waveletThresholding: Perform Wavelet CWT Thresholding

Description Usage Arguments Details Note Author(s) See Also

View source: R/waveletThresholding.R

Description

Apply precomputed wavelet coefficient threshold to continuous wavelet transform (CWT) of specified input data. Thresholding performed chromosome-by-chromosome. Only scales > minscale considered for peak detection. Number of significant scales has to be > minsig for the window to be considered significant.

Usage

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waveletThresholding(infile, outdir, exptname, mother = "morlet", winsize = 200, minsig = 2, minsigscale = 3, 
	maxsigscale = -1, p.thres = 0.2, p.min = 0.001, p.max = 0.3)

Arguments

infile

Input padded graph file (required)

outdir

Output directory (required)

exptname

Unique string to identify name of experiment (required)

mother

Wavelet mother function used for the CWT. Tested choices are "morlet","haar","gaussian1", "gaussian2" (default="morlet")

winsize

Window size for padded graph files (default=200)

minsig

Minimum number of significant scales for a window to be considered significant (default=2)

minsigscale

Minimum significant scale considered for peak detection (default=3)

maxsigscale

Minimum significant scale considered for peak detection (default=-1)

p.thres

Threshold p-value for calling significant windows (default=0.2)

p.min

Minimum quantile (1-p.min) to be output for wavelet coefficient distribution (default=0.3)

p.max

Maximum quantile (1-p.max) as above (default=0.001)

Details

This function writes the results from the wavelet thresholding into a file within the peaks folder of outdir.

Note

Function messages are piped to a log file which can be found in the log folder of outdir.

Author(s)

Apratim Mitra

See Also

wavCWT


WaveSeqR documentation built on May 2, 2019, 5:19 p.m.