A D E G I M N R S

A

addPseudocountsToMatrix() - Method in class MotifSearch

Replaces values of 0.0 in the matrix (motif model) with small pseudocount values (0.0001).

D

determineMatrixModel() - Method in class EM_MotifSearch

The Maximization step in the EM algorithm.

determineMotifInstances() - Method in class EM_MotifSearch

The Expectation step in the EM algorithm.

determineMotifInstances() - Method in class Gibbs_MotifSearch

The Expectation step in the EM algorithm.

E

EM() - Method in class EM_MotifSearch

Executes the EM (Expectation Maximization) algorithm.

EM_MotifSearch - Class in <Unnamed>

An instance of the EM_MotifSearch class represents a search using the EM algorithm for a motif common to a set of genomic sequences.

EM_MotifSearch(String, int) - Constructor for class EM_MotifSearch

Creates an initially empty EM_MotifSearch.

G

getConsensusSequence() - Method in class MotifSearch

Returns the consensus sequence for the motif.

getIndexViaSampling(Vector<Double>) - Method in class Gibbs_MotifSearch

Returns the index of a randomly sampled value in a Vector.

getInformationContentOfMatrix() - Method in class EM_MotifSearch

Returns the information content associated with the matrix model.

getInstanceLocations() - Method in class MotifSearch

Returns a copy of the indices of start locations of motif instances in the sequences.

getMatrix() - Method in class MotifSearch

Returns a copy of the matrix that models the motif.

getNucleotideContent(char) - Method in class MotifSearch

Returns a double representing the frequency that the specified nucleotide character occurs in the genomic sequences.

getScoreForMotifInstance(String) - Method in class EM_MotifSearch

Given a candidate motif instance, returns the score (probability) of that instance based on the matrix model.

Gibbs_MotifSearch - Class in <Unnamed>

An instance of the Gibbs_MotifSearch class represents a search using the Gibbs sampling algorithm for a motif common to a set of genomic sequences.

Gibbs_MotifSearch(String, int) - Constructor for class Gibbs_MotifSearch

Creates an initially empty Gibbs_MotifSearch.

I

instanceLocations - Variable in class MotifSearch

A collection of integers where each integer represents the index of the start location of a motif instance in a genomic sequence

M

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

The main method generates an EM_MotifSearch for a motif of the specified length in the genomic sequences found in the specified FASTA file.

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

The main method generates a Gibbs_MotifSearch for a motif of the specified length in the genomic sequences found in the specified FASTA file.

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

The main method creates an initially empty MotifSearch for a motif of the specified length in the genomic sequences found in the specified FASTA file.

matrix - Variable in class MotifSearch

A 2D array corresponding to a position-specific scoring matrix (PSSM) that is a model of the motif being searched for

matrixToString() - Method in class MotifSearch

Returns a String representation of the matrix that models the motif.

motifInstancesToString() - Method in class MotifSearch

Returns a String representation of motif instances found in the genomic sequences.

motifLength - Variable in class MotifSearch

The length of the motif being search for

MotifSearch - Class in <Unnamed>

An instance of the MotifSearch class represents a search for a motif common to a set of genomic sequences.

MotifSearch(String, int) - Constructor for class MotifSearch

Creates an initially empty MotifSearch.

N

numSequences - Variable in class MotifSearch

The number of genomic sequences

R

run_EM_multiple_times(int) - Method in class EM_MotifSearch

Executes the EM (Expectation Maximization) algorithm multiple times.

S

sequences - Variable in class MotifSearch

A collection of genomic sequences

setRandomLocationsForMotifInstances() - Method in class EM_MotifSearch

The initial random seed step in the EM algorithm.

A D E G I M N R S