Package 'aroma.core' reference manual

Title:	Core Methods and Classes Used by 'aroma.*' Packages Part of the Aroma Framework
Description:	Core methods and classes used by higher-level 'aroma.*' packages part of the Aroma Project, e.g. 'aroma.affymetrix' and 'aroma.cn'.
Authors:	Henrik Bengtsson [aut, cre, cph], Mark Robinson [ctb], Ken Simpson [ctb]
Maintainer:	Henrik Bengtsson <[email protected]>
License:	LGPL (>= 2.1)
Version:	3.3.0
Built:	2024-08-13 04:19:09 UTC
Source:	https://github.com/HenrikBengtsson/aroma.core

Package aroma.core

Description

Core methods and classes used by higher-level 'aroma.*' packages part of the Aroma Project, e.g. 'aroma.affymetrix' and 'aroma.cn'.

This package is a support package for aroma.affymetrix. This package should be considered to be in an alpha or beta phase. You should expect the API to be changing over time. For practical purposes, consider this package a private package.

Installation and updates

This package is available on CRAN, i.e. to install do install.packages("aroma.core").

License

The releases of this package is licensed under LGPL version 2.1 or newer.

The development code of the packages is under a private licence (where applicable) and patches sent to the author fall under the latter license, but will be, if incorporated, released under the "release" license above.

Author(s)

Henrik Bengtsson

References

[1] H. Bengtsson, The R.oo package - Object-Oriented Programming with References Using Standard R Code, In Kurt Hornik, Friedrich Leisch and Achim Zeileis, editors, Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), March 20-22, Vienna, Austria. http://www.ci.tuwien.ac.at/Conferences/DSC-2003/Proceedings/

The AbstractCNData class

Description

Package: aroma.core
Class AbstractCNData

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--AbstractCNData

Directly known subclasses:
AbstractPSCNData, NonPairedPSCNData, PairedPSCNData

public class AbstractCNData
extends RawGenomicSignals

An AbstractCNData object holds copy number data.

Usage

AbstractCNData(chromosome=NULL, x=NULL, y=NULL, ..., name=NULL, .virtuals=NULL)
AbstractCNData(chromosome=NULL, x=NULL, y=NULL, ..., name=NULL, .virtuals=NULL)

Arguments

`chromosome`	(Optional) An `integer` scalar (or a `vector` of length J), which can be used to specify which chromosome each locus belongs to in case multiple chromosomes are segments. This argument is also used for annotation purposes.
`x`	Optional `numeric` `vector` of J genomic locations. If `NULL`, index locations `1:J` are used.
`y`	Optional `numeric` `vector` of J genomic locations.
`...`	Optional named locus-specific signal `vector`s of length J.
`name`	Optional `character` string.
`.virtuals`	(Internal) a `list` with virtual column name `function`s.

Fields and Methods

Methods:

	`findLargeGaps`	-
	`getChipType`	-
	`getLocusData`	-
	`getPlatform`	-
	`setChipType`	-
	`setPlatform`	-

Methods inherited from RawGenomicSignals:
*, +, -, addBy, append, applyBinaryOperator, as.character, as.data.frame, assertOneChromosome, binnedSmoothing, binnedSmoothingByField, clearCache, clone, divideBy, drawDensity, estimateStandardDeviation, extractChromosome, extractChromosomes, extractDataForSegmentation, extractRegion, extractRegions, extractSubset, gaussianSmoothing, getBasicField, getCXY, getChromosome, getChromosomes, getDefaultLocusFields, getLocusFields, getPositions, getSigma, getSignalColumnName, getSignalColumnNames, getSignals, getWeights, getXScale, getXY, getYScale, hasWeights, kernelSmoothing, lines, multiplyBy, nbrOfChromosomes, nbrOfLoci, plot, points, print, segmentByCBS, segmentByGLAD, segmentByHaarSeg, segmentByMPCBS, setBasicField, setSigma, setSignals, setWeights, setXScale, setYScale, signalRange, sort, subtractBy, xMax, xMin, xRange, xSeq, yMax, yMin, yRange

Methods inherited from RichDataFrame:
$, $<-, [, [[, [[<-, as.data.frame, as.list, dim, dropVirtualColumn, getColumnNames, getColumnNamesTranslator, getFullName, getName, getTags, getVirtualColumn, getVirtualColumnFunction, getVirtualColumnNames, hasColumn, hasColumns, hasVirtualColumn, hasVirtualColumns, length, names, newInstance, print, rbind, setAttributes, setColumnNamesMap, setColumnNamesTranslator, setName, setTags, setVirtualColumn, subset, translateColumnNames

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The AbstractPSCNData class

Description

Package: aroma.core
Class AbstractPSCNData

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--AbstractCNData
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--AbstractPSCNData

Directly known subclasses:
NonPairedPSCNData, PairedPSCNData

public class AbstractPSCNData
extends AbstractCNData

A AbstractPSCNData object holds parent-specific copy number data.

Usage

AbstractPSCNData(chromosome=NULL, x=NULL, isSNP=NULL, mu=NULL, ...)
AbstractPSCNData(chromosome=NULL, x=NULL, isSNP=NULL, mu=NULL, ...)

Arguments

`chromosome`	(Optional) An `integer` scalar (or a `vector` of length J), which can be used to specify which chromosome each locus belongs to in case multiple chromosomes are segments. This argument is also used for annotation purposes.
`x`	Optional `numeric` `vector` of J genomic locations. If `NULL`, index locations `1:J` are used.
`isSNP`	An optional `logical` `vector` of length J specifying whether each locus is a SNP or not (non-polymorphic loci).
`mu`	An optional `numeric` `vector` of J genotype calls in {0,1/2,1} for AA, AB, and BB, respectively, and `NA` for non-polymorphic loci.
`...`	Optional named locus-specific signal `vector`s of length J.

Fields and Methods

Methods:
No methods defined.

Methods inherited from AbstractCNData:
findLargeGaps, getChipType, getLocusData, getPlatform, hasKnownPositions, orderAlongGenome, setChipType, setPlatform

Author(s)

Henrik Bengtsson

A binary file holding local CpG density for each cell (probe/feature)

Description

A binary file holding local CpG density for each cell (probe/feature).

Usage

AromaCellCpgFile(...)
AromaCellCpgFile(...)

Arguments

...

Arguments passed to constructor of AromaCellTabularBinaryFile.

Details

Note that this class does not assume a rectangular chip layout. In other words, there is no concept of mapping a spatial location on the array to a cell index and vice versa. The reason for this to be able to use this class also for non-rectangular chip types.

Author(s)

Mark Robinson

A binary file holding chromosome/position for each cell

Description

A binary file holding chromosome/position for each cell.

Usage

AromaCellPositionFile(...)
AromaCellPositionFile(...)

Arguments

...

Arguments passed to constructor of AromaCellTabularBinaryFile.

Details

Author(s)

Henrik Bengtsson

The AromaCellTabularBinaryFile class

Description

Package: aroma.core
Class AromaCellTabularBinaryFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--ColumnNamesInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--GenericTabularFile
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaPlatformInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaMicroarrayTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaCellTabularBinaryFile

Directly known subclasses:
AromaCellCpgFile, AromaCellPositionFile, AromaCellSequenceFile

public abstract static class AromaCellTabularBinaryFile
extends AromaMicroarrayTabularBinaryFile

An AromaCellTabularBinaryFile is an AromaTabularBinaryFile with the constraint that the rows map one-to-one to the cells (features) of a microarray.

Usage

AromaCellTabularBinaryFile(...)
AromaCellTabularBinaryFile(...)

Arguments

...

Arguments passed to AromaTabularBinaryFile.

Fields and Methods

Methods:

	`byChipType`	-
	`nbrOfCells`	-

Methods inherited from AromaMicroarrayTabularBinaryFile:
allocate, as.character, byChipType, findByChipType, getChipType, getFilenameExtension, getPlatform

Methods inherited from AromaPlatformInterface:
getAromaPlatform, getAromaUflFile, getAromaUgpFile, getChipType, getPlatform, getUnitAnnotationDataFile, getUnitNamesFile, getUnitTypesFile, isCompatibleWith

Methods inherited from AromaTabularBinaryFile:
[, [<-, [[, allocate, as.character, colApply, colMeans, colStats, colSums, dimnames<-, getBytesPerColumn, getColClasses, getDefaultColumnNames, getRootName, importFrom, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, readFooter, readHeader, readRawFooter, setAttributesByTags, subset, summary, updateData, updateDataColumn, writeFooter, writeRawFooter

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Methods inherited from ColumnNamesInterface:
appendColumnNamesTranslator, appendColumnNamesTranslatorByNULL, appendColumnNamesTranslatorBycharacter, appendColumnNamesTranslatorByfunction, appendColumnNamesTranslatorBylist, clearColumnNamesTranslator, clearListOfColumnNamesTranslators, getColumnNames, getColumnNamesTranslator, getDefaultColumnNames, getListOfColumnNamesTranslators, nbrOfColumns, setColumnNames, setColumnNamesTranslator, setListOfColumnNamesTranslators, updateColumnNames

Methods inherited from GenericDataFile:
as.character, clone, compareChecksum, copyTo, equals, fromFile, getAttribute, getAttributes, getChecksum, getChecksumFile, getCreatedOn, getDefaultFullName, getExtension, getExtensionPattern, getFileSize, getFileType, getFilename, getFilenameExtension, getLastAccessedOn, getLastModifiedOn, getOutputExtension, getPath, getPathname, gunzip, gzip, hasBeenModified, is.na, isFile, isGzipped, linkTo, readChecksum, renameTo, renameToUpperCaseExt, setAttribute, setAttributes, setAttributesBy, setAttributesByTags, setExtensionPattern, testAttributes, validate, validateChecksum, writeChecksum, getParentName

Methods inherited from FullNameInterface:
appendFullNameTranslator, appendFullNameTranslatorByNULL, appendFullNameTranslatorByTabularTextFile, appendFullNameTranslatorByTabularTextFileSet, appendFullNameTranslatorBycharacter, appendFullNameTranslatorBydata.frame, appendFullNameTranslatorByfunction, appendFullNameTranslatorBylist, clearFullNameTranslator, clearListOfFullNameTranslators, getDefaultFullName, getFullName, getFullNameTranslator, getListOfFullNameTranslators, getName, getTags, hasTag, hasTags, resetFullName, setFullName, setFullNameTranslator, setListOfFullNameTranslators, setName, setTags, updateFullName

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

Author(s)

Henrik Bengtsson

The AromaGenomeTextFile class

Description

Package: aroma.core
Class AromaGenomeTextFile

Directly known subclasses:
AromaUcscGenomeTextFile

public abstract static class AromaGenomeTextFile
extends FileCacheKeyInterface

An AromaGenomeTextFile represents a annotation tabular text file that specifies the number of bases (nucleotides) per chromosome for a particular genome/organism.

Usage

AromaGenomeTextFile(...)
AromaGenomeTextFile(...)

Arguments

...

Arguments passed to TabularTextFile.

Details

An AromaGenomeTextFile is a tab-delimited text file with a header containing (at least) column names 'chromosome' and 'nbrOfBases'. The 'chromosome' column specifies the chromosomes (character strings) and the 'nbrOfBases' column specifies the lengths (integer) of the chromosomes in number of bases (nucleotides).

The filename of an AromaGenomeTextFile should have format "<genome>,chromosomes(,<tag>)*.txt", and be located in annotationData/genomes/<genome>/, e.g. annotationData/genomes/Human/Human,chromosomes,max,20090503.txt.

Fields and Methods

Methods:

	`byGenome`	-
	`readDataFrame`	-

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from TabularTextFile:
as.character, getCommentChar, getDefaultColumnClassPatterns, getDefaultColumnClasses, getDefaultColumnNames, getHeader, getReadArguments, hasColumnHeader, nbrOfLines, nbrOfRows, readColumnNames, readColumns, readDataFrame, readLines, readRawHeader, setCommentChar

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

Examples

# Locate a Human,chromosomes(,.*)*.txt file
db <- AromaGenomeTextFile$byGenome("Human")
print(db)

# Read the data
df <- readDataFrame(db)
print(df)
str(df)

# Details on the file format
oopts <- options(width=40)
print(readLines(db))
options(oopts)
# Locate a Human,chromosomes(,.*)*.txt file
db <- AromaGenomeTextFile$byGenome("Human")
print(db)

# Read the data
df <- readDataFrame(db)
print(df)
str(df)

# Details on the file format
oopts <- options(width=40)
print(readLines(db))
options(oopts)

The abstract AromaMicroarrayDataFile class

Description

Package: aroma.core
Class AromaMicroarrayDataFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--AromaMicroarrayDataFile

Directly known subclasses:

public abstract static class AromaMicroarrayDataFile
extends FileCacheKeyInterface

An AromaMicroarrayDataFile object represents a single microarray data file. Each such file originates from a specific chip type on a given platform.

