OpenMS
Analysis

High-level analysis like PeakPicking, Quantitation, Identification, MapAlignment. More...

Collaboration diagram for Analysis:

Modules

 SignalProcessing
 Signal processing classes (noise estimation, noise filters, baseline 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 identification 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.
 

Classes

class  FeatureDeconvolution
 An algorithm to decharge features (i.e. as found by FeatureFinder). More...
 
class  MetaboliteFeatureDeconvolution
 An algorithm to decharge small molecule features (i.e. as found by FeatureFinder). More...
 
class  PeakIntensityPredictor
 Predict peak heights of peptides based on Local Linear Map model. More...
 

Detailed Description

High-level analysis like PeakPicking, Quantitation, Identification, MapAlignment.