LCMSQA-package {LCMSQA}

LC/MS Quality Assessment

Description

The 'LCMSQA' package is designed to assess the quality of liquid chromatography/mass spectrometry (LC/MS) experiment using a user-friendly web application built with the R package 'shiny'. It utilizes the R package 'xcms' workflow for data import, visualization, and quality check of LC/MS experiments.

The application consists of four main tabs:

• Total Ion Chromatogram (and Base Peak Chromatogram)

• Extracted Ion Chromatogram (XIC)

• Mass Spectrum

• Metabolic Feature Detection

Please check the vignette for the details (Run vignette("LCMSQA", package = "LCMSQA")).

Details

The application needs the following inputs:

• (required) mass-spectrometry data files of quality control (QC) samples in open formats: AIA/ANDI NetCDF, mzXML, mzData and mzML.

• (optional) internal standard information in a CSV format with the columns:

  • compound: the name of compound

  • adduct: adduct type (e.g., [M+H]+)

  • mode: must be either "positive" or "negative"

  • mz: a known mass-to-charge ratio (m/z) value

In the application UI, a user can tune the following parameters:

• Set m/z and retention time of interest

  • compound (or m/z) with a ppm tolerance

  • retention time in second (min, max)

• Peak picking using the centWave method (see xcms::CentWaveParam)

  • ppm: the maximal tolerated m/z deviation in consecutive scans in ppm for the initial region of interest (ROI) definition

  • peak width: the expected approximate peak width in chromatographic space

  • signal/noise cut: the signal to noise ratio cutoff

  • m/z diff: the minimum difference in m/z dimension required for peaks with overlapping retention times

  • noise: a minimum intensity required for centroids to be considered in the first analysis step

  • prefilter (>= peaks, >= intensity): the prefilter step for the first analysis step (ROI detection)

  • Gaussian fit: whether or not a Gaussian should be fitted to each peak

  • m/z center: the function to calculate the m/z center of the chromatographic peaks

  • integration: whether or not peak limits are found through descent on the Mexican Hat filtered data

• Peak grouping using the peak density method (see xcms::PeakDensityParam)

  • bandwidth: the bandwidth (standard deviation of the smoothing kernel) to be used

  • min fraction: the minimum fraction of samples in which the peaks has to be detected to define a peak group

  • bin size: the size of overlapping slices in m/z dimension

Author(s)

Maintainer: Jaehyun Joo [e-mail]

Authors:

• Blanca Himes