilbert_curve_methylation_difference(subgroup, comparison, chromosome = paste0("chr", 1:22),
    species = "hg19", type = c("global_mean", "subgroup_mean", "difference"))

Arguments

subgroup	subgroup information which corresponds to sample IDs stored in methylation_hooks. The value can be a vector with same length as sample IDs or a named vector that names are sample IDs if you only use a subset of samples.
comparison	if there are more than one subgroups, the comparison of two subgroups which shows the methylation difference The value is a vector of length of two and the difference is calculated as subgroup[1] - subgroup[2]
chromosome	a vector of chromosome names
species	species
type	Three types of visualization are supported, see "details" section

Details

Genome is segmented by 1kb window and mean methylation for each 1kb window is calculated, later visualized by Hilbert curve.

There are three types of visualization methods:

global_mean

the mean methylation averaged from all samples

subgroup_mean

the mean methylation averaged in every subgroup

difference

the difference of methylation in two subgroups

To compare methylation in two subgroups, users can use following two ways:

• directly compare mean methylation in the two subgroups

• use combination of "global_mean" + "difference" (this one I feel better to visualize the difference)

Value

A GRanges object which contains mean methylation for the 1kb segmentation and other statistics. If users just need this object without making any plots, set type = "none".

The returned value can be sent to general_chipseq_association_to_methylation.

Author(s)

Zuguang Gu <[e-mail]>

Examples

# There is no example
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jokergoo/epik documentation built on Sept. 28, 2019, 9:20 a.m.