| Title: | CGHbase: Base functions and classes for arrayCGH data analysis. |
|---|---|
| Description: | Contains functions and classes that are needed by arrayCGH packages. |
| Authors: | Sjoerd Vosse, Mark van de Wiel |
| Maintainer: | Mark van de Wiel <[email protected]> |
| License: | GPL |
| Version: | 1.65.0 |
| Built: | 2024-07-23 05:29:12 UTC |
| Source: | https://github.com/bioc/CGHbase |
CGHbase: Base functions and classes for arrayCGH data analysis.
Main infrastructural classes: cghRaw, cghSeg, cghCall.
Full help on methods and associated functions is available from withing class help pages.
Attached data sets: Wilting, WiltingRaw, WiltingNorm, WiltingSeg, WiltingCalled.
Sjoerd Vosse <[email protected]>
This function accesses the regions information
stored in the featureData of an object derived from the cghRegions-class.
avedist(object) nclone(object)avedist(object) nclone(object)
object |
Object derived from class |
avedist returns a vector containing the Average L1-distance of clone signatures to the medoid signature;
nclone returns a vector containing the number of clones that is included in each region;
Sjoerd Vosse
Container for aCGH data and experimental
metadata. cghCall class is derived from
eSet, and requires the following matrices of equal dimension
as assayData members:
copynumber
segmented
calls
probloss
probnorm
probgain
Furthermore, columns named Chromosome, Start, and End are
required as featureData members, containing feature position information.
Directly extends class eSet.
new('cghCall',
phenoData = [AnnotatedDataFrame],
experimentData = [MIAME],
annotation = [character],
copynumber = [matrix],
segmented = [matrix],
calls = [matrix],
probloss = [matrix],
probnorm = [matrix],
probgain = [matrix],
featureData = [AnnotatedDataFrame],
...)
An object of class cghCall is generally obtained as output
from CGHcall.
Inherited from eSet:
assayData:Contains matrices with equal
dimensions, and with column number equal to
nrow(phenoData). assayData must contain the following matrices
copynumber
segmented
calls
probloss
probnorm
probgain
with rows represening array probes
and columns representing samples. Additional matrices of
identical size (e.g., representing measurement errors) may
also be included in assayData. Class:AssayData-class
phenoData:See eSet
featureData:An AnnotatedDataFrame with columns
Chromosome, Start, and End containing array element position
data.
experimentData:See eSet
annotation:See eSet
Class-specific methods.
copynumber(cghCall), copynumber(cghCall,matrix)<-
Access and
set elements named copynumber in the AssayData-class
slot.
segmented(cghCall), segmented(cghCall,matrix)<-
Access and
set elements named segmented in the AssayData-class
slot.
calls(cghCall), calls(cghCall,matrix)<-
Access and
set elements named calls in the AssayData-class
slot.
probloss(cghCall), probloss(cghCall,matrix)<-
Access and
set elements named probloss in the AssayData-class
slot.
probnorm(cghCall), probnorm(cghCall,matrix)<-
Access and
set elements named probnorm in the AssayData-class
slot.
probgain(cghCall), probgain(cghCall,matrix)<-
Access and
set elements named probgain in the AssayData-class
slot.
chromosomes, bpstart, bpend
Access the chromosomal positions stored in featureData
Create a plot containing log2ratios, segments and call probabilities ordered by chromosomal position. EXTRA OPTIONS PLUS DEFAULTS: dotres=10. Every dotres-th log2-ratio is plotted. dotres=1 plots all data. However, higher values save a lot of space and allow quicker browsing of the plots. ylimit=c(-5,5): limits of the y-axis. gaincol='green'; losscol='red';ampcol="darkgreen";dlcol="darkred": Colors used for gain, loss (bars) and amplifications, double loss (tick marks). build='GRCh37': build of humun genome used for determining positions of centromeres
Create a plot summarizing the call probabilities of all samples
Create a frequency plot summarizing the calls of all samples
See eSet for derived methods.
