Description Usage Arguments Value References
This algorithm detects peaks, smooth bumps in series of numbers. This algorithm should not be used for series containing brief spikes. Consider filtering/smoothing your data before using this algorithm. Please refer to the paper by Weber et al. for more details.
1 2 | peakpick(mat, neighlim, deriv.lim = 0.04, peak.min.sd = 0.5,
peak.npos = 10L, mc.cores = 1)
|
mat |
matrix of series with series organized columnwise |
neighlim |
integer limit for how far apart peaks must be. Peak pairs closer than or equal to neighlim to each other have the lesser peak eliminated. |
deriv.lim |
numeric upper limit for the estimatied derivative for a point to be considered for a peak call |
peak.min.sd |
numeric minimum number of standard deviations for a peak to rise above the mean of its immediate vicinity in order to be considered for a peak call |
peak.npos |
integer peak standard deviations and means will be estimated plus/minus npos positions from peak |
mc.cores |
the number of cores to perform this computation |
boolean matrix with dimensions of mat representing peaks
Weber, C.M., Ramachandran, S., and Henikoff, S. (2014). Nucleosomes are context-specific, H2A.Z-modulated barriers to RNA polymerase. Molecular Cell 53, 819-830.
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