# characterize_peak This function characterizes peaks by species/strain in a simulated spectrum after taking the highest peak or merging peaks in each bin. ```r characterize_peak(spec, option = 1, bin.size = 1, min.mz = 1000, max.mz = 2200) ``` ## Arguments - `spec`: A data frame that contains m/z values of peaks, normalized intensities of peaks, species names, and strain names. Either an output of `simulate_poly_spectra` or one elements of a list output from `simulate_many_poly_spectra`. - `option`: An option on how to merge peaks. There are two options: 1) no merge, thus take the highest intensity peak in each bin after binning a spectrum by bin.size, or 2) take a sum of intensity within each bin after binning a spectrum by bin.size. - `bin.size`: An integer. A bin size. (1 by default) - `min.mz`: A real number. Minimum mass-to-charge ratio. (1000 by default) - `max.mz`: A real number. Maximum mass-to-charge ratio. (2200 by default) ## Returns A data frame that contains m/z values of peaks (mz), intensities of peaks (int), species names (species), and strain names (strain). Species and strain columns may contain more than one species/strain if an option 2 is chosen. ## Examples ```r spectra.processed.A <- process_monospectra( file=system.file("extdata", "listA.txt", package="MGMS2"), mass.range=c(1000,2200)) spectra.processed.B <- process_monospectra( file=system.file("extdata", "listB.txt", package="MGMS2"), mass.range=c(1000,2200)) spectra.processed.C <- process_monospectra( file=system.file("extdata", "listC.txt", package="MGMS2"), mass.range=c(1000,2200)) spectra.mono.summary.A <- summarize_monospectra( processed.obj=spectra.processed.A, species='A', directory=tempdir()) spectra.mono.summary.B <- summarize_monospectra( processed.obj=spectra.processed.B, species='B', directory=tempdir()) spectra.mono.summary.C <- summarize_monospectra( processed.obj=spectra.processed.C, species='C', directory=tempdir()) mono.info=gather_summary(c(spectra.mono.summary.A, spectra.mono.summary.B, spectra.mono.summary.C)) mixture.ratio <- list() mixture.ratio['A']=1 mixture.ratio['B']=0.5 mixture.ratio['C']=0 sim.template <- create_insilico_mixture_template(mono.info) insilico.spectrum <- simulate_poly_spectra(sim.template, mixture.ratio) merged.spectrum <- characterize_peak(insilico.spectrum, option=2) ```

characterize_peak function