mCsmoothing: Smoothing and plotting methylation data

Description Usage Arguments Details Value Author(s) Examples

Description

Smoothing and plotting methylation data, even chromosome wide.

Usage

1
2
3
## S4 method for signature 'methylPipe,BSdata'
mCsmoothing(Object, refgr, Scorefun='sum', Nbins=20,
Context="CG", plot=TRUE)

Arguments

Object

An object of class BSdata

refgr

GRanges; Genomic Ranges to plot the data

Scorefun

character; either sum or mean for smoothing

Nbins

numeric; the number of interval each range is divided

Context

character; either all or a combination of CG, CHG, and CHH

plot

logical; whether the smoothed profile has to be plotted

Details

The sum or the mean methylation level is determined on each window of size Binsize and smoothed with the smooth.spline function.

Value

A list with three components: pos (the left most point of each window), score (either the sum or the mean methylation levels), smoothed (the smoothed methylation levels).

Author(s)

Mattia Pelizzola

Examples

1
2
3
4
5
6
require(BSgenome.Hsapiens.UCSC.hg18)
uncov_GR <- GRanges(Rle('chr20'), IRanges(c(14350,69251,84185), c(18349,73250,88184)))
H1data <- system.file('extdata', 'H1_chr20_CG_10k_tabix_out.txt.gz', package='methylPipe')
H1.db <- BSdata(file=H1data, uncov=uncov_GR, org=Hsapiens)
gr <- GRanges("chr20",IRanges(1,5e5))
sres <- mCsmoothing(H1.db, gr, Scorefun='sum', Nbins=50, Context="CG", plot=TRUE)

methylPipe documentation built on May 20, 2017, 10:04 p.m.

Search within the methylPipe package
Search all R packages, documentation and source code