|  Concept | OpenMS concepts (types, macros, ...) | 
|   Class test macros | These macros are used by the test programs in the subdirectory OpenMS/source/TEST | 
|   Exceptions | Exceptions | 
|   Condition macros | Macros used for to enforce preconditions and postconditions | 
|  System | Very vasic functionality like file system or stopwatch | 
|  Datastructures | Auxilary datastructures | 
|  Math | Math functions and classes | 
|   Statistics functions | Various statistical functions | 
|   Misc functions | Math functions | 
|  Kernel | Kernel datastructures | 
|   ComparatorUtils | A collection of utilities for comparators | 
|   RangeUtils | Predicates for range operations | 
|  Format | IO classes | 
|   File IO | File IO classes | 
|   Database IO | Database IO classes | 
|  Metadata | Classes that capture meta data about a MS or HPLC-MS experiment | 
|  Chemistry |  | 
|  Spectrum Comparison | The classes within this group are used to compare single spectra, by reporting a similarity value | 
|  Spectrum filters | This group contains filtering classes for spectra | 
|   Spectra Preprocessors | The spectra preprocessors filter the spectra with different criterions | 
|   Spectra Filters | Spectra filters report single values of spectra e.g. the TIC | 
|   Peak Marker | These classes mark peaks according to different criterions | 
|  Analysis | High-level analysis like PeakPicking, Quantitation, Identification, MapAlginment | 
|   SignalProcessing | Signal processing classes (noise estimation, noise filters, basline filters) | 
|   PeakPicking | Classes for the transformation of raw ms data into peak data | 
|   FeatureFinder | The feature detection algorithms | 
|   MapAlignment | The map alignment algorithms | 
|   FeatureGrouping | The feature grouping | 
|   Identification | Protein and peptide identitfication classes | 
|   Clustering | This class contains SpectraClustering classes These classes are components for clustering all kinds of data for which a distance relation, normalizable in the range of [0,1], is available. Mainly this will be data for which there is a corresponding CompareFunctor given (e.g. PeakSpectrum) that is yielding the similarity normalized in the range of [0,1] of such two elements, so it can easily converted to the needed distances | 
|  Visual | Visualization classes | 
|   Spectrum visualizaion widgets | Spectrum visualization widgets | 
|   TOPPView | GUI elements for TOPPView | 
|   TOPPAS | GUI elements for TOPPAS | 
|   Dialogs | Dialogs for user interaction | 
|  Simulation | Simulation classes |