Public Member Functions
double	manhattanDistance (double[] x, double[] y)

Static Public Member Functions
static double	median (Collection< Double > list)

static double	median (double[] list)

static double	median (int[] list)

static double	quantile (List<?extends Number > list, double pct)

static double	quantile (double[] vals, double pct)

static double	mean (double[] values)

static double	mean (Matrix data)

static double	mean (Collection<?extends Number > values)

static double	average (Collection<?extends Number > values)

static double	average (double[] values)

static double	variance (double[] values)

static double	variance (double[] values, double mean)

static double	variance (List<?extends Number > values)

static double	variance (List<?extends Number > values, double mean)

static double	covariance (List<?extends Number > values1, List<?extends Number > values2, double mean1, double mean2)

static double	covariance (List<?extends Number > values1, List<?extends Number > values2)

static double	pearsonCorrelation (List<?extends Number > values1, List<?extends Number > values2)

static double	min (Collection< Double > vals)

static double	max (Collection< Double > vals)

static double	min (double[] vals)

static double	max (double[] vals)

static int	minInt (Collection< Integer > vals)

static int	maxInt (Collection< Integer > vals)

static int	min (int[] vals)

static int	max (int[] vals)

static double	metaAvg (Collection< double[]> data)

static double	sum (List< Double > vals)

static double	sum (double[] vals)

static double	tstat (List< Double > g1, List< Double > g2, double tstat_tuning_param)

static double	tstat (double[] g1, double[] g2, double tstat_tuning_param)

static double	diff (double[] g1, double[] g2)

static double	maxmean (double[] vals)

static double	pairedTStat (List< Double > g1, List< Double > g2)

static double	pairedTStat (double[] gr1, double[] gr2)

static double	stdev (Collection<?extends Number > values)

static double	stdev (double[] values)

static double	pearsonDistance (double[] x, double[] y)

static double	pearsonDistance (List< Double > xA, List< Double > yA)

static double	spearmanCorrelation (List< Double > xA, List< Double > yA)

static double	spearmanCorrelation (double[] x, double[] y)

static double	euclideanDistance (double[] x, double[] y)

static double	euclideanDistance (List< Double > x, List< Double > y)

static double	FDRCorrect (double[] pvals, double alpha)

static double	FDRCorrect (List< Double > pvals, double alpha)

static double	FDR (EmpiricalDistribution observedDist, EmpiricalDistribution[] randomDist, double x)

static double[]	hochbergPvalueAdjust (double[] pvals)

static double	pvalue (List< Double > data, double value, boolean isSorted)

static double	pvalue (double[] data, double value, boolean isSorted)

static double	pvalue (List< Double > data, double value)

static void	main (String[] args) throws Exception

static double	zScore (double observation, double[] controlObservations, double fudge_factor)

static double	zScore (double observation, double mean, double variance, int length)

static double	tstat (List< Double > g1, List< Double > g2)

static double	zScore (double observation, double[] controlObservations)

static double[]	computePermutedZScores (double observation, double[] controlObservations, double fudge_factor)

static double[]	computePermutedZScores (double observation, double[] controlObservations)

static double[]	rank (double[] vals, boolean ascending)

static double	absFold (Collection< Double > g1, Collection< Double > g2, boolean log)

static double	absFold (double[] g1, double[] g2, boolean log)

static double	fold (Collection< Double > g1, Collection< Double > g2, boolean log)

static double	fold (double[] g1, double[] g2, boolean log)

static double	fold (double[] g1, boolean log)

static double	medianCollection (Collection< Double > values)

static double	hypergeometric (int numberOfGenesTotal, int diffExpressedGenes, int genesInSet, int diffExpressedGenesInSet)

static double	MAD (double[] array)

static double	maxStdev (Matrix data)

static double	maxMAD (Matrix data)

static double	geometricMean (double[] vals)

static double	geometricMeanMAD (Matrix data)

