Class DiffExAnalyzerUtils
- java.lang.Object
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- ubic.gemma.core.analysis.expression.diff.DiffExAnalyzerUtils
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public class DiffExAnalyzerUtils extends Object
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Constructor Summary
Constructors Constructor Description DiffExAnalyzerUtils()
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static BioAssayDimension
createBADMap(List<BioMaterial> columnsToUse)
This bioAssayDimension shouldn't get persisted; it is only for dealing with subset diff ex. analyses.static AnalysisType
determineAnalysisType(BioAssaySet bioAssaySet, Collection<ExperimentalFactor> experimentalFactors, ExperimentalFactor subsetFactor, boolean includeInteractionsIfPossible)
Determines the analysis to execute based on the experimental factors, factor values, and block design.static AnalysisType
determineAnalysisType(BioAssaySet bioAssaySet, DifferentialExpressionAnalysisConfig config)
FIXME this should probably deal with the case of outliers and also theLinearModelAnalyzer
's EXCLUDE_CHARACTERISTICS_VALUESstatic DoubleMatrix<String,String>
makeDataMatrix(ObjectMatrix<String,String,Object> designMatrix, DoubleMatrix<CompositeSequence,BioMaterial> namedMatrix)
Convert the data into a string-keyed matrix.static String
nameForR(CompositeSequence cs)
static void
populateFactorValuesFromBASet(BioAssaySet ee, ExperimentalFactor f, Collection<FactorValue> fvs)
static void
writeConfig(DifferentialExpressionAnalysisConfig config, Writer writer)
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Method Detail
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createBADMap
public static BioAssayDimension createBADMap(List<BioMaterial> columnsToUse)
This bioAssayDimension shouldn't get persisted; it is only for dealing with subset diff ex. analyses.- Parameters:
columnsToUse
- columns to use- Returns:
- bio assay dimension
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populateFactorValuesFromBASet
public static void populateFactorValuesFromBASet(BioAssaySet ee, ExperimentalFactor f, Collection<FactorValue> fvs)
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makeDataMatrix
public static DoubleMatrix<String,String> makeDataMatrix(ObjectMatrix<String,String,Object> designMatrix, DoubleMatrix<CompositeSequence,BioMaterial> namedMatrix)
Convert the data into a string-keyed matrix. Assumes that the row names of the designMatrix are concordant with the column names of the namedMatrix
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nameForR
public static String nameForR(CompositeSequence cs)
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determineAnalysisType
public static AnalysisType determineAnalysisType(BioAssaySet bioAssaySet, DifferentialExpressionAnalysisConfig config)
FIXME this should probably deal with the case of outliers and also theLinearModelAnalyzer
's EXCLUDE_CHARACTERISTICS_VALUES- Returns:
- selected type of analysis such as t-test, two-way ANOVA, etc.
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determineAnalysisType
public static AnalysisType determineAnalysisType(BioAssaySet bioAssaySet, Collection<ExperimentalFactor> experimentalFactors, @Nullable ExperimentalFactor subsetFactor, boolean includeInteractionsIfPossible)
Determines the analysis to execute based on the experimental factors, factor values, and block design.FIXME: this should probably deal with the case of outliers and also the
LinearModelAnalyzer
's EXCLUDE_CHARACTERISTICS_VALUES- Parameters:
bioAssaySet
- experiment or subset to determine the analysis type forexperimentalFactors
- which factors to use, or null if to use all from the experimentsubsetFactor
- can be nullincludeInteractionsIfPossible
- include interactions among the provided experimental factors if possible- Returns:
- an appropriate analysis type
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writeConfig
public static void writeConfig(DifferentialExpressionAnalysisConfig config, Writer writer) throws IOException
- Throws:
IOException
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