Based on the features found during the Feature detection, quantitation can be performed. OpenMS offers a number of feature grouping algorithms. The take one or several feature maps and group feature in one map or across maps, depending on the algorithm.
The classes described in this section can be found in the ANALYSIS/MAPMATCHING folder.
All feature grouping algorithms are derived from the common base class FeatureGroupingAlgorithm and, thus, share a common interface. Currently two algorithms are implemented. One for isotope-labeled experiments with two labels and another for label-free quantitation.
The first example shows the label-free quantitation (Tutorial_Unlabeled.C):
First, we load two feature maps:
In order to write the a valid output file, we need to set the input file names and sizes.
Then, we instanciate the algorithm and group the features:
Finally, we store the grouped features in a consensusXML file.
The second example shows the isotope-labeled quantitation (Tutorial_Labeled.C):
First, we load the feature map:
The isotope-labeled quantitation finds two types of features in the same map (heavy and light variant). So we add two map descriptions with the same file name to the output and set the labels accordingly:
Then, we instanciate the algorithm and group the features:
Finally, we store the grouped features in a consensusXML file. In order to write a valid file, we need to set the input file names and sizes.
OpenMS / TOPP release 1.9.0 | Documentation generated on Sun Oct 27 2013 01:11:37 using doxygen 1.8.4 |