Sjoerd Vosse
eSet-class, cghRaw-class, cghSeg-class
# create an instance of cghCall new("cghCall") # create an instance of cghCall through \code{\link{ExpandCGHcall}} ## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) perc.tumor <- rep(0.75, 3) listcalled <- CGHcall(segmented,cellularity=perc.tumor) called <- ExpandCGHcall(listcalled,segmented) # plot the first sample. Default only every 10th log2-ratio is plotted (dotres=10). Adjust using dotres= option below. plot(called[,1]) # plot the first chromosome of the first sample plot(called[chromosomes(called)==1,1]) # get the copynumber values of the third and fourth sample log2ratios <- copynumber(called[,3:4]) # get the names of the samples sampleNames(called) # get the names of the array elements featureNames(called) ## End(Not run)# create an instance of cghCall new("cghCall") # create an instance of cghCall through \code{\link{ExpandCGHcall}} ## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) perc.tumor <- rep(0.75, 3) listcalled <- CGHcall(segmented,cellularity=perc.tumor) called <- ExpandCGHcall(listcalled,segmented) # plot the first sample. Default only every 10th log2-ratio is plotted (dotres=10). Adjust using dotres= option below. plot(called[,1]) # plot the first chromosome of the first sample plot(called[chromosomes(called)==1,1]) # get the copynumber values of the third and fourth sample log2ratios <- copynumber(called[,3:4]) # get the names of the samples sampleNames(called) # get the names of the array elements featureNames(called) ## End(Not run)
Container for aCGH data and experimental
metadata. cghRaw class is derived from
eSet, and requires a matrix named copynumber as
assayData member. Furthermore, columns named Chromosome, Start, and End
are required as featureData members, containing feature position information.
Directly extends class eSet.
new('cghRaw',
phenoData = [AnnotatedDataFrame],
experimentData = [MIAME],
annotation = [character],
copynumber = [matrix],
featureData = [AnnotatedDataFrame],
...)
make_cghRaw is a function to convert a dataframe or textfile to
an object of class cghRaw. The input should be either a dataframe
or a tabseparated textfile (textfiles must contain a header). The first
three columns should contain the name, chromosome and position in bp for
each array target respectively. The chromosome and position column must
contain numbers only. Following these is a column with log2 ratios for
each of your samples. If the input type is a textfile, missing values
should be represented as 'NA' or an empty field.
Inherited from eSet:
assayData:Contains matrices with equal
dimensions, and with column number equal to
nrow(phenoData). assayData must contain a matrix
copynumber with rows represening array probes
and columns representing samples. Additional matrices of
identical size (e.g., representing measurement errors) may
also be included in assayData. Class:AssayData-class
phenoData:See eSet
featureData:An AnnotatedDataFrame with columns
Chromosome, Start, and End containing array element position
data.
experimentData:See eSet
annotation:See eSet
Class-specific methods.
copynumber(cghRaw), copynumber(cghRaw,matrix)<-
Access and
set elements named copynumber in the AssayData-class
slot.
chromosomes, bpstart, bpend
Access the chromosomal positions stored in featureData
Create a plot containing log2ratios ordered by chromosomal position
See eSet for derived methods. Annotation functionality is not yet supported.
Sjoerd Vosse
eSet-class, cghSeg-class, cghCall-class
# create an instance of cghRaw new("cghRaw") # create an instance of cghRaw from a dataframe data(Wilting) rawcgh <- make_cghRaw(Wilting) # plot the first sample plot(rawcgh[,1]) # first three chromosomes plot(rawcgh[chromosomes(rawcgh)==1,1]) # get the copynumber values of the third and fourth sample log2ratios <- copynumber(rawcgh[,3:4]) # get the names of the samples sampleNames(rawcgh) # get the names of the array elements featureNames(rawcgh)# create an instance of cghRaw new("cghRaw") # create an instance of cghRaw from a dataframe data(Wilting) rawcgh <- make_cghRaw(Wilting) # plot the first sample plot(rawcgh[,1]) # first three chromosomes plot(rawcgh[chromosomes(rawcgh)==1,1]) # get the copynumber values of the third and fourth sample log2ratios <- copynumber(rawcgh[,3:4]) # get the names of the samples sampleNames(rawcgh) # get the names of the array elements featureNames(rawcgh)
Container for aCGH regions data and experimental
metadata. cghRegions class is derived from
eSet, and requires a matrix named regions as
assayData member. Furthermore, columns named Chromosome, Start, End,
Nclone, and Avedist are required as featureData members, containing region
and position information.
