peakpick: Identifies smooth peaks in series of numbers.
In peakPick: Peak Picking Methods Inspired by Biological Data

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.

peakPick documentation built on May 2, 2019, 7:02 a.m.