Usage

AromaMicroarrayDataFile(...)
AromaMicroarrayDataFile(...)

Arguments

...

Arguments passed to GenericDataFile.

Fields and Methods

Methods:

	`getChipType`	-
	`getPlatform`	-
	`isAverageFile`	-

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Author(s)

Henrik Bengtsson

The AromaMicroarrayDataSet class

Description

Package: aroma.core
Class AromaMicroarrayDataSet

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFileSet
~~~~~~~~~~~~|
~~~~~~~~~~~~+--AromaMicroarrayDataSet

Directly known subclasses:

public abstract static class AromaMicroarrayDataSet
extends GenericDataFileSet

An AromaMicroarrayDataSet object represents a set of AromaMicroarrayDataFiles with identical chip types.

Usage

AromaMicroarrayDataSet(files=NULL, ...)
AromaMicroarrayDataSet(files=NULL, ...)

Arguments

`files`	A `list` of `AromaMicroarrayDataFile`:s.
`...`	Arguments passed to `GenericDataFileSet`.

Fields and Methods

Methods:

	`as.AromaMicroarrayDataSetList`	-
	`as.AromaMicroarrayDataSetTuple`	-
	`getAverageFile`	-
	`getChipType`	-
	`getPlatform`	-

Methods inherited from GenericDataFileSet:
[, [[, anyDuplicated, anyNA, append, appendFiles, appendFullNamesTranslator, appendFullNamesTranslatorByNULL, appendFullNamesTranslatorByTabularTextFile, appendFullNamesTranslatorByTabularTextFileSet, appendFullNamesTranslatorBydata.frame, appendFullNamesTranslatorByfunction, appendFullNamesTranslatorBylist, as.character, as.list, byName, byPath, c, clearCache, clearFullNamesTranslator, clone, copyTo, dsApplyInPairs, duplicated, equals, extract, findByName, findDuplicated, getChecksum, getChecksumFileSet, getChecksumObjects, getDefaultFullName, getFile, getFileClass, getFileSize, getFiles, getFullNames, getNames, getOneFile, getPath, getPathnames, getSubdirs, gunzip, gzip, hasFile, indexOf, is.na, names, nbrOfFiles, rep, resetFullNames, setFullNamesTranslator, sortBy, unique, update2, updateFullName, updateFullNames, validate, getFullNameTranslatorSet, getParentName

Author(s)

Henrik Bengtsson

The AromaMicroarrayDataSetTuple class

Description

Package: aroma.core
Class AromaMicroarrayDataSetTuple

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFileSetList
~~~~~~~~~~~~|
~~~~~~~~~~~~+--AromaMicroarrayDataSetTuple

Directly known subclasses:
AromaUnitTotalCnBinarySetTuple

public abstract static class AromaMicroarrayDataSetTuple
extends GenericDataFileSetList

Usage

AromaMicroarrayDataSetTuple(..., .setClass="AromaMicroarrayDataSet")
AromaMicroarrayDataSetTuple(..., .setClass="AromaMicroarrayDataSet")

Arguments

`...`	Arguments passed to `GenericDataFileSetList`.
`.setClass`	The name of the class of the input set.

Fields and Methods

Methods:

	`as`	-
	`as.AromaMicroarrayDataSetTuple`	-
	`getChipTypes`	-
	`getFullNames`	-
	`getSets`	-
	`getTags`	-
	`nbrOfChipTypes`	Gets the number of chip types.

Methods inherited from GenericDataFileSetList:
as, as.GenericDataFileSetList, as.character, as.data.frame, as.list, assertDuplicates, clone, extract, getAsteriskTags, getDefaultFullName, getFileList, getFileListClass, getFullNames, getNames, getSet, getSets, getTags, indexOf, length, nbrOfFiles, nbrOfSets, setTags

Author(s)

Henrik Bengtsson

The AromaMicroarrayTabularBinaryFile class

Description

Package: aroma.core
Class AromaMicroarrayTabularBinaryFile

Directly known subclasses:
AromaCellCpgFile, AromaCellPositionFile, AromaCellSequenceFile, AromaCellTabularBinaryFile, AromaUflFile, AromaUgcFile, AromaUgpFile, AromaUnitChromosomeTabularBinaryFile, AromaUnitGcContentFile, AromaUnitTabularBinaryFile

public abstract static class AromaMicroarrayTabularBinaryFile
extends AromaPlatformInterface

An AromaMicroarrayTabularBinaryFile is an abstract AromaTabularBinaryFile.

Usage

AromaMicroarrayTabularBinaryFile(...)
AromaMicroarrayTabularBinaryFile(...)

Arguments

...

Arguments passed to AromaTabularBinaryFile.

Fields and Methods

Methods:

	`byChipType`	-
	`getChipType`	-
	`getFilenameExtension`	-
	`getPlatform`	-

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaPlatform class

Description

Package: aroma.core
Class AromaPlatform

Object
~~|
~~+--AromaPlatform

Directly known subclasses:

public abstract static class AromaPlatform
extends Object

An AromaPlatform provides methods for a given platform, e.g. Affymetrix, Agilent, Illumina.

Usage

AromaPlatform(...)
AromaPlatform(...)

Arguments

...

Not used.

Methods

Methods:

	`byName`	-
	`equals`	-
	`getAromaUgpFile`	-
	`getName`	-
	`getUnitNamesFile`	-
	`getUnitTypesFile`	-

Author(s)

Henrik Bengtsson

Examples

## Not run: 
 library("aroma.affymetrix")
platform <- AromaPlatform$byName("Affymetrix")
print(platform)
stopifnot(getName(platform) == "Affymetrix")


## End(Not run)## Not run: 
 library("aroma.affymetrix")
platform <- AromaPlatform$byName("Affymetrix")
print(platform)
stopifnot(getName(platform) == "Affymetrix")


## End(Not run)

The AromaPlatformInterface class

Description

Package: aroma.core
Class AromaPlatformInterface

Interface
~~|
~~+--AromaPlatformInterface

Directly known subclasses:
AromaCellCpgFile, AromaCellPositionFile, AromaCellSequenceFile, AromaCellTabularBinaryFile, AromaMicroarrayTabularBinaryFile, AromaUflFile, AromaUgcFile, AromaUgpFile, AromaUnitCallFile, AromaUnitChromosomeTabularBinaryFile, AromaUnitFracBCnBinaryFile, AromaUnitGcContentFile, AromaUnitGenotypeCallFile, AromaUnitPscnBinaryFile, AromaUnitSignalBinaryFile, AromaUnitTabularBinaryFile, AromaUnitTotalCnBinaryFile, AromaUnitTypesFile

public abstract class AromaPlatformInterface
extends Interface

An AromaPlatformInterface provides methods for a given platform, e.g. Affymetrix, Agilent, Illumina.

Usage

AromaPlatformInterface(...)
AromaPlatformInterface(...)

Arguments

...

Not used.

Methods

Methods:

	`getAromaPlatform`	Gets the platform.
	`getAromaUflFile`	-
	`getAromaUgpFile`	-
	`getChipType`	Gets the chip type.
	`getPlatform`	Gets the platform.
	`getUnitNamesFile`	-
	`getUnitTypesFile`	-

Methods inherited from Interface:
extend, print, uses

Author(s)

Henrik Bengtsson

The AromaRepository class

Description

Package: aroma.core
Class AromaRepository

Object
~~|
~~+--AromaRepository

Directly known subclasses:

public static class AromaRepository
extends Object

An AromaRepository object provides methods for downloading annotation data from the Aroma repository.

Usage

AromaRepository(urlPath="https://www.aroma-project.org/data", verbose=FALSE, ...)
AromaRepository(urlPath="https://www.aroma-project.org/data", verbose=FALSE, ...)

Arguments

`urlPath`	The URL to the Aroma repository.
`verbose`	The `Verbose` to be used during processing.
`...`	Not used.

Methods

Methods:

	`downloadACC`	-
	`downloadACM`	-
	`downloadACP`	-
	`downloadACS`	-
	`downloadAll`	-
	`downloadCDF`	-
	`downloadChipTypeFile`	Download a particular chip type annotation file.
	`downloadProbeSeqsTXT`	-
	`downloadTXT`	-
	`downloadUFL`	-
	`downloadUGC`	-
	`downloadUGP`	-

Author(s)

Henrik Bengtsson

The AromaTabularBinaryFile class

Description

Package: aroma.core
Class AromaTabularBinaryFile

public abstract static class AromaTabularBinaryFile
extends FileCacheKeyInterface

A AromaTabularBinaryFile represents a file with a binary format. It has a well defined header, a data section, and a footer.

Usage

AromaTabularBinaryFile(...)
AromaTabularBinaryFile(...)

Arguments

...

Arguments passed to GenericTabularFile.

Fields and Methods

Methods:

	`[`	-
	`[<-`	-
	`colMeans`	-
	`colSums`	-
	`getBytesPerColumn`	-
	`getColClasses`	-
	`importFrom`	-
	`nbrOfColumns`	-
	`nbrOfRows`	-
	`readColumns`	-
	`readFooter`	Reads the file footer in XML format into a named nested list.
	`subset`	-
	`summary`	-
	`writeFooter`	Writes a named nested list to the file footer in XML format.

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaTabularBinarySet class

Description

Package: aroma.core
Class AromaTabularBinarySet

Directly known subclasses:
AromaUnitCallSet, AromaUnitFracBCnBinarySet, AromaUnitGenotypeCallSet, AromaUnitPscnBinarySet, AromaUnitSignalBinarySet, AromaUnitTotalCnBinarySet

public static class AromaTabularBinarySet
extends GenericTabularFileSet

An AromaTabularBinarySet object represents a set of AromaTabularBinaryFiles with identical chip types.

Usage

AromaTabularBinarySet(files=NULL, ...)
AromaTabularBinarySet(files=NULL, ...)

Arguments

`files`	A `list` of `AromaTabularBinaryFile`:s.
`...`	Arguments passed to `GenericDataFileSet`.

Fields and Methods

Methods:
No methods defined.

Methods inherited from GenericTabularFileSet:
extractMatrix, calculateAverageColumnAcrossFiles

Author(s)

Henrik Bengtsson

The AromaTransform class

Description

Package: aroma.core
Class AromaTransform

Object
~~|
~~+--ParametersInterface
~~~~~~~|
~~~~~~~+--AromaTransform

Directly known subclasses:

public abstract static class AromaTransform
extends ParametersInterface

This abstract class represents a transform (algorithm/operator) that transforms data. A transform has an input data set, which is transformed into an output data set.

Usage

AromaTransform(dataSet=NULL, tags="*", ..., .reqSetClass="AromaMicroarrayDataSet")
AromaTransform(dataSet=NULL, tags="*", ..., .reqSetClass="AromaMicroarrayDataSet")

Arguments

`dataSet`	The input data set as an `AromaMicroarrayDataSet`.
`tags`	A `character` `vector` of tags to be appended to the tags of the input data set.
`...`	Not used.
`.reqSetClass`	Internal argument.

Details

Subclasses must implement the process() method.

Fields and Methods

Methods:

	`getFullName`	Gets the full name of the output data set.
	`getInputDataSet`	Gets the input data set.
	`getName`	Gets the name of the output data set.
	`getOutputDataSet`	Gets the transformed data set.
	`getPath`	Gets the path of the output directory.
	`getRootPath`	Gets the root path of the output directory.
	`getTags`	Gets the tags of the output data set.
	`isDone`	Checks if the data set is processed or not.
	`process`	Processes the data set.
	`setTags`	-

Methods inherited from ParametersInterface:
getParameterSets, getParameters, getParametersAsString

Author(s)

Henrik Bengtsson

The AromaUnitCallFile class

Description

Package: aroma.core
Class AromaUnitCallFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--ColumnNamesInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--GenericTabularFile
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaPlatformInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitSignalBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitCallFile

Directly known subclasses:
AromaUnitGenotypeCallFile

public static class AromaUnitCallFile
extends AromaUnitSignalBinaryFile

An AromaUnitCallFile is a AromaUnitSignalBinaryFile.

