procope.evaluation.networkperformance
Class ROC

java.lang.Object
  extended by procope.evaluation.networkperformance.ROC

public class ROC
extends Object

Contains static methods to calculate ROC curves for protein networks. These ROC curves are a measure for the performance of a network, a reference complex set is needed for calculation.

For a detailed description of the ROC curve calcuation process, please read the documentation of ProCope.

Author:
Jan Krumsiek

Method Summary
static List<ROCCurve> calculateROCCurves(List<ProteinNetwork> scoreNetworks, ComplexSet reference, ComplexSet referenceForNegativeSet, LocalizationData locData, boolean restrictToNetworkProteins)
          Calculate the ROC curves for a given set of networks.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Method Detail

calculateROCCurves

public static List<ROCCurve> calculateROCCurves(List<ProteinNetwork> scoreNetworks,
                                                ComplexSet reference,
                                                ComplexSet referenceForNegativeSet,
                                                LocalizationData locData,
                                                boolean restrictToNetworkProteins)
Calculate the ROC curves for a given set of networks. Can use a different complex set for the identification

Parameters:
scoreNetworks - list of networks for which the ROC curves will be calculated
reference - reference set to be used
referenceForNegativeSet - reference set used to sample the set of true negatives, may be set to null to use the same set as the reference set
locData - localization data, use null if you do not want to use localization data for negative set generation
restrictToNetworkProteins - Determines whether the positive and negative sets may only contain edges, where both proteins are contained in at least one of the score networks. If this is set to false, the true-positive rate probably does not converge against 1.0.
Returns:
list of ROC curves for the given networks