Directly extends class eSet.
new('cghRegions',
phenoData = [AnnotatedDataFrame],
experimentData = [MIAME],
annotation = [character],
regions = [matrix],
featureData = [AnnotatedDataFrame],
...)
An object of this class is generally obtained by running the function CGHregions.
Inherited from eSet:
assayData:Contains matrices with equal
dimensions, and with column number equal to
nrow(phenoData). assayData must contain a matrix
regions with rows represening regions
and columns representing samples. Additional matrices of
identical size (e.g., representing measurement errors) may
also be included in assayData. Class:AssayData
phenoData:See eSet
featureData:An AnnotatedDataFrame with columns
Chromosome, Start, End, Nclone, and Avedist containing region
and position information.
experimentData:See eSet
annotation:See eSet
Class-specific methods.
regions(cghRegions), regions(cghRegions,matrix)<-
Access and
set elements named regions in the AssayData-class
slot.
chromosomes, bpstart, bpend, nclone, avedist
Access the region and position
information stored in featureData
Create a plot displaying chromosomes on the Y-axis and base pair position on the X-axis. A new region is displayed by a slight jump with respect to the previous region. Each region is displayed as a bi-colored segment, the lower and upper part of which correspond to the proportions pl and pg of samples with a loss (red) or gain (green), respectively. The color coding is displayed as well: 1: pl (pg) < 10%; 2: 10% = pl (pg) < 30%; 3:30% = pl (pg) < 50%; 4: pl (pg) = 50%.
Create a frequency plot
See eSet for derived methods. Annotation functionality is not yet supported.
Sjoerd Vosse
eSet, cghRaw-class, cghSeg-class, cghCall-class
# create an instance of cghRegions new("cghRegions") # load an instance of cghRegions data(WiltingRegions) # plot all region data plot(WiltingRegions) # make a frequency plot frequencyPlot(WiltingRegions) # extract the region values values <- regions(WiltingRegions) # get the names of the samples sampleNames(WiltingRegions)# create an instance of cghRegions new("cghRegions") # load an instance of cghRegions data(WiltingRegions) # plot all region data plot(WiltingRegions) # make a frequency plot frequencyPlot(WiltingRegions) # extract the region values values <- regions(WiltingRegions) # get the names of the samples sampleNames(WiltingRegions)
Container for aCGH data and experimental
metadata. cghSeg class is derived from
eSet, and requires a matrix named copynumber as well as a
matrix named segmented as assayData members of equal dimensions.
Furthermore, columns named Chromosome, Start, and End are
required as featureData members, containing feature position information.
Directly extends class eSet.
new('cghSeg',
phenoData = [AnnotatedDataFrame],
experimentData = [MIAME],
annotation = [character],
copynumber = [matrix],
segmented = [matrix],
featureData = [AnnotatedDataFrame],
...)
An object of class cghSeg is generally obtained as output
from segmentData.
Inherited from eSet:
assayData:Contains matrices with equal
dimensions, and with column number equal to
nrow(phenoData). assayData must contain matrices
copynumber and segmented with rows represening array probes
and columns representing samples. Additional matrices of
identical size (e.g., representing measurement errors) may
also be included in assayData. Class:AssayData-class
phenoData:See eSet
featureData:An AnnotatedDataFrame with columns
Chromosome, Start, and End containing array element position
data.
experimentData:See eSet
annotation:See eSet
Class-specific methods.
copynumber(cghSeg), copynumber(cghSeg,matrix)<-
Access and
set elements named copynumber in the AssayData-class
slot.
segmented(cghSeg), segmented(cghSeg,matrix)<-
Access and
set elements named segmented in the AssayData-class
slot.
chromosomes, bpstart, bpend
Access the chromosomal positions stored in featureData
Create a plot containing log2ratios and segments ordered by chromosomal position. TWO EXTRA OPTIONS PLUS DEFAULTS: dotres=10. Every dotres-th log2-ratio is plotted. dotres=1 plots all data. However, higher values save a lot of space and allow quicker browsing of the plots. ylimit=c(-2,5): limits of the y-axis
See eSet for derived methods.
