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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