topDirs: Filter results of multiHiCcompare

In multiHiCcompare: Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available

Description

Filter results of multiHiCcompare

Usage

topDirs(
  hicexp,
  logfc_cutoff = 1,
  logcpm_cutoff = 1,
  p.adj_cutoff = 0.01,
  D_cutoff = 1,
  alpha = 0.05,
  return_df = "pairedbed"
)

Arguments

hicexp	A hicexp object which has been compared.
logfc_cutoff	The logFC value you wish to filter by. Defaults to 1.
logcpm_cutoff	The logCPM cutoff you wish to filter by. Defaults to 1.
p.adj_cutoff	The adjusted p-value cutoff you wish to filter by. Defaults to 0.01.
D_cutoff	The distance cutoff you wish to filter by. Interactions with a D < D_cutoff will be filtered. Defaults to 1.
alpha	The p-value cutoff for determining the count of number of times a region is significant. Used to calculate the number of times a region was detected as significantly interacting. Defaults to 0.05.
return_df	The format for the data.frame returned by the function. Options are "bed" and "pairedbed".

Details

This function is meant to filter the results of multiHiCcompare. The top differentially interacting regions (DIRs) can be returned by using this function. When the return_df = "bed" option is set the resulting data.frame can be input into the plot_pvals or plot_counts functions to visualize the top DIRs.

Value

A data.table containing the filtered results.

Examples

data('hicexp_diff')
topDirs(hicexp_diff)

multiHiCcompare documentation built on Nov. 8, 2020, 7:04 p.m.