Adaptive Processing of LC-MS Data
Adaptive binning specifically for the machine learning approach.
Adaptive binning
Adjust retention time across spectra.
Adaptive processing of LC/MS data
Convert a number of cdf files in the same directory to a feature table
Continuity index
Internal function: Extract data feature from EIC.
Plot extracted ion chromatograms based on the machine learning method ...
Plot extracted ion chromatograms
Internal function: calculate the score for each EIC based on predictio...
Internal function: Calculate the single predictor quality.
Align peaks from spectra into a feature table.
Internal function: finding the best match between a set of detected fe...
An internal function that is not supposed to be directly accessed by t...
An internal function that is not supposed to be directly accessed by t...
Find peaks and valleys of a curve.
Interpolate missing intensities and calculate the area for a single EI...
Peak detection using the machine learning approach.
Loading LC/MS data.
Producing a table of known features based on a table of metabolites an...
An internal function: finding matches between two vectors of m/z value...
An internal function.
Internal function: Updates the information of a feature for the known ...
Plot the data in the m/z and retention time plane.
Plot the data in the m/z and retention time plane.
Generates 3 dimensional plots for LCMS data.
Compute a 2D Binned Kernel Density Estimate from LC/MS data in CDF for...
Filter noise and detect peaks from LC/MS data in CDF format
Filter noise and detect peaks from LC/MS data in text format
Generate feature table from noise-removed LC/MS profile
Recover weak signals in some profiles that is not identified as a peak...
Removing long ridges at the same m/z.
Semi-supervised feature detection using 2D peak detection
Semi-supervised feature detection using machine learning approach.
Semi-supervised feature detection
Targeted search of metabolites with given m/z and (optional) retention...
Two step hybrid feature detection using 2D peak detection.
Two step hybrid feature detection.
Provides methods for the processing of liquid chromatography-mass spectrometry (LC/MS) based metabolomics data, including adaptive tolerance level searching, non-parametric intensity grouping, the use of run filter to preserve weak signals, model-based estimation of peak intensities, and peak detection based on existing knowledge. Related references include Yu et al. (2009) <doi:10.1093/bioinformatics/btp291>, Liu et al. (2020) <doi:10.1038/s41598-020-70850-0>, Yu et al. (2014) <doi:10.1093/bioinformatics/btu430>, Yu et al. (2013) <doi:10.1021/pr301053d>.