SampleNormalization: The SampleNormalization class
In NSA: Post-normalization of total copy numbers

Description Usage Arguments Details Fields and Methods References See Also

Package: NSA
Class SampleNormalization

Object
~~|
~~+--SampleNormalization

Directly known subclasses:

public static class SampleNormalization
extends Object

This class represents the Sample normalization method [1], which looks for normal regions within the tumoral samples.

1	SampleNormalization(data=NULL, tags="*", ...)

`data`	A named `list` with data set named `"total"` and `"fracB"` where the former should be of class `AromaUnitTotalCnBinarySet` and the latter of class `AromaUnitFracBCnBinarySet`. The two data sets must be for the same chip type, have the same number of samples and the same sample names.
`tags`	Tags added to the output data sets.
`...`	Not used.

...

Methods:

	`findArraysTodo`	-
	`getDataSets`	-
	`getFullName`	-
	`getName`	-
	`getOutputDataSets`	-
	`getPath`	-
	`getRootPath`	-
	`getTags`	-
	`nbrOfFiles`	-
	`process`	Finds normal regions within tumoral samples.
	`setTags`	-

Methods inherited from Object:
asThis, $, $<-, [[, [[<-, as.character, attach, attachLocally, clearCache, clone, detach, equals, extend, finalize, gc, getEnvironment, getFields, getInstantiationTime, getStaticInstance, hasField, hashCode, ll, load, objectSize, print, registerFinalizer, save

[1] ...

Low-level versions of the Sample normalization method is available via the sampleNByTotalAndFracB.numeric() methods.

NSA documentation built on May 29, 2017, 3:36 p.m.