Peak_Detector: Peak_Detector
In Sautie/MALDITOFSpectraPA: Processing and analysis of MALDI_TOF spectra

Description Usage Arguments Details Value Examples

Peak_Detector is a pipeline of two stages for 1) import and processing of Maldi_Tof spectra and 2) peak detection

Peak_Detector(
  Dp,
  filein,
  fileout,
  keyCode = "Identifiant_MALDI",
  speColumn = "Taxonomie",
  t = "sqrt",
  smooth = "SavitzkyGolay",
  baseline = "SNIP",
  normalization = "TIC",
  Iter = 100,
  SN_R = 2,
  minFreq = 0.25,
  align = TRUE
)

`Dp:`	folder containing the ".mzXML" files,
`filein:`	metadata input csv file,
`fileout:`	output csv file,
`keyCode:`	code for dataframe joining (default value:"Identifiant_MALDI"),
`speColumn:`	taxonomic identification of isolate (default value, speColumn="Taxonomie"),
`t:`	spectrum transformation, (default value, t="sqrt"), "log"
`smooth:`	smoothing method, (default value smooth="SavitzkyGolay"), "MovingAverage", "WMovingAverage"
`baseline:`	baseline removing method, (default value, baseline="SNIP"), "TopHat", "ConvexHull"
`normalization:`	normalization algorithm (default value, normalization="TIC"), PQN
`Iter:`	number of iterations for baseline removing (default value, Iter=100)
`SN_R:`	signal_to_noise ratio (default value, SN_R=2),
`minFreq:`	the minimum peak frequency for spectrum selection (default value, minFreq=0.25),
`align:`	boolean Boolean parameter to indicate whether or not spectrum alignment is performed (default value, align=TRUE)

stage 1) import, check of quality, transformation, smoothing, baseline removing, normalization, and alignment of MALDI_TOF spectra

stage 2) peak detection, binning, filtering and merging with metadata ("Filtered_Meta.csv")

merged dataframes and csv file

1
2
3

 df_Peaks<-Peak_Detector("newdata", "Filtered_Meta.csv", "Filtered_Meta_Peaks.csv"),
           df_Peaks_0<-Peak_Detector("newdata", "Filtered_Meta.csv", "Filtered_Meta_Peaks_0.csv", minFreq=0, align=FALSE)
           df_PeaksTH<-Peak_Detector"newdata", "Filtered_Meta.csv", "Filtered_Meta_Peaks.csv", baseline="TopHat")