static double	anovaFStat (Collection< double[]> lists)

static int[]	randomPermutation (int n)

static double[]	toDoubleArray (List< Double > lst)

static ArrayList< Double >	toDoubleArrayList (double[] intervalScores)

static ArrayList< Double >	toUniqueSortedList (ArrayList< Double > List)

static Matrix	absoluteValue (Matrix permutations)

static double[]	absoluteValue (double[] observed)

static double	entropy (double[] p_vec)

static double	hamming (double[] x, double[] y, double threshold)

static double	hamming (List< Double > x, List< Double > y, double threshold)

static Double	JSDist (double[] p1, double[] p2)

static double[]	normalizeToRelativeAbundance (double[] vals)

static double	zscoreToPvalue (double zscore)

static double	zScore2 (double observation, double[] controlObservations)

static double	getKSStatistic (double[] observed, double[] expected)

Static Public Attributes
static final String	USAGE

Member Function Documentation

static double broad.core.math.Statistics.absFold	(	Collection< Double >	g1,
		Collection< Double >	g2,
		boolean	log
	)

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static double broad.core.math.Statistics.absFold	(	double[]	g1,
		double[]	g2,
		boolean	log
	)

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static Matrix broad.core.math.Statistics.absoluteValue ( Matrix permutations )

static

static double [] broad.core.math.Statistics.absoluteValue ( double[] observed )

static

static double broad.core.math.Statistics.anovaFStat ( Collection< double[]> lists )

static

static double broad.core.math.Statistics.average ( Collection<?extends Number > values )

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static double broad.core.math.Statistics.average ( double[] values )

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static double [] broad.core.math.Statistics.computePermutedZScores	(	double	observation,
		double[]	controlObservations,
		double	fudge_factor
	)

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static double [] broad.core.math.Statistics.computePermutedZScores	(	double	observation,
		double[]	controlObservations
	)

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static double broad.core.math.Statistics.covariance	(	List<?extends Number >	values1,
		List<?extends Number >	values2,
		double	mean1,
		double	mean2
	)

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static double broad.core.math.Statistics.covariance	(	List<?extends Number >	values1,
		List<?extends Number >	values2
	)

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static double broad.core.math.Statistics.diff	(	double[]	g1,
		double[]	g2
	)

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static double broad.core.math.Statistics.entropy ( double[] p_vec )

static

static double broad.core.math.Statistics.euclideanDistance	(	double[]	x,
		double[]	y
	)

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static double broad.core.math.Statistics.euclideanDistance	(	List< Double >	x,
		List< Double >	y
	)

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static double broad.core.math.Statistics.FDR	(	EmpiricalDistribution	observedDist,
		EmpiricalDistribution[]	randomDist,
		double	x
	)

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static double broad.core.math.Statistics.FDRCorrect	(	double[]	pvals,
		double	alpha
	)

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static double broad.core.math.Statistics.FDRCorrect	(	List< Double >	pvals,
		double	alpha
	)

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static double broad.core.math.Statistics.fold	(	Collection< Double >	g1,
		Collection< Double >	g2,
		boolean	log
	)

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static double broad.core.math.Statistics.fold	(	double[]	g1,
		double[]	g2,
		boolean	log
	)

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static double broad.core.math.Statistics.fold	(	double[]	g1,
		boolean	log
	)

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static double broad.core.math.Statistics.geometricMean ( double[] vals )

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static double broad.core.math.Statistics.geometricMeanMAD ( Matrix data )

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static double broad.core.math.Statistics.getKSStatistic	(	double[]	observed,
		double[]	expected
	)

static

static double broad.core.math.Statistics.hamming	(	double[]	x,
		double[]	y,
		double	threshold
	)

static

computes the hamming distance between two vectors, given a threshold. The threshold is used to reduce the vectors to a trinary form were, for example x[i] is set to 1 when x[i]>threshold, x[i] is set to -1 when x[i]< threshold and 0 otherwise

