cr_enriched_heatmap_at_tss_cgi: Visualizing enrichment for epigenomic signals at TSS-CGIs

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

Description

Visualizing enrichment for epigenomic signals at TSS-CGIs

Usage

cr_enriched_heatmap_at_tss_cgi(cr, txdb, expr, cgi,
    fdr_cutoff = 0.05, meth_diff_cutoff = 0.1, marks = NULL, type = "neg", extend = 5000,
    expr_ha)

Arguments

cr	correalted regions
txdb	transcriptome annotation which was used in correlated_regions
expr	expression matrix which was used in correlated_regions
cgi	CpG island, a GRanges object
fdr_cutoff	cutoff for fdr, used to filter significant CRs
meth_diff_cutoff	cutoff for methylation difference. If there are no subgroup information or only one subgroup, meth_IQR column is used for filtering. If there are more than one subgroups, meth_diameter column is used for filtering.
marks	names of histone marks, should be supported in chipseq_hooks
type	visualize negative correlated regions or positive correlated regions
extend	base pairs extended to upstream and downstream
expr_ha	a HeatmapAnnotation class object. It is used for the expression heatmap

Details

There are several heatmaps visualize various signals enriched at TSS-CGIs. In the plot, in the extended CGI region, one CGI only overlaps to one gene TSS and one gene TSS should only overlap to one extended CGI. Since one CGI only corresponds to one gene, in the heatmap, each row corresponds to one single gene.

There are following heatmaps:

• heatmap for gene expression

• If cr is returned form cr_enriched_heatmap, there is a one column heatmap which shows the k-means cluters genes belong to

• heatmap for significant correlated regions

• a point plot showing CGI length

• heatmap for correlation between methylation and gene expression

• heatmap for mean methylation

• heatmap for metnylation difference

• heatmap for correlation, mean signal and signal difference for histone marks

If there are more than 12 heatmaps, they will be put into two pages.

Heatmaps are split into two sub-clusters by k-means clustering on the mean methylation matrix. If there are two subgroups in all samples, each subcluster are split by high expression/low expression in subgroup 1. In each high expression/low expression, rows are split by the k-means clusters calculated in cr_enriched_heatmap. Finally, rows are clustered by considering closeness of signals in the extended CGI regions.

Value

no value is returned

Author(s)

Zuguang Gu <[e-mail]>

Examples

# There is no example
NULL

jokergoo/epik documentation built on Sept. 28, 2019, 9:20 a.m.