Interface OutlierDetectionService
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- All Known Implementing Classes:
OutlierDetectionServiceImpl
public interface OutlierDetectionService
- Author:
- paul
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description Collection<OutlierDetails>
getOutlierDetails(ExpressionExperiment ee)
Obtain existing outlier details from a previousidentifyOutliersByMedianCorrelation(ExpressionExperiment)
invocation.Collection<OutlierDetails>
identifyOutliersByMedianCorrelation(DoubleMatrix<BioAssay,BioAssay> cormat)
Identify outliers by sorting by median, then looking for non-overlap of first quartile-second quartile range This is exposed for efficiency in geeq score calculation, use this#identifyOutliers(ExpressionExperiment, boolean, boolean) to have the correlation matrix computed correctly for you.Collection<OutlierDetails>
identifyOutliersByMedianCorrelation(ExpressionExperiment ee)
Identify outliers by median correlation for the given dataset.
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Method Detail
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getOutlierDetails
@Nullable Collection<OutlierDetails> getOutlierDetails(ExpressionExperiment ee)
Obtain existing outlier details from a previousidentifyOutliersByMedianCorrelation(ExpressionExperiment)
invocation.- Returns:
- outlier details or
null
if none exist.
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identifyOutliersByMedianCorrelation
Collection<OutlierDetails> identifyOutliersByMedianCorrelation(ExpressionExperiment ee)
Identify outliers by median correlation for the given dataset.- Parameters:
ee
- The experiment to identify sample outliers in.- Returns:
- the information about the identified outliers.
- See Also:
identifyOutliersByMedianCorrelation(DoubleMatrix)
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identifyOutliersByMedianCorrelation
Collection<OutlierDetails> identifyOutliersByMedianCorrelation(DoubleMatrix<BioAssay,BioAssay> cormat)
Identify outliers by sorting by median, then looking for non-overlap of first quartile-second quartile range This is exposed for efficiency in geeq score calculation, use this#identifyOutliers(ExpressionExperiment, boolean, boolean) to have the correlation matrix computed correctly for you.- Parameters:
cormat
- the correlation matrix to identify outliers in.- Returns:
- the information about the identified outliers.
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