org.fhcrc.cpl.toolbox.proteomics
Class ProteomicsRegressionUtilities

java.lang.Object
  org.fhcrc.cpl.toolbox.proteomics.ProteomicsRegressionUtilities

public class ProteomicsRegressionUtilities
extends java.lang.Object

Utilities for regression analysis specific to msInspect -- mostly making use of Feature. These utilities were originally in the class that became toolbox.RegressionUtilities

Field Summary

protected static org.apache.log4j.Logger	_log
static int	DEFAULT_REGRESSION_MODE
static int	REGRESSION_MODE_SCAN
static int	REGRESSION_MODE_TIME

Constructor Summary

ProteomicsRegressionUtilities()

Method Summary

static double[]	calculateStudentizedResiduals(double[] xValues, double[] yValues) Calculate studentized residuals
static double[]	modalRegressionIterateDegree(double[] xset, double[] yset, int maxDegree, double leverageNumerator, double maxStudentizedResidual, boolean showCharts)
static java.util.List<Feature>	selectFeaturesWithLowAbsMassLeverage(Feature[] features, float maxLeverage) Select low-leverage features, where leverage is defined by mass
static Feature[]	selectFeaturesWithLowAbsoluteSomething(Feature[] allFeatures, double[] somethings, double maxSomething)
static Feature[]	selectFeaturesWithLowLeverage(Feature[] allFeatures, double leverageNumerator, int scanOrTimeMode) return an array containing the subset of the allFeatures array in which all features have leverage < leverageNumerator/n Used in AmtDatabaseBuilder, and possibly also in selecting MS1 features with no embedded MS2 for matching
static Feature[]	selectFeaturesWithLowLeverageAndOrStudentizedResidual(Feature[] features, double[] xValues, double[] yValues, double leverageNumerator, double maxStudentizedResidual, boolean modalRegression, int degree, boolean keepHighLeverage, boolean showCharts)
static Feature[]	selectFeaturesWithLowLeverageAndStudentizedResidual(Feature[] features, double[] xValues, double[] yValues, double leverageNumerator, double maxStudentizedResidual, boolean modalRegression, int degree, boolean showCharts)
static Feature[]	selectFeaturesWithLowStudentizedResidual(Feature[] features, double[] xValues, double[] yValues, double leverageNumerator, double maxStudentizedResidual, boolean modalRegression, int degree, boolean showCharts)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

_log

protected static org.apache.log4j.Logger _log

REGRESSION_MODE_SCAN

public static final int REGRESSION_MODE_SCAN

See Also:

Constant Field Values

REGRESSION_MODE_TIME

public static final int REGRESSION_MODE_TIME

See Also:

Constant Field Values

DEFAULT_REGRESSION_MODE

public static final int DEFAULT_REGRESSION_MODE

See Also:

Constant Field Values

Constructor Detail

ProteomicsRegressionUtilities

public ProteomicsRegressionUtilities()

Method Detail

modalRegressionIterateDegree

public static double[] modalRegressionIterateDegree(double[] xset,
                                                    double[] yset,
                                                    int maxDegree,
                                                    double leverageNumerator,
                                                    double maxStudentizedResidual,
                                                    boolean showCharts)
                                             throws java.io.IOException

Throws:

java.io.IOException

selectFeaturesWithLowLeverage

public static Feature[] selectFeaturesWithLowLeverage(Feature[] allFeatures,
                                                      double leverageNumerator,
                                                      int scanOrTimeMode)

return an array containing the subset of the allFeatures array in which all features have leverage < leverageNumerator/n Used in AmtDatabaseBuilder, and possibly also in selecting MS1 features with no embedded MS2 for matching

Parameters:

allFeatures -

leverageNumerator -

scanOrTimeMode -

Returns:

selectFeaturesWithLowAbsoluteSomething

public static Feature[] selectFeaturesWithLowAbsoluteSomething(Feature[] allFeatures,
                                                               double[] somethings,
                                                               double maxSomething)

selectFeaturesWithLowLeverageAndStudentizedResidual

public static Feature[] selectFeaturesWithLowLeverageAndStudentizedResidual(Feature[] features,
                                                                            double[] xValues,
                                                                            double[] yValues,
                                                                            double leverageNumerator,
                                                                            double maxStudentizedResidual,
                                                                            boolean modalRegression,
                                                                            int degree,
                                                                            boolean showCharts)

selectFeaturesWithLowStudentizedResidual

public static Feature[] selectFeaturesWithLowStudentizedResidual(Feature[] features,
                                                                 double[] xValues,
                                                                 double[] yValues,
                                                                 double leverageNumerator,
                                                                 double maxStudentizedResidual,
                                                                 boolean modalRegression,
                                                                 int degree,
                                                                 boolean showCharts)

selectFeaturesWithLowAbsMassLeverage

public static java.util.List<Feature> selectFeaturesWithLowAbsMassLeverage(Feature[] features,
                                                                           float maxLeverage)

Select low-leverage features, where leverage is defined by mass

Parameters:

features -

maxLeverage -

Returns:

calculateStudentizedResiduals

public static double[] calculateStudentizedResiduals(double[] xValues,
                                                     double[] yValues)

Calculate studentized residuals

Parameters:

xValues -

yValues -

Returns:

selectFeaturesWithLowLeverageAndOrStudentizedResidual

public static Feature[] selectFeaturesWithLowLeverageAndOrStudentizedResidual(Feature[] features,
                                                                              double[] xValues,
                                                                              double[] yValues,
                                                                              double leverageNumerator,
                                                                              double maxStudentizedResidual,
                                                                              boolean modalRegression,
                                                                              int degree,
                                                                              boolean keepHighLeverage,
                                                                              boolean showCharts)