mCsmoothing: Smoothing and plotting methylation data
In methylPipe: Base resolution DNA methylation data analysis

Description Usage Arguments Details Value Author(s) Examples

Smoothing and plotting methylation data, even chromosome wide.

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

`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

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

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).

Mattia Pelizzola

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)