Usage

AromaUnitCallFile(...)
AromaUnitCallFile(...)

Arguments

...

Arguments passed to AromaUnitSignalBinaryFile.

Fields and Methods

Methods:

	`extractCallArray`	-
	`extractCalls`	-
	`extractMatrix`	-
	`findUnitsTodo`	-

Methods inherited from AromaUnitSignalBinaryFile:
allocate, allocateFromUnitAnnotationDataFile, allocateFromUnitNamesFile, as.character, extractMatrix, extractRawGenomicSignals, fromFile, getChipType, getExtensionPattern, getFilenameExtension, getNumberOfFilesAveraged, getPlatform, isAverageFile, nbrOfUnits, readDataFrame, writeDataFrame

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaUnitCallSet class

Description

Package: aroma.core
Class AromaUnitCallSet

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFileSet
~~~~~~~~~~~~|
~~~~~~~~~~~~+--GenericTabularFileSet
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--AromaTabularBinarySet
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitSignalBinarySet
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitCallSet

Directly known subclasses:
AromaUnitGenotypeCallSet

public static class AromaUnitCallSet
extends AromaUnitSignalBinarySet

An AromaUnitCallSet object represents a set of AromaUnitCallFiles with identical chip types.

Usage

AromaUnitCallSet(...)
AromaUnitCallSet(...)

Arguments

...

Arguments passed to AromaUnitSignalBinarySet.

Fields and Methods

Methods:

	`extractCallArray`	-
	`extractCalls`	-
	`extractGenotypeMatrix`	-
	`findUnitsTodo`	-

Methods inherited from AromaUnitSignalBinarySet:
byName, findByName, getAromaFullNameTranslatorSet, getAromaUgpFile, getChipType, getPlatform, validate, writeDataFrame

Methods inherited from AromaTabularBinarySet:
getDefaultFullName, getRootName, setAttributesBy, setAttributesBySampleAnnotationFile, setAttributesBySampleAnnotationSet, setAttributesByTags

Methods inherited from GenericTabularFileSet:
extractMatrix, calculateAverageColumnAcrossFiles

Author(s)

Henrik Bengtsson

The AromaUnitFracBCnBinaryFile class

Description

Package: aroma.core
Class AromaUnitFracBCnBinaryFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--ColumnNamesInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--GenericTabularFile
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaPlatformInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitSignalBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitFracBCnBinaryFile

Directly known subclasses:

public static class AromaUnitFracBCnBinaryFile
extends AromaUnitSignalBinaryFile

An AromaUnitFracBCnBinaryFile is a AromaUnitTabularBinaryFile.

Usage

AromaUnitFracBCnBinaryFile(...)
AromaUnitFracBCnBinaryFile(...)

Arguments

...

Arguments passed to AromaUnitTabularBinaryFile.

Fields and Methods

Methods:

	`extractRawAlleleBFractions`	-

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaUnitFracBCnBinarySet class

Description

Package: aroma.core
Class AromaUnitFracBCnBinarySet

Directly known subclasses:

public static class AromaUnitFracBCnBinarySet
extends AromaUnitSignalBinarySet

An AromaUnitFracBCnBinarySet object represents a set of AromaUnitFracBCnBinaryFiles with identical chip types.

Usage

AromaUnitFracBCnBinarySet(...)
AromaUnitFracBCnBinarySet(...)

Arguments

...

Arguments passed to AromaUnitSignalBinarySet.

Details

The term "allele B fraction" is also know as "allele B frequency", which was coined by Peiffer et al. (2006). Note that the term "frequency" is a bit misleading since it is not a frequency in neither the statistical nor the population sense, but rather only proportion relative to the total amount of allele A and allele B signals, which is calculated for each sample independently.

Fields and Methods

Methods:

	`byName`	-
	`writeDataFrame`	-

Methods inherited from AromaUnitSignalBinarySet:
byName, findByName, getAromaFullNameTranslatorSet, getAromaUgpFile, getChipType, getPlatform, validate, writeDataFrame

Methods inherited from AromaTabularBinarySet:
getDefaultFullName, getRootName, setAttributesBy, setAttributesBySampleAnnotationFile, setAttributesBySampleAnnotationSet, setAttributesByTags

Methods inherited from GenericTabularFileSet:
extractMatrix, calculateAverageColumnAcrossFiles

Author(s)

Henrik Bengtsson

References

[1] Peiffer et al., High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping, Genome Res, 2006.

The AromaUnitGenotypeCallFile class

Description

Package: aroma.core
Class AromaUnitGenotypeCallFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--ColumnNamesInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--GenericTabularFile
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaPlatformInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitSignalBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitCallFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitGenotypeCallFile

Directly known subclasses:

public static class AromaUnitGenotypeCallFile
extends AromaUnitCallFile

An AromaUnitGenotypeCallFile is a AromaUnitTabularBinaryFile.

Usage

AromaUnitGenotypeCallFile(...)
AromaUnitGenotypeCallFile(...)

Arguments

...

Arguments passed to AromaUnitTabularBinaryFile.

Fields and Methods

Methods:

	`extractGenotypeMatrix`	-
	`extractGenotypes`	-
	`isHeterozygous`	-
	`isHomozygous`	-
	`updateGenotypes`	-

Methods inherited from AromaUnitCallFile:
allocate, extractCallArray, extractCalls, extractMatrix, findUnitsTodo

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaUnitGenotypeCallSet class

Description

Package: aroma.core
Class AromaUnitGenotypeCallSet

Directly known subclasses:

public static class AromaUnitGenotypeCallSet
extends AromaUnitCallSet

An AromaUnitGenotypeCallSet object represents a set of AromaUnitGenotypeCallFiles with identical chip types.

Usage

AromaUnitGenotypeCallSet(...)
AromaUnitGenotypeCallSet(...)

Arguments

...

Arguments passed to AromaUnitCallSet.

Fields and Methods

Methods:

	`byName`	-
	`extractGenotypes`	-

Methods inherited from AromaUnitCallSet:
byPath, extractCallArray, extractCalls, extractGenotypeMatrix, findByName, findUnitsTodo

Methods inherited from AromaUnitSignalBinarySet:
byName, findByName, getAromaFullNameTranslatorSet, getAromaUgpFile, getChipType, getPlatform, validate, writeDataFrame

Methods inherited from AromaTabularBinarySet:
getDefaultFullName, getRootName, setAttributesBy, setAttributesBySampleAnnotationFile, setAttributesBySampleAnnotationSet, setAttributesByTags

Methods inherited from GenericTabularFileSet:
extractMatrix, calculateAverageColumnAcrossFiles

Author(s)

Henrik Bengtsson

The AromaUnitPscnBinaryFile class

Description

Package: aroma.core
Class AromaUnitPscnBinaryFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--ColumnNamesInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--GenericTabularFile
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaPlatformInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitSignalBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--CopyNumberDataFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitPscnBinaryFile

Directly known subclasses:

public abstract static class AromaUnitPscnBinaryFile
extends CopyNumberDataFile

An AromaUnitPscnBinaryFile is a AromaUnitSignalBinaryFile that holds total copy number signals (TCNs) and allele B fractions (BAFs). The TCNs can either be on an unknown scale or ratios relative to a reference. The signals are always stored on the original scale, i.e. they are never stored on the logaritmic scale. The BAFs are always on a [0-eps,1+eps] scale, where eps >= 0.

Usage

AromaUnitPscnBinaryFile(...)
AromaUnitPscnBinaryFile(...)

Arguments

...

Arguments passed to AromaUnitSignalBinaryFile.

Fields and Methods

Methods:

	`extractRawCopyNumbers`	-
	`hasAlleleBFractions`	-
	`hasStrandiness`	-
	`hasTotalCopyNumberRatios`	-

Methods inherited from CopyNumberDataFile:
as, as.CopyNumberDataFile, getNumberOfFilesAveraged, hasAlleleBFractions, hasStrandiness

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaUnitPscnBinarySet class

Description

Package: aroma.core
Class AromaUnitPscnBinarySet

Directly known subclasses:

public static class AromaUnitPscnBinarySet
extends CopyNumberDataSet

An AromaUnitPscnBinarySet object represents a set of AromaUnitPscnBinaryFiles with identical chip types.

Usage

AromaUnitPscnBinarySet(...)
AromaUnitPscnBinarySet(...)

Arguments

...

Arguments passed to AromaUnitSignalBinarySet.

Fields and Methods

Methods:

	`byName`	-
	`getAverageFile`	-
	`writeDataFrame`	-

Methods inherited from CopyNumberDataSet:
as, as.CopyNumberDataSet, doCBS, hasAlleleBFractions, hasStrandiness

Methods inherited from AromaUnitSignalBinarySet:
byName, findByName, getAromaFullNameTranslatorSet, getAromaUgpFile, getChipType, getPlatform, validate, writeDataFrame

Methods inherited from AromaTabularBinarySet:
getDefaultFullName, getRootName, setAttributesBy, setAttributesBySampleAnnotationFile, setAttributesBySampleAnnotationSet, setAttributesByTags

Methods inherited from GenericTabularFileSet:
extractMatrix, calculateAverageColumnAcrossFiles

Author(s)

Henrik Bengtsson

The AromaUnitSignalBinaryFile class

Description

Package: aroma.core
Class AromaUnitSignalBinaryFile

Directly known subclasses:
AromaUnitCallFile, AromaUnitFracBCnBinaryFile, AromaUnitGenotypeCallFile, AromaUnitPscnBinaryFile, AromaUnitTotalCnBinaryFile, AromaUnitTypesFile

public static class AromaUnitSignalBinaryFile
extends AromaPlatformInterface

An AromaUnitSignalBinaryFile is a AromaTabularBinaryFile.

Usage

AromaUnitSignalBinaryFile(...)
AromaUnitSignalBinaryFile(...)

Arguments

...

Arguments passed to AromaTabularBinaryFile.

Fields and Methods

Methods:

	`extractMatrix`	-
	`getChipType`	-
	`getNumberOfFilesAveraged`	-
	`getPlatform`	-
	`isAverageFile`	-
	`nbrOfUnits`	-
	`readDataFrame`	-
	`writeDataFrame`	Writes the data file as a tab-delimited text file.

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaUnitSignalBinarySet class

Description

Package: aroma.core
Class AromaUnitSignalBinarySet

Directly known subclasses:
AromaUnitCallSet, AromaUnitFracBCnBinarySet, AromaUnitGenotypeCallSet, AromaUnitPscnBinarySet, AromaUnitTotalCnBinarySet

public static class AromaUnitSignalBinarySet
extends AromaTabularBinarySet

An AromaUnitSignalBinarySet object represents a set of AromaUnitSignalBinaryFiles with identical chip types.

Usage

AromaUnitSignalBinarySet(...)
AromaUnitSignalBinarySet(...)

Arguments

...

Arguments passed to AromaTabularBinarySet.

Fields and Methods

Methods:

	`byName`	-
	`getAromaUgpFile`	-
	`getChipType`	-
	`getPlatform`	-
	`writeDataFrame`	Writes the data set as a tab-delimited text file.

Methods inherited from AromaTabularBinarySet:
getDefaultFullName, getRootName, setAttributesBy, setAttributesBySampleAnnotationFile, setAttributesBySampleAnnotationSet, setAttributesByTags

Methods inherited from GenericTabularFileSet:
extractMatrix, calculateAverageColumnAcrossFiles

Author(s)

Henrik Bengtsson

The AromaUnitTabularBinaryFile class

Description

Package: aroma.core
Class AromaUnitTabularBinaryFile

Directly known subclasses:
AromaUflFile, AromaUgcFile, AromaUgpFile, AromaUnitChromosomeTabularBinaryFile, AromaUnitGcContentFile

public abstract static class AromaUnitTabularBinaryFile
extends UnitAnnotationDataFile

A AromaUnitTabularBinaryFile is an AromaTabularBinaryFile with the constraint that the rows map one-to-one to, and in the same order as, the units in a annotation chip type file (e.g. CDF file). The (full) chip type of the annotation chip type file is given by the mandatory file footer chipType.

Usage

AromaUnitTabularBinaryFile(...)
AromaUnitTabularBinaryFile(...)

Arguments

...

Arguments passed to AromaTabularBinaryFile.

Fields and Methods

Methods:

	`byChipType`	-
	`nbrOfUnits`	-
	`writeDataFrame`	Writes the data file as a tab-delimited text file.