Parameters

x
y
threshold	to use in order to reduce the vectors

Returns

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static double broad.core.math.Statistics.hamming	(	List< Double >	x,
		List< Double >	y,
		double	threshold
	)

static

computes the hamming distance between two vectors, given a threshold. The threshold is used to reduce the vectors to a trinary form were, for example x.get(i) is set to 1 when x.get(i)>threshold, x.get(i)is set to -1 when x.get(i)< threshold and 0 otherwise

Parameters

x
y
threshold	to use in order to reduce the vectors

Returns

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static double [] broad.core.math.Statistics.hochbergPvalueAdjust ( double[] pvals )

static

Adjust a set of P values for multiple testing with the Hochberg method

Parameters

pvals The P values

Returns: Array of adjusted P values in same order

static double broad.core.math.Statistics.hypergeometric	(	int	numberOfGenesTotal,
		int	diffExpressedGenes,
		int	genesInSet,
		int	diffExpressedGenesInSet
	)

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static Double broad.core.math.Statistics.JSDist	(	double[]	p1,
		double[]	p2
	)

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static double broad.core.math.Statistics.MAD ( double[] array )

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static void broad.core.math.Statistics.main ( String[] args ) throws Exception

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double broad.core.math.Statistics.manhattanDistance	(	double[]	x,
		double[]	y
	)

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static double broad.core.math.Statistics.max ( Collection< Double > vals )

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static double broad.core.math.Statistics.max ( double[] vals )

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static int broad.core.math.Statistics.max ( int[] vals )

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static int broad.core.math.Statistics.maxInt ( Collection< Integer > vals )

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static double broad.core.math.Statistics.maxMAD ( Matrix data )

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static double broad.core.math.Statistics.maxmean ( double[] vals )

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static double broad.core.math.Statistics.maxStdev ( Matrix data )

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static double broad.core.math.Statistics.mean ( double[] values )

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static double broad.core.math.Statistics.mean ( Matrix data )

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static double broad.core.math.Statistics.mean ( Collection<?extends Number > values )

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static double broad.core.math.Statistics.median ( Collection< Double > list )

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static double broad.core.math.Statistics.median ( double[] list )

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static double broad.core.math.Statistics.median ( int[] list )

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static double broad.core.math.Statistics.medianCollection ( Collection< Double > values )

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static double broad.core.math.Statistics.metaAvg ( Collection< double[]> data )

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static double broad.core.math.Statistics.min ( Collection< Double > vals )

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static double broad.core.math.Statistics.min ( double[] vals )

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static int broad.core.math.Statistics.min ( int[] vals )

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static int broad.core.math.Statistics.minInt ( Collection< Integer > vals )

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static double [] broad.core.math.Statistics.normalizeToRelativeAbundance ( double[] vals )

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static double broad.core.math.Statistics.pairedTStat	(	List< Double >	g1,
		List< Double >	g2
	)

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static double broad.core.math.Statistics.pairedTStat	(	double[]	gr1,
		double[]	gr2
	)

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static double broad.core.math.Statistics.pearsonCorrelation	(	List<?extends Number >	values1,
		List<?extends Number >	values2
	)

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static double broad.core.math.Statistics.pearsonDistance	(	double[]	x,
		double[]	y
	)

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static double broad.core.math.Statistics.pearsonDistance	(	List< Double >	xA,
		List< Double >	yA
	)

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static double broad.core.math.Statistics.pvalue	(	List< Double >	data,
		double	value,
		boolean	isSorted
	)

static

Computes what is P(X > value) using list of values

Parameters

data
value
isSorted	true if the data list is sorted, it will avoid sorting here.

Returns

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static double broad.core.math.Statistics.pvalue	(	double[]	data,
		double	value,
		boolean	isSorted
	)

static

Computes what is P(X > value) using list of values

Parameters

data
value
isSorted	true if the data list is sorted, it will avoid sorting here.