Sjoerd Vosse
eSet-class, cghRaw-class, cghCall-class
# create an instance of cghSeg new("cghSeg") # create an instance of cghSeg through \code{segmentData} ## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) # plot the first sample. Default only every 10th log2-ratio is plotted (dotres=10). Adjust using dotres= option below. plot(segmented[,1]) # first three chromosomes plot(segmented[chromosomes(segmented)<=3,1]) # get the copynumber values of the third and fourth sample log2ratios <- copynumber(segmented[,3:4]) # get the names of the samples sampleNames(segmented) # get the names of the array elements featureNames(segmented) ## End(Not run)# create an instance of cghSeg new("cghSeg") # create an instance of cghSeg through \code{segmentData} ## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) # plot the first sample. Default only every 10th log2-ratio is plotted (dotres=10). Adjust using dotres= option below. plot(segmented[,1]) # first three chromosomes plot(segmented[chromosomes(segmented)<=3,1]) # get the copynumber values of the third and fourth sample log2ratios <- copynumber(segmented[,3:4]) # get the names of the samples sampleNames(segmented) # get the names of the array elements featureNames(segmented) ## End(Not run)
These generic functions access the position data
stored in the featureData of an object derived from the cghRaw-class,
cghSeg-class or cghCall-class.
chromosomes(object) bpstart(object) bpend(object)chromosomes(object) bpstart(object) bpend(object)
object |
Object derived from class |
chromosomes returns a vector of chromosome numbers;
bpstart returns a vector of basepair start positions;
bpend returns a vector of basepair end positions;
Sjoerd Vosse
cghRaw-class, cghSeg-class, cghCall-class
These generic functions access the copynumber values
of assay data stored in an object derived from the cghRaw-class,
cghSeg-class or cghCall-class.
copynumber(object) copynumber(object) <- value segmented(object) segmented(object) <- value calls(object) calls(object) <- valuecopynumber(object) copynumber(object) <- value segmented(object) segmented(object) <- value calls(object) calls(object) <- value
object |
Object derived from class |
value |
Matrix with rows representing features and columns samples. |
copynumber returns a matrix of copynumber values;
Sjoerd Vosse
cghRaw-class, cghSeg-class, cghCall-class
data(WiltingCalled) log2ratios <- copynumber(WiltingCalled) segments <- segmented(WiltingCalled) calls <- calls(WiltingCalled)data(WiltingCalled) log2ratios <- copynumber(WiltingCalled) segments <- segmented(WiltingCalled) calls <- calls(WiltingCalled)
This function creates a frequency plot for aCGH regions.
frequencyPlot(x, y, ...)frequencyPlot(x, y, ...)
x |
An object of class |
y |
This argument is not used and should be missing. |
... |
Arguments |
We find plotted on the x-axis the array probes sorted by chromosomal position. The vertical bars represent the frequency of gains and losses across your samples. The black bars represent gains, the gray bars represent losses.
This function creates a plot.
Mark van de Wiel and Sjoerd Vosse
Mark A. van de Wiel and Wessel N. van Wieringen (2007). CGHregions: Dimension Reduction for Array CGH Data with Minimal Information Loss. Cancer Informatics, 2, 55-63.
## Not run: data(WiltingRegions) frequencyPlot(WiltingRegions) ## End(Not run)## Not run: data(WiltingRegions) frequencyPlot(WiltingRegions) ## End(Not run)
This function creates a frequency plot for aCGH profiles.
frequencyPlotCalls(x,main='Frequency Plot', gaincol='blue', losscol='red', misscol=NA, build='GRCh37', ...)frequencyPlotCalls(x,main='Frequency Plot', gaincol='blue', losscol='red', misscol=NA, build='GRCh37', ...)
x |
An object of class |
main |
Title of plot |
gaincol |
Color to use for gains |
losscol |
Color to use for losses |
misscol |
Missings |
build |
Build of Humane Genome.Either |
... |
Arguments |
We find plotted on the x-axis the array probes sorted by chromosomal position. The vertical bars represent the frequency of gains or losses.
This function creates a plot.