Methods inherited from UnitAnnotationDataFile:
byChipType, getAromaUflFile, getAromaUgpFile, getChipType, getDefaultExtension, getPlatform, nbrOfUnits

Methods inherited from AromaMicroarrayTabularBinaryFile:
allocate, as.character, byChipType, findByChipType, getChipType, getFilenameExtension, getPlatform

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaUnitTotalCnBinaryFile class

Description

Package: aroma.core
Class AromaUnitTotalCnBinaryFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--ColumnNamesInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--GenericTabularFile
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaPlatformInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitSignalBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--CopyNumberDataFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitTotalCnBinaryFile

Directly known subclasses:

public abstract static class AromaUnitTotalCnBinaryFile
extends CopyNumberDataFile

An AromaUnitTotalCnBinaryFile is a AromaUnitSignalBinaryFile.

Usage

AromaUnitTotalCnBinaryFile(...)
AromaUnitTotalCnBinaryFile(...)

Arguments

...

Arguments passed to AromaUnitSignalBinaryFile.

Fields and Methods

Methods:

	`extractPSCNArray`	-
	`extractPSCNMatrix`	-
	`extractRawCopyNumbers`	-
	`getAM`	-
	`hasAlleleBFractions`	-
	`hasStrandiness`	-

Methods inherited from CopyNumberDataFile:
as, as.CopyNumberDataFile, getNumberOfFilesAveraged, hasAlleleBFractions, hasStrandiness

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The AromaUnitTotalCnBinarySet class

Description

Package: aroma.core
Class AromaUnitTotalCnBinarySet

Directly known subclasses:

public static class AromaUnitTotalCnBinarySet
extends CopyNumberDataSet

An AromaUnitTotalCnBinarySet object represents a set of AromaUnitTotalCnBinaryFiles with identical chip types.

Usage

AromaUnitTotalCnBinarySet(...)
AromaUnitTotalCnBinarySet(...)

Arguments

...

Arguments passed to AromaUnitSignalBinarySet.

Fields and Methods

Methods:

	`as.AromaUnitTotalCnBinarySetTuple`	-
	`as.CopyNumberDataSetTuple`	-
	`byName`	-
	`exportAromaUnitPscnBinarySet`	-
	`exportTotalCnRatioSet`	-
	`extractPSCNArray`	-
	`getAverageFile`	-
	`getUnitNamesFile`	-
	`writeDataFrame`	-

Methods inherited from CopyNumberDataSet:
as, as.CopyNumberDataSet, doCBS, hasAlleleBFractions, hasStrandiness

Methods inherited from AromaUnitSignalBinarySet:
byName, findByName, getAromaFullNameTranslatorSet, getAromaUgpFile, getChipType, getPlatform, validate, writeDataFrame

Methods inherited from AromaTabularBinarySet:
getDefaultFullName, getRootName, setAttributesBy, setAttributesBySampleAnnotationFile, setAttributesBySampleAnnotationSet, setAttributesByTags

Methods inherited from GenericTabularFileSet:
extractMatrix, calculateAverageColumnAcrossFiles

Author(s)

Henrik Bengtsson

The AromaUnitTypesFile class

Description

Package: aroma.core
Class AromaUnitTypesFile

Object
~~|
~~+--FullNameInterface
~~~~~~~|
~~~~~~~+--GenericDataFile
~~~~~~~~~~~~|
~~~~~~~~~~~~+--ColumnNamesInterface
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--GenericTabularFile
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--CacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--FileCacheKeyInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaTabularBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaPlatformInterface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitSignalBinaryFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--UnitAnnotationDataFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--UnitTypesFile
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AromaUnitTypesFile

Directly known subclasses:

public static class AromaUnitTypesFile
extends UnitTypesFile

Usage

AromaUnitTypesFile(...)
AromaUnitTypesFile(...)

Arguments

...

Arguments passed to AromaUnitTabularBinaryFile.

Fields and Methods

Methods:

	`getChipType`	-
	`getPlatform`	-
	`getUnitTypes`	-
	`importFromUnitTypesFile`	-

Methods inherited from UnitTypesFile:
getUnitTypes, nbrOfUnits

Methods inherited from UnitAnnotationDataFile:
byChipType, getAromaUflFile, getAromaUgpFile, getChipType, getDefaultExtension, getPlatform, nbrOfUnits

Methods inherited from FileCacheKeyInterface:
getCacheKey

Methods inherited from CacheKeyInterface:
getCacheKey

Methods inherited from GenericTabularFile:
[, as.character, dim, extractMatrix, head, nbrOfColumns, nbrOfRows, readColumns, readDataFrame, tail, writeColumnsToFiles

Author(s)

Henrik Bengtsson

The BinnedScatter class

Description

Package: aroma.core
Class BinnedScatter

list
~~|
~~+--BinnedScatter

Directly known subclasses:

public class BinnedScatter
extends list

Usage

BinnedScatter(data=NULL, density=NULL, map=NULL, params=NULL)
BinnedScatter(data=NULL, density=NULL, map=NULL, params=NULL)

Arguments

`data`	A Nx2 `numeric` `matrix`.
`density`	...
`map`	...
`params`	A `list` of parameters.

Fields and Methods

Methods:

	`plot`	-
	`points`	-
	`reorder`	-
	`subsample`	-
	`subset`	-

Methods inherited from list:
Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, all.equal, as.CopyNumberDataSetTuple, as.data.frame, attachLocally, callHooks, coerce,ANY,list-method, exportAromaUnitPscnBinarySet, listToXml, mergeBoxplotStats, relist, type.convert, within

Author(s)

Henrik Bengtsson

Examples

# Sample scatter data
n <- 10e3
x <- rnorm(n=n)
y <- rnorm(n=n)
xy <- cbind(x=x, y=sin(x)+y/5)

# Bin data and estimate densities
xyd <- binScatter(xy)

layout(matrix(1:4, nrow=2))
par(mar=c(5,4,2,1))

# Plot data
plot(xyd, pch=1)

# Thin scatter data by subsampling
rhos <- c(1/3, 1/4, 1/6)
for (kk in seq_along(rhos)) {
  xyd2 <- subsample(xyd, size=rhos[kk])
  points(xyd2, pch=1, col=kk+1)
}

for (kk in seq_along(rhos)) {
  xyd2 <- subsample(xyd, size=rhos[kk])
  plot(xyd2, pch=1, col=kk+1)
  mtext(side=3, line=0, sprintf("Density: %.1f%%", 100*rhos[kk]))
}
# Sample scatter data
n <- 10e3
x <- rnorm(n=n)
y <- rnorm(n=n)
xy <- cbind(x=x, y=sin(x)+y/5)

# Bin data and estimate densities
xyd <- binScatter(xy)

layout(matrix(1:4, nrow=2))
par(mar=c(5,4,2,1))

# Plot data
plot(xyd, pch=1)

# Thin scatter data by subsampling
rhos <- c(1/3, 1/4, 1/6)
for (kk in seq_along(rhos)) {
  xyd2 <- subsample(xyd, size=rhos[kk])
  points(xyd2, pch=1, col=kk+1)
}

for (kk in seq_along(rhos)) {
  xyd2 <- subsample(xyd, size=rhos[kk])
  plot(xyd2, pch=1, col=kk+1)
  mtext(side=3, line=0, sprintf("Density: %.1f%%", 100*rhos[kk]))
}

The CbsModel class

Description

Package: aroma.core
Class CbsModel

Object
~~|
~~+--ChromosomalModel
~~~~~~~|
~~~~~~~+--CopyNumberChromosomalModel
~~~~~~~~~~~~|
~~~~~~~~~~~~+--CopyNumberSegmentationModel
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--CbsModel

Directly known subclasses:

public static class CbsModel
extends CopyNumberSegmentationModel

This class represents the Circular Binary Segmentation (CBS) model [1].

Usage

CbsModel(cesTuple=NULL, ..., seed=NULL)
CbsModel(cesTuple=NULL, ..., seed=NULL)

Arguments

`cesTuple`	A `CopyNumberDataSetTuple`.
`...`	Arguments passed to the constructor of `CopyNumberSegmentationModel`.
`seed`	An (optional) `integer` that if specified will (temporarily) set the random seed each time before calling the segmentation method. For more information, see `segmentByCBS`().

Fields and Methods

Methods:
No methods defined.

Methods inherited from CopyNumberSegmentationModel:
fit, getAsteriskTags, getFitFunction, getFullNames, getRegions, getTags, plot, plotCopyNumberRegionLayers, writeRegions

Methods inherited from CopyNumberChromosomalModel:
as.character, calculateChromosomeStatistics, calculateRatios, estimateSds, extractRawCopyNumbers, fit, getChromosomeLength, getDataFileMatrix, getMaxNAFraction, getNames, getOptionalArguments, getPairedNames, getRefSetTuple, getReference, getReferenceSetTuple, isPaired, newPlot, plotAxesLayers, plotChromosomesLayers, plotCytobandLayers, plotFitLayers, plotGridHorizontalLayers, plotRawCopyNumbers, plotSampleLayers, setReference

Methods inherited from ChromosomalModel:
as.character, fit, getAlias, getAromaGenomeTextFile, getAsteriskTags, getChipType, getChipTypes, getChromosomes, getFullName, getFullNames, getGenome, getGenomeData, getGenomeFile, getListOfAromaUgpFiles, getName, getNames, getParentPath, getPath, getReportPath, getRootPath, getSetTuple, getSets, getTags, indexOf, nbrOfArrays, nbrOfChipTypes, setChromosomes, setGenome

Author(s)

Henrik Bengtsson

References

[1] Olshen, A. B., Venkatraman, E. S., Lucito, R., Wigler, M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5: 557-572, 2004.
[2] Venkatraman, E. S. & Olshen, A. B. A faster circular binary segmentation algorithm for the analysis of array CGH data. Bioinformatics, 2007.

The ChromosomalModel class

Description

Package: aroma.core
Class ChromosomalModel

Object
~~|
~~+--ChromosomalModel

Directly known subclasses:
CbsModel, CopyNumberChromosomalModel, CopyNumberSegmentationModel, GladModel, HaarSegModel, RawCopyNumberModel

public abstract static class ChromosomalModel
extends Object

This abstract class represents a chromosomal model.

Usage

ChromosomalModel(cesTuple=NULL, tags="*", genome="Human", chromosomes=NULL, ...)
ChromosomalModel(cesTuple=NULL, tags="*", genome="Human", chromosomes=NULL, ...)

Arguments

`cesTuple`	A `AromaMicroarrayDataSetTuple`.
`tags`	A `character` `vector` of tags.
`genome`	A `character` string specifying what genome is process.
`chromosomes`	(optional) A `vector` specifying which chromosomes to process.
`...`	Not used.

Fields and Methods

Methods:

	`fit`	-
	`getChipType`	Gets a label for all chip types merged.
	`getChipTypes`	-
	`getChromosomes`	Gets the chromosomes to be processed.
	`getFullName`	-
	`getFullNames`	-
	`getGenome`	-
	`getName`	-
	`getNames`	Gets the names of the arrays.
	`getPath`	-
	`getSets`	-
	`getTags`	-
	`indexOf`	-
	`nbrOfArrays`	Gets the number of arrays.
	`nbrOfChipTypes`	Gets the number of chip types.
	`setChromosomes`	-
	`setGenome`	-

Requirements

This class requires genome information annotation files for every chip type.

Author(s)

Henrik Bengtsson

The ChromosomeExplorer class

Description

Package: aroma.core
Class ChromosomeExplorer

Object
~~|
~~+--Explorer
~~~~~~~|
~~~~~~~+--ChromosomeExplorer

Directly known subclasses:

public static class ChromosomeExplorer
extends Explorer

Usage

ChromosomeExplorer(model=NULL, zooms=2^(0:6), ...)
ChromosomeExplorer(model=NULL, zooms=2^(0:6), ...)

Arguments

`model`	A `CopyNumberChromosomalModel` object.
`zooms`	An positive `integer` `vector` specifying for which zoom levels the graphics should be generated.
`...`	Not used.

