| adaptive.bin | Adaptive binning |
| adaptive.bin.2 | Adaptive binning specifically for the machine learning... |
| adduct.table | A table of potential adducts. |
| adjust.time | Adjust retention time across spectra. |
| aligned | sample data after alignment |
| aligned.learn | sample data after alignment, processed by the machine... |
| apLCMS | Adaptive processing of LC/MS data |
| apLCMS-package | Adaptive processing of LC/MS data |
| cdf.to.ftr | Convert a number of cdf files in the same directory to a... |
| cont.index | Continuity index |
| eic.disect | Internal function: Extract data feature from EIC. |
| EIC.plot | Plot extracted ion chromatograms |
| EIC.plot.learn | Plot extracted ion chromatograms based on the machine... |
| eic.pred | Internal function: calculate the score for each EIC based on... |
| 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 |
| features2 | Feature tables after elution time correction. |
| features2.learn | Feature tables after elution time correction. The original... |
| features.learn | Sample feature tables from 4 profiles. The original feature... |
| find.match | Internal function: finding the best match between a set of... |
| find.tol | An internal function that is not supposed to be directly... |
| find.tol.time | An internal function that is not supposed to be directly... |
| find.turn.point | Find peaks and valleys of a curve. |
| interpol.area | Interpolate missing intensities and calculate the area for a... |
| known.table.common.pos | A known feature table based on HMDB. |
| known.table.hplus | A known feature table based on HMDB. |
| 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... |
| mass.match | An internal function: finding matches between two vectors of... |
| merge.seq.3 | An internal function. |
| metabolite.table | A known metabolite table based on HMDB. |
| new.aligned | Feature data after alignment and weak signal recovery |
| new.aligned.learn | Feature data after alignment and weak signal recovery. The... |
| peak.characterize | Internal function: Updates the information of a feature for... |
| 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.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.learn | Sample profile data after noise filtration by the machine... |
| prof.to.features | Generate feature table from noise-removed LC/MS profile |
| recovered | Sample data after weak signal recovery |
| recovered.learn | Sample data after weak signal recovery. The original peak... |
| recover.weaker | Recover weak signals in some profiles that is not identified... |
| rm.ridge | Removing long ridges at the same m/z. |
| semi.sup | Semi-supervised feature detection |
| semi.sup.learn | Semi-supervised feature detection using machine learning... |
| target.search | Targeted search of metabolites with given m/z and (optional)... |
| two.step.hybrid | Two step hybrid feature detection. |
