CSA_fragmentationPeakDetection {IDSL.CSA}

CSA peakList MSP generation

Description

This function detects fragmentation peaks for the Composite Spectra Analysis (CSA) using IDSL.IPA peaklists.

Usage

CSA_fragmentationPeakDetection(CSA_hrms_address, CSA_hrms_file,
tempAlignedTableSubsetsFolder = NULL, peaklist, selectedIPApeaks = NULL,
RTtolerance, massError, minSNRbaseline, smoothingWindowMS1, scanTolerance, nSpline,
topRatioPeakHeight, minIonRangeDifference, minNumCSApeaks, pearsonRHOthreshold,
outputCSAeic = NULL)

Arguments

CSA_hrms_address

path to the HRMS file

CSA_hrms_file

CSA HRMS file

tempAlignedTableSubsetsFolder

tempAlignedTableSubsetsFolder

peaklist

IDSL.IPA peaklist

selectedIPApeaks

A vector of selected IDSL.IPA peaks only when a number of IDSL.IPA peaks from one peaklist is processed. When 'NULL' is selected, the entire peaks in the peaklist are processed.

RTtolerance

retention time tolerance to detect common peaks

massError

Mass accuracy in Da

minSNRbaseline

A minimum baseline S/N threshold for IDSL.IPA pseudo-precursor m/z

smoothingWindowMS1

number of scans for peak smoothing.

scanTolerance

a scan tolerance to extend the chromatogram for better calculations.

nSpline

number of points for further smoothing using a cubic spline smoothing method to add more points to calculate Pearson correlation rho values

topRatioPeakHeight

The top percentage of the chromatographic peak to calculate Pearson correlation rho values

minIonRangeDifference

Minimum distance (Da) between lowest and highest m/z to prevent clustering isotopic envelopes

minNumCSApeaks

Minumum number of ions in a CSA cluster

pearsonRHOthreshold

Minimum threshold for Pearson correlation rho values

outputCSAeic

When 'NULL' CSA EICs are not plotted. 'outputCSAeic' represents an address to save CSA EICs figures.

Value

A dataframe peaklist of co-detected CSA analysis.

References

[1] Fakouri Baygi, S., Kumar, Y., Barupal, D.K. (2022). IDSL.IPA Characterizes the Organic Chemical Space in Untargeted LC/HRMS Data Sets. Journal of Proteome Research, 21(6), 1485-1494, doi:10.1021/acs.jproteome.2c00120

[2] Fakouri Baygi, S., Fernando, S., Hopke, P.K., Holsen, T.M., Crimmins, B.S. (2021). Nontargeted discovery of novel contaminants in the Great Lakes region: A comparison of fish fillets and fish consumers. Environmental Science & Technology, 55(6), 3765-3774, doi:10.1021/acs.est.0c08507