Fields and Methods

Methods:

	`display`	-
	`getChromosomes`	Gets the chromosomes available.
	`getFullNames`	-
	`getModel`	Gets the model.
	`getNames`	-
	`getPath`	-
	`getZooms`	-
	`indexOf`	-
	`process`	Generates image files, scripts and dynamic pages for the explorer.
	`setArrays`	Sets the arrays.
	`setCytoband`	-
	`setZooms`	-

Methods inherited from Explorer:
addIncludes, addIndexFile, as.character, display, getAlias, getArraysOfInput, getAsteriskTags, getFullName, getIncludePath, getMainPath, getName, getNameOfInput, getNames, getPath, getReportPathPattern, getRootPath, getSampleLayerPrefix, getSubname, getTags, getTagsOfInput, getTemplatePath, getVersion, nbrOfArrays, process, setAlias, setArrays, setReportPathPattern, setSubname, setup, splitByReportPathPattern, updateSetupExplorerFile

Generating PNG images

In order to get better looking graphs, but also to be able to generate bitmap images on systems without direct bitmap support, which is the case when running R in batch mode or on Unix without X11 support, images are created using the png2 device (a wrapper for bitmap() imitating png()). The png() is only used if png2(), which requires Ghostscript, does not. Note, when images are created using png2(), the images does not appear immediately, although the function call is completed, so be patient.

Author(s)

Henrik Bengtsson

Binned smoothing of a matrix column by column

Description

Binned smoothing of a matrix column by column.

Usage

## S3 method for class 'matrix'
colBinnedSmoothing(Y, x=seq_len(nrow(Y)), w=NULL, xOut=NULL, xOutRange=NULL,
  from=min(x, na.rm = TRUE), to=max(x, na.rm = TRUE), by=NULL, length.out=length(x),
  na.rm=TRUE, FUN="median", ..., verbose=FALSE)
## S3 method for class 'matrix'
colBinnedSmoothing(Y, x=seq_len(nrow(Y)), w=NULL, xOut=NULL, xOutRange=NULL,
  from=min(x, na.rm = TRUE), to=max(x, na.rm = TRUE), by=NULL, length.out=length(x),
  na.rm=TRUE, FUN="median", ..., verbose=FALSE)

Arguments

`Y`	A `numeric` JxI `matrix` (or a `vector` of length J.)
`x`	A (optional) `numeric` `vector` specifying the positions of the J entries. The default is to assume uniformly distributed positions.
`w`	A optional `numeric` `vector` of prior weights for each of the J entries.
`xOut`	Optional `numeric` `vector` of K bin center locations.
`xOutRange`	Optional Kx2 `matrix` specifying the boundary locations for K bins, where each row represents a bin $[x0,x1)$ . If not specified, the boundaries are set to be the midpoints of the bin centers, such that the bins have maximum lengths without overlapping. Vice verse, if `xOut` is not specified, then `xOut` is set to be the mid points of the `xOutRange` boundaries.
`from`, `to`, `by`, `length.out`	If neither `xOut` nor `xOutRange` is specified, the `xOut` is generated uniformly from these arguments, which specify the center location of the first and the last bin, and the distance between the center locations, utilizing the `seq`() function. Argument `length.out` can be used as an alternative to `by`, in case it specifies the total number of bins instead.
`FUN`	A `function`.
`na.rm`	If `TRUE`, missing values are excluded, otherwise not.
`...`	Not used.
`verbose`	See `Verbose`.

Details

Note that all zero-length bins $[x0,x1)$ will get result in an NA value, because such bins contain no data points. This also means that colBinnedSmoothing(Y, x=x, xOut=xOut) where xOut contains duplicated values, will result in some zero-length bins and hence NA values.

Value

Returns a numeric KxI matrix (or a vector of length K) where K is the total number of bins. The following attributes are also returned:

xOutThe center locations of each bin.
xOutRangeThe bin boundaries.
countThe number of data points within each bin (based solely on argument x).
binWidthThe average bin width.

Author(s)

Henrik Bengtsson

Examples

# Number of tracks
I <- 4

# Number of data points per track
J <- 100

# Simulate data with a gain in track 2 and 3
x <- 1:J
Y <- matrix(rnorm(I*J, sd=1/2), ncol=I)
Y[30:50,2:3] <- Y[30:50,2:3] + 3

# Uniformly distributed equal-sized bins
Ys3 <- colBinnedSmoothing(Y, x=x, from=2, by=3)
Ys5 <- colBinnedSmoothing(Y, x=x, from=3, by=5)

# Custom bins
xOutRange <- t(matrix(c(
  1, 11,
 11, 31,
 31, 41,
 41, 51,
 51, 81,
 81, 91,
 91,101
), nrow=2))
YsC <- colBinnedSmoothing(Y, x=x, xOutRange=xOutRange)

# Custom bins specified by center locations with
# maximized width relative to the neighboring bins.
xOut <- c(6, 21, 36, 46, 66, 86, 96)
YsD <- colBinnedSmoothing(Y, x=x, xOut=xOut)

xlim <- range(x)
ylim <- c(-3,5)
layout(matrix(1:I, ncol=1))
par(mar=c(3,3,1,1)+0.1, pch=19)
for (ii in 1:I) {
  plot(NA, xlim=xlim, ylim=ylim)
  points(x, Y[,ii], col="#999999")

  xOut <- attr(Ys3, "xOut")
  lines(xOut, Ys3[,ii], col=2)
  points(xOut, Ys3[,ii], col=2)

  xOut <- attr(Ys5, "xOut")
  lines(xOut, Ys5[,ii], col=3)
  points(xOut, Ys5[,ii], col=3)

  xOut <- attr(YsC, "xOut")
  lines(xOut, YsC[,ii], col=4)
  points(xOut, YsC[,ii], col=4, pch=15)

  xOut <- attr(YsD, "xOut")
  lines(xOut, YsD[,ii], col=5)
  points(xOut, YsD[,ii], col=5, pch=15)

  if (ii == 1) {
    legend("topright", pch=c(19,19,15,15), col=c(2,3,4,5),
           c("by=3", "by=5", "Custom #1", "Custom #2"), horiz=TRUE, bty="n")
  }
}


# Sanity checks
xOut <- x
YsT <- colBinnedSmoothing(Y, x=x, xOut=xOut)
stopifnot(all(YsT == Y))
stopifnot(all(attr(YsT, "counts") == 1))

xOut <- attr(YsD, "xOut")
YsE <- colBinnedSmoothing(YsD, x=xOut, xOut=xOut)
stopifnot(all(YsE == YsD))
stopifnot(all(attr(YsE, "xOutRange") == attr(YsD, "xOutRange")))
stopifnot(all(attr(YsE, "counts") == 1))

# Scramble ordering of loci
idxs <- sample(x)
x2 <- x[idxs]
Y2 <- Y[idxs,,drop=FALSE]
Y2s <- colBinnedSmoothing(Y2, x=x2, xOut=x2)
stopifnot(all(attr(Y2s, "xOut") == x2))
stopifnot(all(attr(Y2s, "counts") == 1))
stopifnot(all(Y2s == Y2))

xOut <- x[seq(from=2, to=J, by=3)]
YsT <- colBinnedSmoothing(Y, x=x, xOut=xOut)
stopifnot(all(YsT == Ys3))
stopifnot(all(attr(YsT, "counts") == 3))

xOut <- x[seq(from=3, to=J, by=5)]
YsT <- colBinnedSmoothing(Y, x=x, xOut=xOut)
stopifnot(all(YsT == Ys5))
stopifnot(all(attr(YsT, "counts") == 5))

# Number of tracks
I <- 4

# Number of data points per track
J <- 100

# Simulate data with a gain in track 2 and 3
x <- 1:J
Y <- matrix(rnorm(I*J, sd=1/2), ncol=I)
Y[30:50,2:3] <- Y[30:50,2:3] + 3

# Uniformly distributed equal-sized bins
Ys3 <- colBinnedSmoothing(Y, x=x, from=2, by=3)
Ys5 <- colBinnedSmoothing(Y, x=x, from=3, by=5)

# Custom bins
xOutRange <- t(matrix(c(
  1, 11,
 11, 31,
 31, 41,
 41, 51,
 51, 81,
 81, 91,
 91,101
), nrow=2))
YsC <- colBinnedSmoothing(Y, x=x, xOutRange=xOutRange)

# Custom bins specified by center locations with
# maximized width relative to the neighboring bins.
xOut <- c(6, 21, 36, 46, 66, 86, 96)
YsD <- colBinnedSmoothing(Y, x=x, xOut=xOut)

xlim <- range(x)
ylim <- c(-3,5)
layout(matrix(1:I, ncol=1))
par(mar=c(3,3,1,1)+0.1, pch=19)
for (ii in 1:I) {
  plot(NA, xlim=xlim, ylim=ylim)
  points(x, Y[,ii], col="#999999")

  xOut <- attr(Ys3, "xOut")
  lines(xOut, Ys3[,ii], col=2)
  points(xOut, Ys3[,ii], col=2)

  xOut <- attr(Ys5, "xOut")
  lines(xOut, Ys5[,ii], col=3)
  points(xOut, Ys5[,ii], col=3)

  xOut <- attr(YsC, "xOut")
  lines(xOut, YsC[,ii], col=4)
  points(xOut, YsC[,ii], col=4, pch=15)

  xOut <- attr(YsD, "xOut")
  lines(xOut, YsD[,ii], col=5)
  points(xOut, YsD[,ii], col=5, pch=15)

  if (ii == 1) {
    legend("topright", pch=c(19,19,15,15), col=c(2,3,4,5),
           c("by=3", "by=5", "Custom #1", "Custom #2"), horiz=TRUE, bty="n")
  }
}


# Sanity checks
xOut <- x
YsT <- colBinnedSmoothing(Y, x=x, xOut=xOut)
stopifnot(all(YsT == Y))
stopifnot(all(attr(YsT, "counts") == 1))

xOut <- attr(YsD, "xOut")
YsE <- colBinnedSmoothing(YsD, x=xOut, xOut=xOut)
stopifnot(all(YsE == YsD))
stopifnot(all(attr(YsE, "xOutRange") == attr(YsD, "xOutRange")))
stopifnot(all(attr(YsE, "counts") == 1))

# Scramble ordering of loci
idxs <- sample(x)
x2 <- x[idxs]
Y2 <- Y[idxs,,drop=FALSE]
Y2s <- colBinnedSmoothing(Y2, x=x2, xOut=x2)
stopifnot(all(attr(Y2s, "xOut") == x2))
stopifnot(all(attr(Y2s, "counts") == 1))
stopifnot(all(Y2s == Y2))

xOut <- x[seq(from=2, to=J, by=3)]
YsT <- colBinnedSmoothing(Y, x=x, xOut=xOut)
stopifnot(all(YsT == Ys3))
stopifnot(all(attr(YsT, "counts") == 3))

xOut <- x[seq(from=3, to=J, by=5)]
YsT <- colBinnedSmoothing(Y, x=x, xOut=xOut)
stopifnot(all(YsT == Ys5))
stopifnot(all(attr(YsT, "counts") == 5))

Kernel smoothing of a matrix column by column

Description

Kernel smoothing of a matrix column by column.

Usage

## S3 method for class 'matrix'
colKernelSmoothing(Y, x=seq_len(nrow(Y)), w=NULL, xOut=x,
  kernel=c("gaussian", "uniform"), h, censorH=3, na.rm=TRUE, robust=FALSE, ...,
  verbose=FALSE)
## S3 method for class 'matrix'
colKernelSmoothing(Y, x=seq_len(nrow(Y)), w=NULL, xOut=x,
  kernel=c("gaussian", "uniform"), h, censorH=3, na.rm=TRUE, robust=FALSE, ...,
  verbose=FALSE)

Arguments

`Y`	A `numeric` JxI `matrix` (or a `vector` of length J.)
`x`	A (optional) `numeric` `vector` specifying the positions of the J entries. The default is to assume uniformly distributed positions.
`w`	A optional `numeric` `vector` of prior weights for each of the J entries.
`xOut`	A `numeric` `vector` specifying K target positions where the kernel is applied.
`kernel`	A `character` string or a `function` specifying the kernel used.
`h`	A single positive `numeric` specifying the bandwidth of the kernel.
`censorH`	A single positive `numeric` specifying the where to truncate the kernel. If `Inf`, no truncation is done.
`na.rm`	If `TRUE`, missing values are excluded, otherwise not.
`robust`	If `TRUE`, robust estimators are used, otherwise not.
`...`	Not used.
`verbose`	See `Verbose`.

Value

Returns a numeric KxI matrix (or a vector of length K).

