procope.methods.scores.bootstrap
Class Bootstrap

java.lang.Object
  procope.methods.scores.bootstrap.Bootstrap

public class Bootstrap
extends Object

Contains helper methods for the calculation of protein interaction scores using the Bootstrap approach according to

Caroline C. Friedel, Jan Krumsiek, Ralf Zimmer
Bootstrapping the Interactome: Unsupervised Identification of Protein Complexes in Yeast.
RECOMB 2008, LNBI 4955, pp. 3-16.

This class is not instantiatable.

Method Summary

static ProteinNetwork	createBootstrapNetwork(Collection<ComplexSet> clusterings) Creates the bootstrap network for a given set of clusterings.
static ArrayList<ComplexSet>	extractOptimalClusterings(ArrayList<BootstrapClusterings> clusteringLists, int optimalIndex) Extracts all clusterings at a given index of the clustering lists.
static int	findBestIndex(ArrayList<BootstrapClusterings> clusteringsOnlyEff) Finds the index of the clusterings with the best average efficiency in the set.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

extractOptimalClusterings

public static ArrayList<ComplexSet> extractOptimalClusterings(ArrayList<BootstrapClusterings> clusteringLists,
                                                              int optimalIndex)

Extracts all clusterings at a given index of the clustering lists.

Parameters:

clusteringLists - set of clusterings

optimalIndex - index in each clustering list to be extracted

Returns:

set of clusterings with the given inflation coefficient

createBootstrapNetwork

public static ProteinNetwork createBootstrapNetwork(Collection<ComplexSet> clusterings)

Creates the bootstrap network for a given set of clusterings. The weights of the edges in this network represent the frequency of cooccurence of two proteins in the given set of clusterings. For instance, if two proteins appear in the same complex in 60% of the clusterings, their edge gets a weight of 0.6

Parameters:

clusterings - set of clusterings for which the boostrap network is calculated

Returns:

bootstrap network for the given clusterings

findBestIndex

public static int findBestIndex(ArrayList<BootstrapClusterings> clusteringsOnlyEff)

Finds the index of the clusterings with the best average efficiency in the set. Note that all clustering lists must contain the same number of clusterings produced by the same parameters.

Note: The clustering objects do not have to contain actual clusterings, inflation coefficient and efficiency are enough. See also: BootstrapClusterings.BootstrapClusterings(String, boolean)

Parameters:

clusteringsOnlyEff - clusterings list from which the best inflation coeffient is determined

Returns:

index of clusterings with best average efficiency