Sjoerd Vosse & Mark van de Wiel
Mark A. van de Wiel, Kyung In Kim, Sjoerd J. Vosse, Wessel N. van Wieringen, Saskia M. Wilting and Bauke Ylstra. CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics, 23, 892-894.
## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) called <- CGHcall(segmented,cellularity= rep(0.75, 3)) frequencyPlotCalls(called) ## End(Not run)## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) called <- CGHcall(segmented,cellularity= rep(0.75, 3)) frequencyPlotCalls(called) ## End(Not run)
This function converts a dataframe of appropriote format to an object of class cghRaw.
make_cghRaw(input)make_cghRaw(input)
input |
Either a dataframe or character string containing a filename. See details for the format. |
The input should be either a dataframe or a tabseparated textfile (textfiles must contain a header). The first four columns should contain the name, chromosome and the start and end position in bp for each array target respectively. The chromosome and position column must contain numbers only. Following these is a column with log2 ratios for each of your samples. If the input type is a textfile, missing values should be represented as 'NA' or an empty field.
This function returns an object of class cghRaw-class.
Sjoerd Vosse & Mark van de Wiel
data(Wilting) ## Convert to \code{\link{cghRaw}} object cgh <- make_cghRaw(Wilting)data(Wilting) ## Convert to \code{\link{cghRaw}} object cgh <- make_cghRaw(Wilting)
Please see the class descriptions for more details on the plot functions.
## S3 method for class 'cghRaw' plot(x, y, ...) ## S3 method for class 'cghSeg' plot(x, y, ...) ## S3 method for class 'cghCall' plot(x, y, ...) ## S3 method for class 'cghRegions' plot(x, y, ...)## S3 method for class 'cghRaw' plot(x, y, ...) ## S3 method for class 'cghSeg' plot(x, y, ...) ## S3 method for class 'cghCall' plot(x, y, ...) ## S3 method for class 'cghRegions' plot(x, y, ...)
x |
|
y |
This argument is not used and should be missing. |
... |
Arguments |
Sjoerd Vosse
cghRaw-class, cghSeg-class, cghCall-class, cghRegions-class
These generic functions access the call probabilities from assay data
stored in a object derived from the cghCall-class.
probdloss(object) probdloss(object) <- value probloss(object) probloss(object) <- value probnorm(object) probnorm(object) <- value probgain(object) probgain(object) <- value probamp(object) probamp(object) <- valueprobdloss(object) probdloss(object) <- value probloss(object) probloss(object) <- value probnorm(object) probnorm(object) <- value probgain(object) probgain(object) <- value probamp(object) probamp(object) <- value
object |
Object derived from class |
value |
Matrix with rows representing features and columns samples. |
probloss returns matrix of call probabilities;
Sjoerd Vosse
This function accesses the regions values
of assay data stored in an object derived from the cghRegions-class.
regions(object) regions(object) <- valueregions(object) regions(object) <- value
object |
Object derived from class |
value |
Matrix with rows representing features and columns samples. |
regions returns a matrix of regions values;
Sjoerd Vosse
This function creates a summary plot for aCGH profiles.
summaryPlot(x,main='Summary Plot', gaincol='blue', losscol='red', misscol=NA, build='GRCh37', ...)summaryPlot(x,main='Summary Plot', gaincol='blue', losscol='red', misscol=NA, build='GRCh37', ...)
x |
An object of class |
main |
Title of plot |
gaincol |
Color to use for gains |
losscol |
Color to use for losses |
misscol |
Missings |
build |
Build of Humane Genome.Either |
... |
Arguments |
We find plotted on the x-axis the array probes sorted by chromosomal position. The vertical bars represent the average probability that the positions they cover are gained (green bars) or lost (red bars). The green bars represent gains, the red bars represent losses.
This function creates a plot.
Sjoerd Vosse & Mark van de Wiel
Mark A. van de Wiel, Kyung In Kim, Sjoerd J. Vosse, Wessel N. van Wieringen, Saskia M. Wilting and Bauke Ylstra. CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics, 23, 892-894.
## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) called <- CGHcall(segmented,cellularity= rep(0.75, 3)) summaryPlot(called) ## End(Not run)## Not run: data(Wilting) rawcgh <- make_cghSeg(Wilting) normalized <- normalize(rawcgh) segmented <- segmentData(normalized) called <- CGHcall(segmented,cellularity= rep(0.75, 3)) summaryPlot(called) ## End(Not run)
A dataframe containing 4709 rows and 8 columns with arrayCGH data.
WiltingWilting
A dataframe containing the following 8 columns:
The unique identifiers of array elements.
Chromosome number of each array element.
Chromosomal position in bp of each array element.
Raw log2 ratios for cervical cancer sample AdCA10.
Raw log2 ratios for cervical cancer sample SCC27.
Raw log2 ratios for cervical cancer sample SCC32.
Raw log2 ratios for cervical cancer sample SCC36.
Raw log2 ratios for cervical cancer sample SCC39.
Wilting, S.M., Snijders, P.J., Meijer, G.A., Ylstra, B., van den IJssel, P.R., Snijders, A.M., Albertson, D.G., Coffa, J., Schouten, J.P., van de Wiel, M.A., Meijer, C.J., & Steenbergen, R.D. (2006). Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. Journal of Pathology, 210, 258-259.
Cervical cancer arrayCGH data called with CGHcall with default settings, containing 3552 features for 5 samples.
WiltingCalledWiltingCalled
An object of class cghCall
Wilting, S.M., Snijders, P.J., Meijer, G.A., Ylstra, B., van den IJssel, P.R., Snijders, A.M., Albertson, D.G., Coffa, J., Schouten, J.P., van de Wiel, M.A., Meijer, C.J., & Steenbergen, R.D. (2006). Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. Journal of Pathology, 210, 258-259.
Mark A. van de Wiel, Kyung In Kim, Sjoerd J. Vosse, Wessel N. van Wieringen, Saskia M. Wilting and Bauke Ylstra. CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics, 23, 892-894.
Normalized log2 ratios frm cervical cancer arrayCGH data, containing 3552 features for 5 samples. These data have been normalized using the normalize function with default settings.
WiltingCalledWiltingCalled
An object of class cghRaw.
Wilting, S.M., Snijders, P.J., Meijer, G.A., Ylstra, B., van den IJssel, P.R., Snijders, A.M., Albertson, D.G., Coffa, J., Schouten, J.P., van de Wiel, M.A., Meijer, C.J., & Steenbergen, R.D. (2006). Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. Journal of Pathology, 210, 258-259.
Raw log2 ratios from cervical cancer arrayCGH data, containing 3552 features for 5 samples. These data have been preprocessed using preprocess.
WiltingCalledWiltingCalled
An object of class cghRaw.
Wilting, S.M., Snijders, P.J., Meijer, G.A., Ylstra, B., van den IJssel, P.R., Snijders, A.M., Albertson, D.G., Coffa, J., Schouten, J.P., van de Wiel, M.A., Meijer, C.J., & Steenbergen, R.D. (2006). Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. Journal of Pathology, 210, 258-259.
Regions of cervical cancer arrayCGH data as defined by CGHregions with default settings, containing 90 regions over 5 samples.
WiltingRegionsWiltingRegions
An object of class cghRegions
Wilting, S.M., Snijders, P.J., Meijer, G.A., Ylstra, B., van den IJssel, P.R., Snijders, A.M., Albertson, D.G., Coffa, J., Schouten, J.P., van de Wiel, M.A., Meijer, C.J., & Steenbergen, R.D. (2006). Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. Journal of Pathology, 210, 258-259.
Mark A. van de Wiel and Wessel N. van Wieringen (2007). CGHregions: Dimension Reduction for Array CGH Data with Minimal Information Loss. Cancer Informatics, 2, 55-63.
Segmented log2 ratios from cervical cancer arrayCGH data, containing 3552 features for 5 samples. These data have been segmented using segmentData with default settings.
WiltingCalledWiltingCalled
An object of class cghSeg.
Wilting, S.M., Snijders, P.J., Meijer, G.A., Ylstra, B., van den IJssel, P.R., Snijders, A.M., Albertson, D.G., Coffa, J., Schouten, J.P., van de Wiel, M.A., Meijer, C.J., & Steenbergen, R.D. (2006). Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. Journal of Pathology, 210, 258-259.