Author(s)

Henrik Bengtsson

Examples

J <- 100
I <- 4
Y <- matrix(rnorm(I*J, sd=1/2), ncol=I)
# Introduce a gain in column 2 and 3
Y[30:50,2:3] <- Y[30:50,2:3] + 3
x <- 1:J

xOut <- x
Ys1 <- colKernelSmoothing(Y, x=x, xOut=xOut, kernel="gaussian", h=1)
Ys5 <- colKernelSmoothing(Y, x=x, xOut=xOut, kernel="gaussian", h=5)

xlim <- range(c(x,xOut))
ylim <- c(-3,5)
layout(matrix(1:I, ncol=1))
par(mar=c(3,3,1,1)+0.1, pch=19)
for (ii in 1:I) {
  plot(NA, xlim=xlim, ylim=ylim)
  points(x, Y[,ii], col="#999999")
  lines(xOut, Ys1[,ii], col=2)
  points(xOut, Ys1[,ii], col=2)
  lines(xOut, Ys5[,ii], col=3)
  points(xOut, Ys5[,ii], col=3)
}
J <- 100
I <- 4
Y <- matrix(rnorm(I*J, sd=1/2), ncol=I)
# Introduce a gain in column 2 and 3
Y[30:50,2:3] <- Y[30:50,2:3] + 3
x <- 1:J

xOut <- x
Ys1 <- colKernelSmoothing(Y, x=x, xOut=xOut, kernel="gaussian", h=1)
Ys5 <- colKernelSmoothing(Y, x=x, xOut=xOut, kernel="gaussian", h=5)

xlim <- range(c(x,xOut))
ylim <- c(-3,5)
layout(matrix(1:I, ncol=1))
par(mar=c(3,3,1,1)+0.1, pch=19)
for (ii in 1:I) {
  plot(NA, xlim=xlim, ylim=ylim)
  points(x, Y[,ii], col="#999999")
  lines(xOut, Ys1[,ii], col=2)
  points(xOut, Ys1[,ii], col=2)
  lines(xOut, Ys5[,ii], col=3)
  points(xOut, Ys5[,ii], col=3)
}

The CopyNumberChromosomalModel class

Description

Package: aroma.core
Class CopyNumberChromosomalModel

Object
~~|
~~+--ChromosomalModel
~~~~~~~|
~~~~~~~+--CopyNumberChromosomalModel

Directly known subclasses:
CbsModel, CopyNumberSegmentationModel, GladModel, HaarSegModel, RawCopyNumberModel

public abstract static class CopyNumberChromosomalModel
extends ChromosomalModel

This abstract class represents a copy-number model.

Usage

CopyNumberChromosomalModel(cesTuple=NULL, refTuple=NULL, calculateRatios=TRUE, tags="*",
  genome="Human", chromosomes=NULL, maxNAFraction=1/5, ...)
CopyNumberChromosomalModel(cesTuple=NULL, refTuple=NULL, calculateRatios=TRUE, tags="*",
  genome="Human", chromosomes=NULL, maxNAFraction=1/5, ...)

Arguments

`cesTuple`	A `CopyNumberDataSetTuple`.
`refTuple`	An optional `CopyNumberDataFile`, or `CopyNumberDataSet` or `CopyNumberDataSetTuple` for pairwise comparisons.
`calculateRatios`	A `logical` specifying whether ratios should be calculated relative to the reference. If `FALSE`, argument `refTuple` is ignored.
`tags`	A `character` `vector` of tags.
`genome`	A `character` string specifying what genome is process.
`chromosomes`	(optional) A `vector` specifying which chromosomes to process.
`maxNAFraction`	A `double` in [0,1] indicating how many non-finite signals are allowed in the sanity checks of the data.
`...`	Optional arguments that may be used by some of the subclass models.

Fields and Methods

Methods:

	`extractRawCopyNumbers`	Extracts relative copy numbers.
	`fit`	Fits the model.
	`getChromosomeLength`	-
	`getNames`	-
	`getReference`	-
	`isPaired`	-

Requirements

This class requires genome information annotation files for every chip type.

Author(s)

Henrik Bengtsson

The CopyNumberSegmentationModel class

Description

Package: aroma.core
Class CopyNumberSegmentationModel

Object
~~|
~~+--ChromosomalModel
~~~~~~~|
~~~~~~~+--CopyNumberChromosomalModel
~~~~~~~~~~~~|
~~~~~~~~~~~~+--CopyNumberSegmentationModel

Directly known subclasses:
CbsModel, GladModel, HaarSegModel

public abstract static class CopyNumberSegmentationModel
extends CopyNumberChromosomalModel

This abstract class represents a copy-number segmentation model.

Usage

CopyNumberSegmentationModel(...)
CopyNumberSegmentationModel(...)

Arguments

...

Arguments passed to constructor CopyNumberChromosomalModel.

Fields and Methods

Methods:

	`fit`	Fits the model.
	`getFullNames`	-
	`getRegions`	-
	`getTags`	-
	`plot`	-
	`writeRegions`	-

Author(s)

Henrik Bengtsson

Performs Circular Binary Segmentation (CBS) on a data set

Description

Performs Circular Binary Segmentation (CBS) on a data set for one or more chip types.

Usage

  ## Default S3 method:
doCBS(dataSet, tags=NULL, chipTypes, arrays=NULL, ..., verbose=FALSE)
  ## S3 method for class 'CopyNumberDataSet'
doCBS(ds, arrays=NULL, ...)
  ## S3 method for class 'CopyNumberDataSetTuple'
doCBS(dsTuple, arrays=NULL, ..., verbose=FALSE)
## Default S3 method:
doCBS(dataSet, tags=NULL, chipTypes, arrays=NULL, ..., verbose=FALSE)
  ## S3 method for class 'CopyNumberDataSet'
doCBS(ds, arrays=NULL, ...)
  ## S3 method for class 'CopyNumberDataSetTuple'
doCBS(dsTuple, arrays=NULL, ..., verbose=FALSE)

Arguments

`ds`, `dsTuple`, `dataSet`	A `CopyNumberDataSet`, a `CopyNumberDataSetTuple` or a `character` string with the name of one of them.
`tags`	An optional `character` `vector` of data set tags (only when `dataSet` is specified).
`chipTypes`	A `character` `vector` specifying the chip types for the different data sets (only when `dataSet` is specified).
`arrays`	An optional `vector` specifying the subset of arrays to process.
`...`	Additional arguments passed to `CbsModel` and its `fit()` method.
`verbose`	A `logical` or `Verbose`.

Value

Returns the output dataset of CbsModel.

Author(s)

Henrik Bengtsson

Examples

## Not run: 
 
dataSet <- "GSE20939"
tags <- "ACC,-XY,BPN,-XY,RMA,FLN,-XY"
chipTypes <- c("Mapping250K_Nsp", "Mapping250K_Sty")
fit <- doCBS(dataSet, tags=tags, chipTypes=chipTypes, verbose=-10)
print(fit)


## End(Not run)## Not run: 
 
dataSet <- "GSE20939"
tags <- "ACC,-XY,BPN,-XY,RMA,FLN,-XY"
chipTypes <- c("Mapping250K_Nsp", "Mapping250K_Sty")
fit <- doCBS(dataSet, tags=tags, chipTypes=chipTypes, verbose=-10)
print(fit)


## End(Not run)

The Explorer class

Description

Package: aroma.core
Class Explorer

Object
~~|
~~+--Explorer

Directly known subclasses:
ChromosomeExplorer

public abstract static class Explorer
extends Object

Usage

Explorer(tags="*", version="0", ...)
Explorer(tags="*", version="0", ...)

Arguments

`tags`	A `character` `vector` of tags to be added to the output path.
`version`	An optional `character` string.
`...`	Not used.

Fields and Methods

Methods:

	`display`	Displays the explorer in the default browser.
	`getFullName`	-
	`getName`	Gets the name of the explorer.
	`getNames`	Gets the names of the input samples.
	`getPath`	Gets the path of the output directory.
	`getRootPath`	Gets the root path of the output directory.
	`getTags`	Gets the tags of the explorer.
	`getVersion`	-
	`nbrOfArrays`	Gets the total number of arrays.
	`process`	Generates image files, scripts and dynamic pages for the explorer.
	`setArrays`	Sets the arrays.

Output directory structure

The main directory of an Explorer report is reports/<name>/<subname>/. The <name> is typically the same as the name of the input data set, and the <subname> is typically the tags of ditto. This main directory is where main HTML document is stored.

For each chip type, real or "virtual" (combined), there is a subdirectory with the same name as the chip type, i.e. reports/<name>/<subname>/<chiptype>/.

For each chip type directory, there are set of subdirectories each specifying a so called image layer, e.g. an image layer showing the raw data, another containing the estimates of a model fit and so on. Path format: reports/<name>/<subname>/<chiptype>/<image layer>/. In this directory all image files are stored, e.g. PNG files.

In some cases one do not want to all input tags to become part of the subname, but instead for instance use those to name the image layer(s). In such cases one has to override the default names.

Author(s)

Henrik Bengtsson

The GladModel class

Description

Package: aroma.core
Class GladModel

Directly known subclasses:

public static class GladModel
extends CopyNumberSegmentationModel

This class represents the Gain and Loss Analysis of DNA regions (GLAD) model [1]. This class can model chip-effect estimates obtained from multiple chip types, and not all samples have to be available on all chip types.

Usage

GladModel(cesTuple=NULL, ...)
GladModel(cesTuple=NULL, ...)

Arguments

`cesTuple`	A `CopyNumberDataSetTuple`.
`...`	Arguments passed to the constructor of `CopyNumberSegmentationModel`.

Details

Data from multiple chip types are combined "as is". This is based on the assumption that the relative chip effect estimates are non-biased (or at the equally biased across chip types). Note that in GLAD there is no way to down weight certain data points, which is why we can control for differences in variance across chip types.

Fields and Methods

Methods:

	`writeRegions`	-

Methods inherited from CopyNumberSegmentationModel:
fit, getAsteriskTags, getFitFunction, getFullNames, getRegions, getTags, plot, plotCopyNumberRegionLayers, writeRegions

Benchmarking

In high-density copy numbers analysis, the most time consuming step is fitting the GLAD model. The complexity of the model grows more than linearly (squared? exponentially?) with the number of data points in the chromosome and sample being fitted. This is why it take much more than twice the time to fit two chip types together than separately.

Author(s)

Henrik Bengtsson

References

[1] Hupe P et al. Analysis of array CGH data: from signal ratio to gain and loss of DNA regions. Bioinformatics, 2004, 20, 3413-3422.

The HaarSegModel class

Description

Package: aroma.core
Class HaarSegModel

Directly known subclasses:

public static class HaarSegModel
extends CopyNumberSegmentationModel

This class represents the Haar wavelet-based segmentation (HaarSeg) model [1].

Usage

HaarSegModel(cesTuple=NULL, ..., breaksFdrQ=1e-04)
HaarSegModel(cesTuple=NULL, ..., breaksFdrQ=1e-04)

Arguments

`cesTuple`	A `CopyNumberDataSetTuple`.
`breaksFdrQ`	Default tuning parameters specific to the HaarSeg algorithm.
`...`	Arguments passed to the constructor of `CopyNumberSegmentationModel`.

Fields and Methods

Methods:
No methods defined.

Methods inherited from CopyNumberSegmentationModel:
fit, getAsteriskTags, getFitFunction, getFullNames, getRegions, getTags, plot, plotCopyNumberRegionLayers, writeRegions

Author(s)

Henrik Bengtsson

References

[1] Ben-Yaacov E. and Eldar YC. A fast and flexible method for the segmentation of aCGH data, Bioinformatics, 2008. https://webee.technion.ac.il/Sites/People/YoninaEldar/software_det1.php

The NonPairedPSCNData class

Description

Package: aroma.core
Class NonPairedPSCNData

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--AbstractCNData
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--AbstractPSCNData
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--NonPairedPSCNData

Directly known subclasses:

public class NonPairedPSCNData
extends AbstractPSCNData

A NonPairedPSCNData object holds parent-specific copy number data. Two NonPairedPSCNData objects for a matched tumor-normal pair can be combined into a PairedPSCNData object.

Usage

NonPairedPSCNData(chromosome=NULL, x=NULL, isSNP=NULL, mu=NULL, C=NULL, beta=NULL, ...)
NonPairedPSCNData(chromosome=NULL, x=NULL, isSNP=NULL, mu=NULL, C=NULL, beta=NULL, ...)

