edmr: Empirical differentially methylated regions

Description Usage Arguments Value Examples

View source: R/edmr.R

Description

Comprehensive DMR analysis based on bimodal normal distribution model and weighted cost function for regional methylation analysis optimization. It captures the regional methylation modification by taking the spatial distribution of CpGs into account for the enrichment DNA methylation sequencing data so as to optimize the definition of the empirical regions. Combined with the dependent adjustment for regional p-value combination.

Usage

1
2
3
edmr(myDiff, step = 100, dist = "none", DMC.qvalue = 0.01,
  DMC.methdiff = 25, num.DMCs = 1, num.CpGs = 3, DMR.methdiff = 20,
  plot = FALSE, main = "", mode = 1, ACF = TRUE, fuzzypval = 1)

Arguments

myDiff

a data.frame object created by calculateDiffMeth from methylKit package and converted into data.frame. Required.

step

a numeric variable for calculating auto-correlation, default: 100.

dist

distance cutoff to call a gap for DMR, default: "none", which will be automatically determined by the bimodal normal distribution, default: 100.

DMC.qvalue

qvalue cutoff for DMC definition, default: 0.01

DMC.methdiff

methylation difference cutoff for DMC definition, default: 25.

num.DMCs

cutoff of the number DMCs in each region to call DMR, default: 1.

num.CpGs

cutoff of the number of CpGs, default: 3.

DMR.methdiff

cutoff of the DMR mean methylation difference, default=20.

plot

plot the bimodal normal distribution fitting or not, default=FAlSE.

main

the title of the plot, if plot=TRUE. Default=FALSE.

mode

the mode of call DMRs. 1: using all CpGs together. 2: use unidirectional CpGs to call DMRs. default: 1.

ACF

p-value combination test with (TRUE, default) or without (FALSE) dependency adjustment.

fuzzypval

p-value cutoff for raw regions definition.

Value

GRanges

Examples

1
2
3
4
5
6
7
library(GenomicRanges)
library(IRanges)
library(mixtools)
library(data.table)
data(edmr)
mydmr=edmr(myDiff[1:5000,], mode=1, ACF=FALSE)
mysigdmr=filter.dmr(mydmr)

ShengLi/edmr documentation built on Sept. 17, 2021, 3:38 a.m.