org.metaqtl.algo
Class QtlClustAlgorithm
java.lang.Object
org.metaqtl.algo.MetaAlgorithm
org.metaqtl.algo.ClustAlgorithm
org.metaqtl.algo.QtlClustAlgorithm
- All Implemented Interfaces:
- IMetaAlgorithm
public class QtlClustAlgorithm
- extends ClustAlgorithm
This class defines methods to perform a QTL meta-analysis
on a genetic map by applying a clustering of QTL
based on a gaussian mixture model and the EM-algorihtm.
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
QtlClustAlgorithm
public QtlClustAlgorithm(IBioGenome map,
IBioOntology ontology)
- Parameters:
map
- ontology
-
QtlClustAlgorithm
public QtlClustAlgorithm(IBioGenome map,
java.lang.String chrom,
IBioOntology ontology)
run
public void run()
- This method performs a QTL meta-analysis on each chromosome
of the given map. For each chromosome all the possible
QTL cluster combinations are tested and the results are
added to the chromosome. Then the method returns the array
of chromosomes for which the meta-analysis has been performed.
doQtlClustering
public MetaQtlResult[] doQtlClustering(MetaQtlData data)
- For a given data set
data
performs the clustering
on each trait group and returns the results as an array of
MetaQtlResult
objects.
- Parameters:
data
- the data set.
- Returns:
- the results of teh clustering.
- See Also:
MetaQtlData
,
MetaQtlResult
setMaxClusterNumber
public void setMaxClusterNumber(int nmax)
- Parameters:
nmax
- the maximum number of clusters to test.
getEMRanStartNumber
public int getEMRanStartNumber()
- Returns:
- Returns the number of random starting points.
setEMRanStartNumber
public void setEMRanStartNumber(int n)
- Parameters:
n_em_start
- The n_em_start to set.
getEMEps
public double getEMEps()
- Returns:
- Returns the convergence error for the EM.
setEMEps
public void setEMEps(double epsilon)
- Parameters:
em_err
- The em_err to set.