Arguments

`C`	A `numeric` `vector` of J tumor total copy number (TCN) ratios in [0,+`Inf`) (due to noise, small negative values are also allowed). The TCN ratios are typically scaled such that copy-neutral diploid loci have a mean of two.
`beta`	A `numeric` `vector` of J tumor allele B fractions (BAFs) in [0,1] (due to noise, values may be slightly outside as well) or `NA` for non-polymorphic loci.
`mu`	An optional `numeric` `vector` of J genotype calls in {0,1/2,1} for AA, AB, and BB, respectively, and `NA` for non-polymorphic loci. If not given, they are estimated from the normal BAFs using `callNaiveGenotypes` as described in [2].
`isSNP`	An optional `logical` `vector` of length J specifying whether each locus is a SNP or not (non-polymorphic loci).
`chromosome`	(Optional) An `integer` scalar (or a `vector` of length J), which can be used to specify which chromosome each locus belongs to in case multiple chromosomes are segments. This argument is also used for annotation purposes.
`x`	Optional `numeric` `vector` of J genomic locations. If `NULL`, index locations `1:J` are used.
`...`	Optional named locus-specific signal `vector`s of length J.

Fields and Methods

Methods:

	`as`	-
	`as.NonPairedPSCNData`	-
	`as.PairedPSCNData`	-
	`callNaiveGenotypes`	-
	`callSegmentationOutliers`	-
	`dropSegmentationOutliers`	-
	`getSignalColumnNames`	-
	`segmentByCBS`	-

Methods inherited from AbstractPSCNData:
callSNPs, getSNPFields

Methods inherited from AbstractCNData:
findLargeGaps, getChipType, getLocusData, getPlatform, hasKnownPositions, orderAlongGenome, setChipType, setPlatform

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The PairedPSCNData class

Description

Package: aroma.core
Class PairedPSCNData

Directly known subclasses:

public class PairedPSCNData
extends AbstractPSCNData

A PairedPSCNData object holds paired tumor-normal parent-specific copy number data.

Usage

PairedPSCNData(chromosome=NULL, x=NULL, isSNP=NULL, muN=NULL, CT=NULL, betaT=NULL,
  CN=NULL, betaN=NULL, ...)
PairedPSCNData(chromosome=NULL, x=NULL, isSNP=NULL, muN=NULL, CT=NULL, betaT=NULL,
  CN=NULL, betaN=NULL, ...)

Arguments

`CT`	A `numeric` `vector` of J tumor total copy number (TCN) ratios in [0,+`Inf`) (due to noise, small negative values are also allowed). The TCN ratios are typically scaled such that copy-neutral diploid loci have a mean of two.
`CN`	An optional `numeric` `vector` of J normal TCN ratios.
`betaT`	A `numeric` `vector` of J tumor allele B fractions (BAFs) in [0,1] (due to noise, values may be slightly outside as well) or `NA` for non-polymorphic loci.
`betaN`	A `numeric` `vector` of J matched normal BAFs in [0,1] (due to noise, values may be slightly outside as well) or `NA` for non-polymorphic loci.
`muN`	An optional `numeric` `vector` of J genotype calls in {0,1/2,1} for AA, AB, and BB, respectively, and `NA` for non-polymorphic loci. If not given, they are estimated from the normal BAFs using `callNaiveGenotypes` as described in [2].
`isSNP`	An optional `logical` `vector` of length J specifying whether each locus is a SNP or not (non-polymorphic loci).
`chromosome`	(Optional) An `integer` scalar (or a `vector` of length J), which can be used to specify which chromosome each locus belongs to in case multiple chromosomes are segments. This argument is also used for annotation purposes.
`x`	Optional `numeric` `vector` of J genomic locations. If `NULL`, index locations `1:J` are used.
`...`	Optional named locus-specific signal `vector`s of length J.

Fields and Methods

Methods:

	`as`	-
	`as.PairedPSCNData`	-
	`callNaiveGenotypes`	-
	`callSegmentationOutliers`	-
	`dropSegmentationOutliers`	-
	`getSignalColumnNames`	-
	`getTCNs`	-
	`getTotalCopyNumbers`	-
	`normalizeTumorBoost`	-
	`plotTracks`	-
	`segmentByCBS`	-
	`segmentByPairedPSCBS`	-

Methods inherited from AbstractPSCNData:
callSNPs, getSNPFields

Methods inherited from AbstractCNData:
findLargeGaps, getChipType, getLocusData, getPlatform, hasKnownPositions, orderAlongGenome, setChipType, setPlatform

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The ParametersInterface class interface

Description

Package: aroma.core
Class ParametersInterface

Interface
~~|
~~+--ParametersInterface

Directly known subclasses:
AromaTransform

public class ParametersInterface
extends Interface

Usage

ParametersInterface(...)
ParametersInterface(...)

Arguments

...

Not used.

Fields and Methods

Methods:

	`getParameters`	-
	`getParametersAsString`	-

Methods inherited from Interface:
extend, print, uses

Author(s)

Henrik Bengtsson

The RawAlleleBFractions class

Description

Package: aroma.core
Class RawAlleleBFractions

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--RawAlleleBFractions

Directly known subclasses:
RawMirroredAlleleBFractions, SegmentedAlleleBFractions

public class RawAlleleBFractions
extends RawGenomicSignals

Usage

RawAlleleBFractions(...)
RawAlleleBFractions(...)

Arguments

...

Arguments passed to RawGenomicSignals.

Fields and Methods

Methods:

	`extractRawMirroredAlleleBFractions`	-
	`plot`	-

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The RawCopyNumberModel class

Description

Package: aroma.core
Class RawCopyNumberModel

Object
~~|
~~+--ChromosomalModel
~~~~~~~|
~~~~~~~+--CopyNumberChromosomalModel
~~~~~~~~~~~~|
~~~~~~~~~~~~+--RawCopyNumberModel

Directly known subclasses:

public abstract static class RawCopyNumberModel
extends CopyNumberChromosomalModel

This class represents an identity copy-number model which returns the input as is.

Usage

RawCopyNumberModel(...)
RawCopyNumberModel(...)

Arguments

...

Passed to the constructor of the superclass.

Fields and Methods

Methods:
No methods defined.

Author(s)

Henrik Bengtsson

The RawCopyNumbers class

Description

Package: aroma.core
Class RawCopyNumbers

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--RawCopyNumbers

Directly known subclasses:
SegmentedCopyNumbers

public class RawCopyNumbers
extends RawGenomicSignals

Usage

RawCopyNumbers(cn=NULL, ...)
RawCopyNumbers(cn=NULL, ...)

Arguments

`cn`	A `numeric` `vector` of length J specifying the copy number at each loci.
`...`	Arguments passed to `RawGenomicSignals`.

Fields and Methods

Methods:

	`cnRange`	-
	`extractRawCopyNumbers`	-
	`getSignals`	-
	`plot`	-

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

Examples

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Simulating copy-number data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Number of loci
J <- 1000

mu <- double(J)
mu[200:300] <- mu[200:300] + 1
mu[650:800] <- mu[650:800] - 1
eps <- rnorm(J, sd=1/2)
y <- mu + eps
x <- sort(runif(length(y), max=length(y)))


cn <- RawCopyNumbers(y, x)
print(cn)

cn2 <- extractSubset(cn, subset=xSeq(cn, by=5))
print(cn2)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Plot along genome
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, ylim=c(-3,3))
title(main="Complete and subsetted loci")
points(cn2, col="red", pch=176, cex=2)

legend("topright", pch=c(19,176), col=c("#999999", "red"),
       sprintf(c("raw [n=%d]", "every 5th [n=%d]"),
               c(nbrOfLoci(cn), nbrOfLoci(cn2))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Binned smoothing
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Binned smoothing")

cnSa <- binnedSmoothing(cn, by=3)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- binnedSmoothing(cn, by=9)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "Bin(w=3) [n=%d]", "Bin(w=9) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Binned smoothing (by count)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Binned smoothing (by count)")

cnSa <- binnedSmoothing(cn, by=3, byCount=TRUE)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- binnedSmoothing(cn, by=9, byCount=TRUE)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "BinO(w=3) [n=%d]", "BinO(w=9) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Kernel smoothing (default is Gaussian)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Kernel smoothing w/ Gaussian kernel")

cnSa <- kernelSmoothing(cn, h=2)
points(cnSa, col="blue")

cnSb <- kernelSmoothing(cn, h=5)
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "N(.,sd=2) [n=%d]", "N(.,sd=5) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Kernel smoothing
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Kernel smoothing w/ uniform kernel")

xOut <- xSeq(cn, by=10)
cnSa <- kernelSmoothing(cn, xOut=xOut, kernel="uniform", h=2)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- kernelSmoothing(cn, xOut=xOut, kernel="uniform", h=5)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "U(w=2) [n=%d]", "U(w=5) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Simulating copy-number data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Number of loci
J <- 1000

mu <- double(J)
mu[200:300] <- mu[200:300] + 1
mu[650:800] <- mu[650:800] - 1
eps <- rnorm(J, sd=1/2)
y <- mu + eps
x <- sort(runif(length(y), max=length(y)))


cn <- RawCopyNumbers(y, x)
print(cn)

cn2 <- extractSubset(cn, subset=xSeq(cn, by=5))
print(cn2)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Plot along genome
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, ylim=c(-3,3))
title(main="Complete and subsetted loci")
points(cn2, col="red", pch=176, cex=2)

legend("topright", pch=c(19,176), col=c("#999999", "red"),
       sprintf(c("raw [n=%d]", "every 5th [n=%d]"),
               c(nbrOfLoci(cn), nbrOfLoci(cn2))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Binned smoothing
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Binned smoothing")

cnSa <- binnedSmoothing(cn, by=3)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- binnedSmoothing(cn, by=9)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "Bin(w=3) [n=%d]", "Bin(w=9) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Binned smoothing (by count)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Binned smoothing (by count)")

cnSa <- binnedSmoothing(cn, by=3, byCount=TRUE)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- binnedSmoothing(cn, by=9, byCount=TRUE)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "BinO(w=3) [n=%d]", "BinO(w=9) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Kernel smoothing (default is Gaussian)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Kernel smoothing w/ Gaussian kernel")

cnSa <- kernelSmoothing(cn, h=2)
points(cnSa, col="blue")

cnSb <- kernelSmoothing(cn, h=5)
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "N(.,sd=2) [n=%d]", "N(.,sd=5) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Kernel smoothing
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Kernel smoothing w/ uniform kernel")

xOut <- xSeq(cn, by=10)
cnSa <- kernelSmoothing(cn, xOut=xOut, kernel="uniform", h=2)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- kernelSmoothing(cn, xOut=xOut, kernel="uniform", h=5)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "U(w=2) [n=%d]", "U(w=5) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")

The RawGenomicSignals class

Description

Package: aroma.core
Class RawGenomicSignals

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals

Directly known subclasses:
AbstractCNData, AbstractPSCNData, NonPairedPSCNData, PairedPSCNData, RawAlleleBFractions, RawCopyNumbers, RawMirroredAlleleBFractions, RawSequenceReads, SegmentedAlleleBFractions, SegmentedCopyNumbers

public class RawGenomicSignals
extends RichDataFrame

Usage

RawGenomicSignals(y=NULL, x=NULL, w=NULL, chromosome=0L, name=NULL, ...)
RawGenomicSignals(y=NULL, x=NULL, w=NULL, chromosome=0L, name=NULL, ...)

Arguments

`y`	A `numeric` `vector` of length J specifying the signal at each locus.
`x`	A (optional) `numeric` `vector` of length J specifying the position of each locus.
`w`	A (optional) non-negative `numeric` `vector` of length J specifying a weight of each locus.
`chromosome`	An (optional) `integer` specifying the chromosome for these genomic signals.
`name`	An (optional) `character` string specifying the sample name.
`...`	Not used.

Fields and Methods

Methods:

	`*`	-
	`+`	-
	`-`	-
	`addBy`	-
	`append`	-
	`as.data.frame`	-
	`binnedSmoothing`	-
	`divideBy`	-
	`drawDensity`	-
	`estimateStandardDeviation`	-
	`gaussianSmoothing`	-
	`getChromosome`	-
	`getChromosomes`	-
	`getPositions`	-
	`getSigma`	-
	`getSignals`	-
	`getWeights`	-
	`getXScale`	-
	`getYScale`	-
	`hasWeights`	-
	`kernelSmoothing`	-
	`lines`	-
	`multiplyBy`	-
	`nbrOfChromosomes`	-
	`nbrOfLoci`	-
	`plot`	-
	`points`	-
	`segmentByCBS`	-
	`segmentByGLAD`	-
	`segmentByHaarSeg`	-
	`segmentByMPCBS`	-
	`setSigma`	-
	`setSignals`	-
	`setWeights`	-
	`setXScale`	-
	`setYScale`	-
	`signalRange`	-
	`sort`	-
	`subtractBy`	-
	`xMax`	-
	`xMin`	-
	`xRange`	-
	`xSeq`	-
	`yMax`	-
	`yMin`	-
	`yRange`	-

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The RawMirroredAlleleBFractions class

Description

Package: aroma.core
Class RawMirroredAlleleBFractions

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--RawAlleleBFractions
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--RawMirroredAlleleBFractions

Directly known subclasses:

public class RawMirroredAlleleBFractions
extends RawAlleleBFractions

Usage

RawMirroredAlleleBFractions(...)
RawMirroredAlleleBFractions(...)

