Class for score used in Significance Analysis of Microarrays (SAM). More...

#include <yat/statistics/SAMScore.h>

Inheritance diagram for theplu::yat::statistics::SAMScore:

Public Member Functions
	SAMScore (const double s0, bool absolute=true)

double	score (const classifier::Target &target, const utility::VectorBase &value) const

double	score (const classifier::Target &target, const classifier::DataLookupWeighted1D &value) const

double	score (const classifier::Target &target, const utility::VectorBase &value, const utility::VectorBase &weight) const

void	absolute (bool absolute)
	Function changing mode of Score.

virtual double	score (const classifier::Target &target, const classifier::DataLookup1D &value) const

double	score (const classifier::Target &target, const classifier::DataLookup1D &value, const classifier::DataLookup1D &weight) const

Protected Attributes
bool	absolute_

Detailed Description

Class for score used in Significance Analysis of Microarrays (SAM).

The score is similar to the Student t-test but with an added fudge factor in denominator to avoid groups with small variance getting a large score. $\frac{m_x-m_y}{s+s_0}$

see http://www.pnas.org/cgi/content/abstract/98/9/5116 for details

Constructor & Destructor Documentation

theplu::yat::statistics::SAMScore::SAMScore	(	const double	s0,
		bool	absolute = `true`
	)

Parameters

s0	is a fudge factor
absolute	if true max(score, -score) is used

Member Function Documentation

double theplu::yat::statistics::SAMScore::score	(	const classifier::Target &	target,
		const utility::VectorBase &	value
	)		const

virtual

$\frac{m_x-m_y}{s+s_0}$ where $m = \frac{1}{n_x}\sum x_i$ , $s^2 = \left(\frac{1}{n_x}+\frac{1}{n_y} \right) \frac{\sum (x_i-m_x)^2 + \sum(y_i-m_y)^2}{n_x+n_y-2}$ , and $ s_0 $ is the fudge factor.

Returns: SAM score. If absolute=true absolute value of t-score is returned

Implements theplu::yat::statistics::Score.

virtual double theplu::yat::statistics::Score::score	(	const classifier::Target &	target,
		const classifier::DataLookup1D &	value
	)		const

virtualinherited

Function calculating the score. In absolute mode, also the score using negated class labels is calculated, and the largest of the two scores are calculated.

value is copied to a utility::vector and that operator is called. If speed is important this operator should be implemented in inherited class to avoid copying.

Returns: score

double theplu::yat::statistics::SAMScore::score	(	const classifier::Target &	target,
		const classifier::DataLookupWeighted1D &	value
	)		const

virtual

$\frac{m_x-m_y}{s+s_0}$ where $m = \frac{\sum w_ix_i}{w_i}$ , $ s_0 $ is the fudge factor, and $s^2 = \left(\frac{1}{n_x}+\frac{1}{n_y} \right) \frac{\sum w_i(x_i-m_x)^2 + \sum w_i(y_i-m_y)^2}{n_x+n_y-2}$ where $ n $ is weighted version of number of data points $\frac{\left(\sum w_i\right)^2}{\sum w_i^2}$ .

Returns: weighted version of SAM score. If absolute=true absolute value is returned

Reimplemented from theplu::yat::statistics::Score.

double theplu::yat::statistics::SAMScore::score	(	const classifier::Target &	target,
		const utility::VectorBase &	value,
		const utility::VectorBase &	weight
	)		const

virtual

$\frac{m_x-m_y}{s+s_0}$ where $m = \frac{\sum w_ix_i}{w_i}$ , $ s_0 $ is the fudge factor, and $s^2 = \left(\frac{1}{n_x}+\frac{1}{n_y} \right) \frac{\sum w_i(x_i-m_x)^2 + \sum w_i(y_i-m_y)^2}{n_x+n_y-2}$ where $ n $ is weighted version of number of data points $\frac{\left(\sum w_i\right)^2}{\sum w_i^2}$ .

Returns: weighted version of SAM score. If absolute=true absolute value is returned

Implements theplu::yat::statistics::Score.

double theplu::yat::statistics::Score::score	(	const classifier::Target &	target,
		const classifier::DataLookup1D &	value,
		const classifier::DataLookup1D &	weight
	)		const

inherited

Function calculating the weighted version of score. In absolute mode, also the score using negated class labels is calculated, and the largest of the two scores are calculated. Absolute mode should be used when two-tailed test is wanted.

value and weight are copied to utility::vector and the corresponding operator is called. If speed is important this operator should be implemented in inherited class to avoid copying.

Member Data Documentation

bool theplu::yat::statistics::Score::absolute_

protectedinherited

true if method is absolute, which means if score is below expected value (by chance) E, score returns E-score+E instead.

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

yat/statistics/SAMScore.h

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation