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Last data update: 2014.03.03

R: Identify UMRs and LMRs

segmentUMRsLMRs

R Documentation

Identify UMRs and LMRs

Description

This function identifies hypomethylated regions and classifies them into UMRs and LMRs.

Usage

segmentUMRsLMRs(m, meth.cutoff = 0.5, nCpG.cutoff = 3, PMDs = NA,
pdfFilename, num.cores = 1, myGenomeSeq, seqLengths, nCpG.smoothing = 3,
minCover = 5)

Arguments

`m`	GRanges object containing the methylation data.
`meth.cutoff`	Cut-off on methylation for calling hypomethylated regions.
`nCpG.cutoff`	Cut-off on the minimal number of CpGs for calling hypomethylated regions.
`PMDs`	GRanges object of PMDs. Set to either the return value of the function segmentPMDs (see example) or to NA if there are no PMDs (default).
`pdfFilename`	Name of the pdf file in which the figure is saved. If no name is provided (default), the figure is printed to the screen.
`num.cores`	Number of cores used for the calculations.
`myGenomeSeq`	Genome sequence as BSgenome object.
`seqLengths`	A named vector indicating the chromosome lengths of the genome used.
`nCpG.smoothing`	The number of consecutive CpGs that the methylation levels are averaged over.
`minCover`	Only CpGs with a coverage of at least minCover reads will be used.

Value

Returns a GRanges object containing all UMRs and LMRs with the following metadata values: the number of CpGs with a coverage of at least minCover per region (nCG.segmentation), the number of CpGs in the DNA sequence (nCG), the total number of reads that map to CpGs in the region (T), the total number of read that map to CpGs without conversion of the C (M), the mean methylation of the segment (pmeth), the median methylation of the segment (median.meth) and the type (UMR/LMR) of region (type). The function creates a figure showing the classification of regions into UMRs and LMRs based on the number of CpGs they contain. The figure is either printed to the screen (default) or saved as a pdf if a filename is provided.

Author(s)

Lukas Burger lukas.burger@fmi.ch

Examples


library(MethylSeekR)

# get chromosome lengths
library("BSgenome.Hsapiens.UCSC.hg18")
sLengths=seqlengths(Hsapiens)

# read methylation data
methFname <- system.file("extdata", "Lister2009_imr90_hg18_chr22.tab",
package="MethylSeekR")
meth.gr <- readMethylome(FileName=methFname, seqLengths=sLengths)

FDR.cutoff <- 5 
m.sel <- 0.5 
n.sel <- 3

#segment UMRs and LMRs, assuming no PMDs
UMRLMRsegments.gr <- segmentUMRsLMRs(m=meth.gr, meth.cutoff=m.sel,
nCpG.cutoff=n.sel, myGenomeSeq=Hsapiens, seqLengths=sLengths)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MethylSeekR)
Loading required package: rtracklayer
Loading required package: GenomicRanges
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: mhsmm
Loading required package: mvtnorm
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MethylSeekR/segmentUMRsLMRs.Rd_%03d_medium.png", width=480, height=480)
> ### Name: segmentUMRsLMRs
> ### Title: Identify UMRs and LMRs
> ### Aliases: segmentUMRsLMRs
> 
> ### ** Examples
> 
> 
> library(MethylSeekR)
> 
> # get chromosome lengths
> library("BSgenome.Hsapiens.UCSC.hg18")
Loading required package: BSgenome
Loading required package: Biostrings
Loading required package: XVector
> sLengths=seqlengths(Hsapiens)
> 
> # read methylation data
> methFname <- system.file("extdata", "Lister2009_imr90_hg18_chr22.tab",
+ package="MethylSeekR")
> meth.gr <- readMethylome(FileName=methFname, seqLengths=sLengths)
reading methylome data
Read 200000 records
> 
> FDR.cutoff <- 5 
> m.sel <- 0.5 
> n.sel <- 3
> 
> #segment UMRs and LMRs, assuming no PMDs
> UMRLMRsegments.gr <- segmentUMRsLMRs(m=meth.gr, meth.cutoff=m.sel,
+ nCpG.cutoff=n.sel, myGenomeSeq=Hsapiens, seqLengths=sLengths)
identifying UMRs and LMRs
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>