EIC.plot                Plot extracted ion chromatograms
EIC.plot.learn          Plot extracted ion chromatograms based on the
                        machine learning method output
adaptive.bin            Adaptive binning
adaptive.bin.2          Adaptive binning specifically for the machine
                        learning approach.
adduct.table            A table of potential adducts.
adjust.time             Adjust retention time across spectra.
apLCMS-package          Adaptive processing of LC/MS data
cdf.to.ftr              Convert a number of cdf files in the same
                        directory to a feature table
cont.index              Continuity index
eic.disect              Internal function: Extract data feature from
                        EIC.
eic.pred                Internal function: calculate the score for each
                        EIC based on prediction of match status.
eic.qual                Internal function: Calculate the single
                        predictor quality.
feature.align           Align peaks from spectra into a feature table.
features                Sample feature tables from 4 profiles
find.match              Internal function: finding the best match
                        between a set of detected features and a set of
                        known features.
find.tol                An internal function that is not supposed to be
                        directly accessed by the user. Find m/z
                        tolerance level.
find.tol.time           An internal function that is not supposed to be
                        directly accessed by the user. Find elution
                        time tolerance level.
find.turn.point         Find peaks and valleys of a curve.
interpol.area           Interpolate missing intensities and calculate
                        the area for a single EIC.
learn.cdf               Peak detection using the machine learning
                        approach.
load.lcms               Loading LC/MS data.
make.known.table        Producing a table of known features based on a
                        table of metabolites and a table of allowable
                        adducts.
mass.match              An internal function: finding matches between
                        two vectors of m/z values.
merge_seq_3             An internal function.
metabolite.table        A known metabolite table based on HMDB.
peak.characterize       Internal function: Updates the information of a
                        feature for the known feature table.
plot_cdf_2d             Plot the data in the m/z and retention time
                        plane.
plot_txt_2d             Plot the data in the m/z and retention time
                        plane.
present.cdf.3d          Generates 3 dimensional plots for LCMS data.
proc.cdf                Filter noise and detect peaks from LC/MS data
                        in CDF format
proc.cdf.2d             Compute a 2D Binned Kernel Density Estimate
                        from LC/MS data in CDF format.
proc.txt                Filter noise and detect peaks from LC/MS data
                        in text format
prof                    Sample profile data after noise filtration by
                        the run filter
prof.to.features        Generate feature table from noise-removed LC/MS
                        profile
recover.weaker          Recover weak signals in some profiles that is
                        not identified as a peak, but corresponds to
                        identified peaks in other spectra.
rm.ridge                Removing long ridges at the same m/z.
semi.sup                Semi-supervised feature detection
semi.sup.2d             Semi-supervised feature detection using 2D peak
                        detection
semi.sup.learn          Semi-supervised feature detection using machine
                        learning approach.
target.search           Targeted search of metabolites with given m/z
                        and (optional) retention time
two.step.hybrid         Two step hybrid feature detection.
two.step.hybrid.2d      Two step hybrid feature detection using 2D peak
                        detection.
