signalGrouping: Signal grouping

Description Usage Arguments Value

Description

Euclidean distances between m/z signals are hierarchically clustering using the average method and the composite spectrum groups determined by a absolute error cutoff

Usage

1
signalGrouping(spectrum.df = NULL, mzError = 0.001, minPeaks = 5)

Arguments

spectrum.df

a dataframe or matrix with two or more columns: 1. Mass/ Mass-to-charge ratio 2. Intensity

mzError

interpeak absolute m/z error for signal grouping (Default = 0.001)

Value

dataframe of m/z grouped signals, the m/z values of the input dataframe/ matrix peak groups are averaged and the signal intensities summed.


WMBEdmands/compMS2Miner documentation built on May 9, 2019, 10:04 p.m.