Returns

static double broad.core.math.Statistics.pvalue	(	List< Double >	data,
		double	value
	)

static

Computes what is P(X > value) using list of values

Parameters

data
value

Returns

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static double broad.core.math.Statistics.quantile	(	List<?extends Number >	list,
		double	pct
	)

static

Uses the Weighted average method.

Parameters

list	- Ordered list of numbers (i.e. short, float, double, etc)
pct	- Desired quantile

Returns: the estimated quantile requested: x s.t. P(X <= x) >= pct

static double broad.core.math.Statistics.quantile	(	double[]	vals,
		double	pct
	)

static

static int [] broad.core.math.Statistics.randomPermutation ( int n )

static

static double [] broad.core.math.Statistics.rank	(	double[]	vals,
		boolean	ascending
	)

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static double broad.core.math.Statistics.spearmanCorrelation	(	List< Double >	xA,
		List< Double >	yA
	)

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static double broad.core.math.Statistics.spearmanCorrelation	(	double[]	x,
		double[]	y
	)

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static double broad.core.math.Statistics.stdev ( Collection<?extends Number > values )

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static double broad.core.math.Statistics.stdev ( double[] values )

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static double broad.core.math.Statistics.sum ( List< Double > vals )

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static double broad.core.math.Statistics.sum ( double[] vals )

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static double [] broad.core.math.Statistics.toDoubleArray ( List< Double > lst )

static

static ArrayList<Double> broad.core.math.Statistics.toDoubleArrayList ( double[] intervalScores )

static

static ArrayList<Double> broad.core.math.Statistics.toUniqueSortedList ( ArrayList< Double > List )

static

static double broad.core.math.Statistics.tstat	(	List< Double >	g1,
		List< Double >	g2,
		double	tstat_tuning_param
	)

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static double broad.core.math.Statistics.tstat	(	double[]	g1,
		double[]	g2,
		double	tstat_tuning_param
	)

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static double broad.core.math.Statistics.tstat	(	List< Double >	g1,
		List< Double >	g2
	)

static

Two sample T statistic

Parameters

g1	Measurements from group 1
g2	Measurements from group 2

Returns: T statistic (positive iff mean of group 1 is greater than mean of group 2)

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static double broad.core.math.Statistics.variance ( double[] values )

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static double broad.core.math.Statistics.variance	(	double[]	values,
		double	mean
	)

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static double broad.core.math.Statistics.variance ( List<?extends Number > values )

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static double broad.core.math.Statistics.variance	(	List<?extends Number >	values,
		double	mean
	)

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static double broad.core.math.Statistics.zScore	(	double	observation,
		double[]	controlObservations,
		double	fudge_factor
	)

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static double broad.core.math.Statistics.zScore	(	double	observation,
		double	mean,
		double	variance,
		int	length
	)

static

static double broad.core.math.Statistics.zScore	(	double	observation,
		double[]	controlObservations
	)

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static double broad.core.math.Statistics.zScore2	(	double	observation,
		double[]	controlObservations
	)

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static double broad.core.math.Statistics.zscoreToPvalue ( double zscore )

static

Calculate p-value given a Z-score

Returns: double p-value

Member Data Documentation

final String broad.core.math.Statistics.USAGE

static

Initial value:

= "Usage: Statistics TASK=<task_num> <task_args>\n" +
    "\tTasks:\n" +
    "\t\t1. Compute Benjamini-Hochberg FDR adjusted pvalue of a given pvalue column in a file " +
    "\n\t\t\t-in <file (standard input is default)> -fdr <Maximum false discovery rate> -col <Data column, 0 based> [-separator <character used to separate columns, default is tab '\\t>'] " +
    "\n"

The documentation for this class was generated from the following file:

java/broad/core/math/Statistics.java

Public Member Functions

Static Public Member Functions

Static Public Attributes

Member Function Documentation

Member Data Documentation