This function allows the correction of experimental coverage profiles (usually MNase digested nucleosomal DNAs in this library) with control samples (usually naked DNA sample digested with MNase). This is useful to correct MNase biase.
Calculates the coverage values from a RangedData object (or anything with a defined coverage function associated) and returns the coverage normalized to reads per million, allowing the comparison of experiments with a different absolut number of reads.
Remove noise from genomic data smoothing and cleaning the observed signal. This function doesn't alter the shape or the values of the signal as much as the traditional method of sliding window average does, providing a great correlation within the original and filtered data (>0.99).
When using single-ended sequencing, the resulting partial sequences map only in one strand, causing a bias in the coverage profile if not corrected. The only way to correct this is knowing the average size of the real fragments. nucleR uses this information when preprocessing single-ended sequences. You can provide this information by your own (usually a 147bp length is a good aproximation) or you can use this method to automatically guess the size of the inserts.
This function tries to obtain the minimum number of components needed in a FFT filter to achieve or get as close as possible to a given correlation value. Usually you don't need to call directly this function, is used in filterFFT by default.
providing 
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