A C D E G H I K M P R T

A

absorbCluster(Cluster) - Method in class Cluster

Adds all genes in the specified Cluster to this Cluster.

addGene(Gene) - Method in class Cluster

Adds the specified Gene to this Cluster.

addGenesWithHighAffinity(Cluster) - Method in class CAST_Clustering

Adds to the specified Cluster all unassigned genes that are closer to the genes in the Cluster, on average, than the affinity threshold.

assignGenesToClusters(Vector<Vector<Double>>) - Method in class KMeans_Clustering

Assigns each gene to the cluster whose mean expression vector is closest to the gene.

C

cast() - Method in class CAST_Clustering

Performs CAST clustering.

CAST_Clustering - Class in <Unnamed>

An instance of the CAST_Clustering class represents a clustering (i.e., grouping or partitioning) of a collection of genes using the CAST (cluster affinity search technique) clustering method.

CAST_Clustering(String, double) - Constructor for class CAST_Clustering

Creates an initially empty CAST_Clustering.

Cluster - Class in <Unnamed>

An instance of the Cluster class represents a group of genes.

Cluster() - Constructor for class Cluster

Creates a Cluster initially containing zero genes.

Clustering - Class in <Unnamed>

An instance of the Clustering class represents a clustering (i.e., grouping or partitioning) of a collection of genes.

Clustering(String) - Constructor for class Clustering

Creates an initially empty Clustering.

clusters - Variable in class Clustering

A collection of clusters

D

distanceToExpressionVector(Vector<Double>) - Method in class Gene

Returns the Euclidean distance between this Gene's expression values and the specified collection of expression values.

E

experiments - Variable in class Clustering

A collection of experiment names

G

Gene - Class in <Unnamed>

An instance of the Gene class represents (1) the name of a gene (2) the reported function of the gene and (3) the gene's expression values from a set of experiments.

Gene(String) - Constructor for class Gene

Creates a Gene from a tab-delimited String.

genes - Variable in class Clustering

A collection of genes

getClusterMean() - Method in class Cluster

Returns the mean (i.e., average) of the expression vectors of all Genes in this Cluster.

getDistanceToCluster(Cluster) - Method in class Cluster

Computes and returns the distance between this Cluster and the specified Cluster.

getExperimentNamesFromFile(String) - Method in class Clustering

Returns a collection of experiment names for which there is data in the specified file.

getExpressionInOneExperiment(int) - Method in class Gene

Returns the expression value of this Gene in the specified experiment.

getExpressionVector() - Method in class Gene

Returns a copy of this Gene's expression values in all experiments.

getGene(int) - Method in class Cluster

Returns a Gene in this Cluster.

getGeneFunction() - Method in class Gene

Returns a String representation of the gene's function.

getGeneInformationFromFile(String) - Method in class Clustering

Returns a collection of Genes based on data in the specified file.

getGeneName() - Method in class Gene

Returns a String representation of the gene's name.

getMeansOfAllClusters() - Method in class KMeans_Clustering

Return a collection of the mean (average) expression vectors for all of the clusters.

getNumClusters() - Method in class Clustering

Returns the number of clusters in this Clustering.

getNumExperiments() - Method in class Clustering

Returns the number of experiments in this Clustering.

getNumGenes() - Method in class Clustering

Returns the total number of genes in this Clustering.

getSizeOfCluster() - Method in class Cluster

Returns the number of genes in this Cluster.

H

hierarchical() - Method in class Hierarchical_Clustering

Performs centroid-linkage hierarchical clustering.

Hierarchical_Clustering - Class in <Unnamed>

An instance of the Hierarchical_Clustering class represents a clustering (i.e., grouping or partitioning) of a collection of genes using the centroid-linkage hierarchical clustering method.

Hierarchical_Clustering(String, int) - Constructor for class Hierarchical_Clustering

Creates an initially empty Hierarchical_Clustering.

I

initialize() - Method in class Cluster

Clears all genes from this Cluster so that it contains zero genes.

initializeAllClusters() - Method in class KMeans_Clustering

Initializes each cluster so that each cluster contains zero genes.

initiallyAssignOneGeneToEachCluster() - Method in class Hierarchical_Clustering

Assigns each gene to its own unique cluster.

isGeneInCluster(Gene) - Method in class Cluster

Returns a boolean value indicating if the specified Gene is in this Cluster.

K

kMeans() - Method in class KMeans_Clustering

Performs k-means clustering.

KMeans_Clustering - Class in <Unnamed>

An instance of the KMeans_Clustering class represents a clustering (i.e., grouping or partitioning) of a collection of genes using the k-means clustering method.

KMeans_Clustering(String, int) - Constructor for class KMeans_Clustering

Creates an initially empty KMeans_Clustering.

M

main(String[]) - Static method in class CAST_Clustering

The main method creates a Clustering based on gene and experiment data from a tab-delimited text file.

main(String[]) - Static method in class Clustering

The main method creates an initially empty Clustering from a tab-delimited text file of gene and experiment data.

main(String[]) - Static method in class Hierarchical_Clustering

The main method creates a Clustering based on gene and experiment data from a tab-delimited text file.

main(String[]) - Static method in class KMeans_Clustering

The main method creates a Clustering based on gene and experiment data from a tab-delimited text file.

mergeTwoClosestClusters() - Method in class Hierarchical_Clustering

Identifies and merges together the two closest clusters.

P

populateEmptyClusters() - Method in class KMeans_Clustering

If any clusters are empty (contain zero genes), then genes are moved from clusters containing multiple genes.

R

randomlyAssignGenesToClusters() - Method in class KMeans_Clustering

Assigns each gene to a random cluster.

removeGene(Gene) - Method in class Cluster

Removes the specified Gene from this Cluster.

removeGenesWithLowAffinity(Cluster) - Method in class CAST_Clustering

Removes from the specified Cluster any genes that are farther from the genes in the Cluster, on average, than the affinity threshold.

T

toString() - Method in class Cluster

Returns a String representation of this Cluster.

toString() - Method in class Clustering

Returns a String representation of all Clusters in this Clustering.

toString() - Method in class Gene

Returns a String representation of this Gene, including the gene's name and function.

A C D E G H I K M P R T