Class QuantileNormalizer<R,C>

java.lang.Object

ubic.gemma.core.analysis.preprocess.normalize.QuantileNormalizer<R,C>

public class QuantileNormalizer<R,C>
extends Object

Perform quantile normalization on a matrix, as described in:

Bolstad, B (2001) _Probe Level Quantile Normalization of High Density Oligonucleotide Array Data_. Unpublished manuscript PDF

Bolstad, B. M., Irizarry R. A., Astrand, M, and Speed, T. P. (2003) _A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Bias and Variance._ Bioinformatics 19(2) ,pp 185-193. web page. However, note that this deals with missing values differently than the Bioconductor implementation.

Author:

pavlidis

See Also:

• MatrixNormalizer

Constructor Summary

Constructors

Constructor	Description
QuantileNormalizer()

Method Summary

Modifier and Type	Method	Description
DoubleMatrix<R,C>	normalize(DoubleMatrix<R,C> dataMatrix)
DoubleMatrix<R,C>	normalize(DoubleMatrix<R,C> dataMatrix, boolean[] includeInReference)	Normalize, letting only some columns define the reference distribution.

Methods inherited from class Object

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

Constructor Details

QuantileNormalizer

public QuantileNormalizer()

Method Details

normalize

public DoubleMatrix<R,C> normalize(DoubleMatrix<R,C> dataMatrix)

normalize

public DoubleMatrix<R,C> normalize(DoubleMatrix<R,C> dataMatrix,
 @Nullable
 boolean[] includeInReference)

Normalize, letting only some columns define the reference distribution.

Parameters:

includeInReference - one flag per column; null means every column contributes

See Also:

• MatrixNormalizer.quantileNormalize(DoubleMatrix, boolean[])