Arguments

...

Arguments passed to RawAlleleBFractions.

Fields and Methods

Methods:

	`plot`	-

Methods inherited from RawAlleleBFractions:
extractRawMirroredAlleleBFractions, plot

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.profileCGH, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The RawSequenceReads class

Description

Package: aroma.core
Class RawSequenceReads

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--RawSequenceReads

Directly known subclasses:

public class RawSequenceReads
extends RawGenomicSignals

Usage

RawSequenceReads(x=NULL, y=rep(1L, length(x)), ...)
RawSequenceReads(x=NULL, y=rep(1L, length(x)), ...)

Arguments

`x`	An `integer` `vector` of length J specifying the read positions.
`y`	An (optional) `integer` `vector` of length J specifying the number of reads at each position. Default is one read per position.
`...`	Arguments passed to `RawGenomicSignals`.

Fields and Methods

Methods:

	`binnedSums`	-
	`extractRawCopyNumbers`	-
	`nbrOfReads`	-
	`plot`	-

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.profileCGH, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The SegmentedAlleleBFractions class

Description

Package: aroma.core
Class SegmentedAlleleBFractions

Directly known subclasses:

public class SegmentedAlleleBFractions
extends SegmentedGenomicSignalsInterface

Usage

SegmentedAlleleBFractions(..., states=NULL)
SegmentedAlleleBFractions(..., states=NULL)

Arguments

`...`	Arguments passed to `RawAlleleBFractions`.
`states`	A `function` returning the copy-number states given a `vector` of locus positions.

Fields and Methods

Methods:
No methods defined.

Methods inherited from SegmentedGenomicSignalsInterface:
as.data.frame, binnedSmoothingByState, extractSubsetByState, findChangePointsByState, getStateColorMap, getStateColors, getStates, getUniqueStates, getVirtualField, getVirtualLocusFields, kernelSmoothingByState, plot, points, setStateColorMap, setStates

Methods inherited from RawAlleleBFractions:
extractRawMirroredAlleleBFractions, plot

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.profileCGH, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

The SegmentedCopyNumbers class

Description

Package: aroma.core
Class SegmentedCopyNumbers

data.frame
~~|
~~+--RichDataFrame
~~~~~~~|
~~~~~~~+--RawGenomicSignals
~~~~~~~~~~~~|
~~~~~~~~~~~~+--RawCopyNumbers
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--SegmentedGenomicSignalsInterface
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--SegmentedCopyNumbers

Directly known subclasses:

public class SegmentedCopyNumbers
extends SegmentedGenomicSignalsInterface

Usage

SegmentedCopyNumbers(..., states=NULL)
SegmentedCopyNumbers(..., states=NULL)

Arguments

`...`	Arguments passed to `RawCopyNumbers`.
`states`	A `function` returning the copy-number states given a `vector` of locus positions.

Fields and Methods

Methods:
No methods defined.

Methods inherited from RawCopyNumbers:
cnRange, extractRawCopyNumbers, getCNs, getCn, getSignals, plot

Methods inherited from data.frame:
$<-,data.frame-method, $<-, Math, Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, Ops, Summary, [, [<-,data.frame-method, [<-, [[, [[<-,data.frame-method, [[<-, aggregate, anyDuplicated, anyNA, as.NonPairedPSCNData, as.PairedPSCNData, as.data.frame, as.list, as.matrix, as.profileCGH, as.vector, attachLocally, by, callSegmentationOutliers, cbind, coerce,ANY,list-method, coerce,oldClass,S3-method, dim, dimnames, dimnames<-, dropSegmentationOutliers, droplevels, duplicated, edit, findLargeGaps, format, formula, head, initialize,oldClass-method, is.na, merge, na.exclude, na.omit, plot, plotDensity, print, prompt, rbind, row.names, row.names<-, rowsum, segmentByCBS, segmentByPairedPSCBS, show,oldClass-method, slotsFromS3,data.frame-method, split, split<-, stack, str, subset, summary, t, tail, transform, type.convert, unique, unstack, unwrap, within, wrap, writeDataFrame, xtfrm

Author(s)

Henrik Bengtsson

Examples

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Simulating copy-number data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# True CN states
stateFcn <- function(x, ...) {
  states <- integer(length(x))
  states[200 <=x & x <= 300] <- -1L
  states[650 <=x & x <= 800] <- +1L
  states
}

# Number of loci
J <- 1000

y <- rnorm(J, sd=1/2)
x <- 1:length(y)
for (state in c(-1,+1)) {
  idxs <- (stateFcn(x) == state)
  y[idxs] <- y[idxs] + state
}


cn <- SegmentedCopyNumbers(y, x, states=stateFcn)
print(cn)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Subsetting
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, ylim=c(-4,4))
title("Copy numbers annotated by state (and subset by state)")

cnS <- extractSubsetByState(cn, states=c(0,+1L))
print(cnS)
points(cnS, pch=21, cex=1.2, lwd=2, col="purple")

legend("topright", pch=c(19, 21), col=c("#999999", "purple"),
       sprintf(c("raw [n=%d]", "CN in {0,1} [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnS))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Kernel smoothing stratified by state
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Kernel smoothing stratified by state w/ Gaussian kernel")

cnSa <- kernelSmoothingByState(cn, h=2)
points(cnSa, col="blue")

cnSb <- kernelSmoothingByState(cn, h=5)
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "N(.,sd=2) [n=%d]", "N(.,sd=5) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Binned smoothing stratified by state
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Binned smoothing stratified by state")

cnSa <- binnedSmoothingByState(cn, by=3, verbose=-1)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- binnedSmoothingByState(cn, by=9, verbose=-1)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "Bin(w=3) [n=%d]", "Bin(w=9) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Simulating copy-number data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# True CN states
stateFcn <- function(x, ...) {
  states <- integer(length(x))
  states[200 <=x & x <= 300] <- -1L
  states[650 <=x & x <= 800] <- +1L
  states
}

# Number of loci
J <- 1000

y <- rnorm(J, sd=1/2)
x <- 1:length(y)
for (state in c(-1,+1)) {
  idxs <- (stateFcn(x) == state)
  y[idxs] <- y[idxs] + state
}


cn <- SegmentedCopyNumbers(y, x, states=stateFcn)
print(cn)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Subsetting
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, ylim=c(-4,4))
title("Copy numbers annotated by state (and subset by state)")

cnS <- extractSubsetByState(cn, states=c(0,+1L))
print(cnS)
points(cnS, pch=21, cex=1.2, lwd=2, col="purple")

legend("topright", pch=c(19, 21), col=c("#999999", "purple"),
       sprintf(c("raw [n=%d]", "CN in {0,1} [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnS))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Kernel smoothing stratified by state
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Kernel smoothing stratified by state w/ Gaussian kernel")

cnSa <- kernelSmoothingByState(cn, h=2)
points(cnSa, col="blue")

cnSb <- kernelSmoothingByState(cn, h=5)
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "N(.,sd=2) [n=%d]", "N(.,sd=5) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Binned smoothing stratified by state
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plot(cn, col="#999999", ylim=c(-3,3))
title(main="Binned smoothing stratified by state")

cnSa <- binnedSmoothingByState(cn, by=3, verbose=-1)
lines(cnSa, col="blue")
points(cnSa, col="blue")

cnSb <- binnedSmoothingByState(cn, by=9, verbose=-1)
lines(cnSb, col="red")
points(cnSb, col="red")

legend("topright", pch=19, col=c("#999999", "blue", "red"),
       sprintf(c("raw [n=%d]", "Bin(w=3) [n=%d]", "Bin(w=9) [n=%d]"),
       c(nbrOfLoci(cn), nbrOfLoci(cnSa), nbrOfLoci(cnSb))), bty="n")

The SegmentedGenomicSignalsInterface class interface

Description

Package: aroma.core
Class SegmentedGenomicSignalsInterface

Interface
~~|
~~+--SegmentedGenomicSignalsInterface

Directly known subclasses:
SegmentedAlleleBFractions, SegmentedCopyNumbers

public class SegmentedGenomicSignalsInterface
extends Interface

Usage

SegmentedGenomicSignalsInterface(...)
SegmentedGenomicSignalsInterface(...)

Arguments

...

Not used.

Fields and Methods

Methods:

	`as.data.frame`	-
	`binnedSmoothingByState`	-
	`extractSubsetByState`	-
	`findChangePointsByState`	-
	`getStateColorMap`	-
	`getStateColors`	-
	`getStates`	-
	`getUniqueStates`	-
	`kernelSmoothingByState`	-
	`plot`	-
	`points`	-
	`setStateColorMap`	-
	`setStates`	-

Methods inherited from Interface:
extend, print, uses

Author(s)

Henrik Bengtsson

The UnitAnnotationDataFile interface class

Description

Package: aroma.core
Class UnitAnnotationDataFile

Interface
~~|
~~+--UnitAnnotationDataFile

Directly known subclasses:
AromaUflFile, AromaUgcFile, AromaUgpFile, AromaUnitChromosomeTabularBinaryFile, AromaUnitGcContentFile, AromaUnitTabularBinaryFile, AromaUnitTypesFile, TextUnitNamesFile, UnitNamesFile, UnitTypesFile

public static class UnitAnnotationDataFile
extends Interface

A UnitAnnotationDataFile provides methods for querying certain types of chip type annotation data by units.

Usage

UnitAnnotationDataFile(...)
UnitAnnotationDataFile(...)

Arguments

...

Arguments passed to Interface.

Methods

Methods:

	`byChipType`	-
	`getAromaUflFile`	-
	`getAromaUgpFile`	-
	`getChipType`	-
	`getPlatform`	-
	`nbrOfUnits`	-

Methods inherited from Interface:
extend, print, uses

Author(s)

Henrik Bengtsson

The UnitNamesFile interface class

Description

Package: aroma.core
Class UnitNamesFile

Interface
~~|
~~+--UnitAnnotationDataFile
~~~~~~~|
~~~~~~~+--UnitNamesFile

Directly known subclasses:
TextUnitNamesFile

public abstract static class UnitNamesFile
extends UnitAnnotationDataFile

A UnitNamesFile provides methods for querying the unit names of a given chip type.

Usage

UnitNamesFile(...)
UnitNamesFile(...)

Arguments

...

Arguments passed to UnitAnnotationDataFile.

Methods

Methods:

	`getUnitNames`	-
	`indexOf`	-
	`nbrOfUnits`	-

Methods inherited from UnitAnnotationDataFile:
byChipType, getAromaUflFile, getAromaUgpFile, getChipType, getDefaultExtension, getPlatform, nbrOfUnits

Methods inherited from Interface:
extend, print, uses

Author(s)

Henrik Bengtsson

The UnitTypesFile interface class

Description

Package: aroma.core
Class UnitTypesFile

Interface
~~|
~~+--UnitAnnotationDataFile
~~~~~~~|
~~~~~~~+--UnitTypesFile

Directly known subclasses:
AromaUnitTypesFile

public abstract static class UnitTypesFile
extends UnitAnnotationDataFile

A UnitTypesFile provides methods for querying the unit types of a given chip type, e.g. genotyping or copy-number unit, exon unit etc.

Usage

UnitTypesFile(...)
UnitTypesFile(...)

Arguments

...

Arguments passed to UnitAnnotationDataFile.

Methods

Methods:

	`getUnitTypes`	-
	`nbrOfUnits`	-

Methods inherited from UnitAnnotationDataFile:
byChipType, getAromaUflFile, getAromaUgpFile, getChipType, getDefaultExtension, getPlatform, nbrOfUnits

Methods inherited from Interface:
extend, print, uses

The aroma unit-type map

unknown=0, expression=1, genotyping=2, resequencing=3, tag=4, copynumber=5, genotypingcontrol=6, expressioncontrol=7

Author(s)

Henrik Bengtsson

Package 'aroma.core'

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