Interface SampleCoexpressionAnalysisService
- All Known Implementing Classes:
SampleCoexpressionAnalysisServiceImpl
public interface SampleCoexpressionAnalysisService
- Author:
- Paul
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Method Summary
Modifier and TypeMethodDescriptioncompute
(ExpressionExperiment ee, PreparedCoexMatrices matrices) Computes sample correlation matrices for the given experiment.boolean
Loads the analysis containing the coexpression matrices for the given experiment and converts the regressed coexpression matrix into a double matrix.Loads the analysis containing the coexpression matrices for the given experiment and converts the full (non-regressed) coexpression matrix into a double matrix.Load the regressed coexpression matrix for the given experiment.void
Removes all coexpression matrices for the given experiment.
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Method Details
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loadFullMatrix
Loads the analysis containing the coexpression matrices for the given experiment and converts the full (non-regressed) coexpression matrix into a double matrix. If the analysis or the matrix does not exist, computes it.- Parameters:
ee
- the experiment to load the raw coexpression matrix for.- Returns:
- the full, non-regressed matrix. If the matrix is not available event after attempted computation, returns null.
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loadRegressedMatrix
Load the regressed coexpression matrix for the given experiment.- Returns:
- the regressed matrix if available, null might indicate that the is either no analysis or no regressed
matrix, use
hasAnalysis(ExpressionExperiment)
to tell these apart.
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loadBestMatrix
Loads the analysis containing the coexpression matrices for the given experiment and converts the regressed coexpression matrix into a double matrix. If the analysis or the matrix does not exist, computes it. If there are problems loading or computing the regressed matrix (e.g. because the experiment has no experimental design), the full matrix is returned instead.- Parameters:
ee
- the experiment to load the regressed coexpression matrix for.- Returns:
- sample correlation matrix with major factors regressed out, if such matrix exists for the given experiment. If not, the full non-regressed matrix is returned. If no matrix is available event after attempted computation, returns null.
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retrieveExisting
@Transactional(readOnly=true) @Nullable DoubleMatrix<BioAssay,BioAssay> retrieveExisting(ExpressionExperiment ee) -
prepare
@Transactional(readOnly=true) PreparedCoexMatrices prepare(ExpressionExperiment ee) throws FilteringException - Throws:
FilteringException
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compute
@Transactional(isolation=SERIALIZABLE) DoubleMatrix<BioAssay,BioAssay> compute(ExpressionExperiment ee, PreparedCoexMatrices matrices) Computes sample correlation matrices for the given experiment. If the experiment already has any, they are removed. SeeSampleCoexpressionAnalysis
for the description of the matrices that are computed.- Parameters:
ee
- the experiment to create a sample correlation matrix for.- Returns:
- the regressed coexpression matrix if available, otherwise the full
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hasAnalysis
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removeForExperiment
Removes all coexpression matrices for the given experiment.- Parameters:
ee
- the experiment to remove the analysis for.
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