CRAN Package Check Results for Package aroma.core

Last updated on 2018-04-23 23:51:11 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 3.1.1 23.42 115.15 138.57 ERROR
r-devel-linux-x86_64-debian-gcc 3.1.1 19.92 102.49 122.41 ERROR
r-devel-linux-x86_64-fedora-clang 3.1.1 212.11 NOTE
r-devel-linux-x86_64-fedora-gcc 3.1.1 205.02 NOTE
r-devel-windows-ix86+x86_64 3.1.1 64.00 151.00 215.00 NOTE
r-devel-osx-x86_64 3.1.1 NOTE
r-patched-linux-x86_64 3.1.1 24.09 132.73 156.82 ERROR
r-patched-solaris-x86 3.1.1 254.30 NOTE
r-release-linux-x86_64 3.1.1 22.12 131.64 153.76 ERROR
r-release-windows-ix86+x86_64 3.1.1 16.00 294.00 310.00 NOTE
r-release-osx-x86_64 3.1.1 NOTE
r-oldrel-windows-ix86+x86_64 3.1.1 16.00 157.00 173.00 NOTE

Check Details

Version: 3.1.1
Check: package dependencies
Result: NOTE
    Packages suggested but not available for checking:
     ‘sfit’ ‘expectile’ ‘HaarSeg’ ‘mpcbs’
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 3.1.1
Check: examples
Result: ERROR
    Running examples in ‘aroma.core-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: segmentByCBS.RawGenomicSignals
    > ### Title: Segment copy numbers using the CBS method
    > ### Aliases: segmentByCBS.RawGenomicSignals RawGenomicSignals.segmentByCBS
    > ### segmentByCBS,RawGenomicSignals-method
    > ### Keywords: internal methods IO
    >
    > ### ** Examples
    >
    > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    > # Simulating copy-number data
    > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    > # Number of loci
    > J <- 500
    >
    > mu <- double(J)
    > mu[100:150] <- mu[100:150] + 1
    > mu[320:400] <- mu[320:400] - 1
    > eps <- rnorm(J, sd=1/2)
    > y <- mu + eps
    > x <- sort(runif(length(y), max=length(y))) * 1e5
    > w <- runif(J)
    > w[320:400] <- 0.001
    >
    >
    > cn <- RawCopyNumbers(y, x)
    > print(cn)
    RawCopyNumbers:
    Name: <none>
    Number of rows: 500
    Number of columns: 3
    Columns: chromosome [numeric], x [numeric], cn [numeric]
    Chromosomes: 0 [1]
    Number of loci: 500
    Position range: [82113.1,4.98136e+07]
    Mean distance between loci: 99662.3
    >
    > plot(cn, ylim=c(-3,3), col="#aaaaaa", xlab="Position (Mb)")
    >
    > cnS <- binnedSmoothing(cn, by=500e3)
    > print(cnS)
    RawCopyNumbers:
    Name: <none>
    Number of rows: 100
    Number of columns: 3
    Columns: chromosome [numeric], x [numeric], cn [numeric]
    Chromosomes: [0]
    Number of loci: 100
    > lines(cnS, col="black", lwd=3)
    >
    >
    > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    > # Segment
    > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    > legend <- c()
    >
    > if (require("DNAcopy")) {
    + fit <- segmentByCBS(cn)
    + cnr <- extractCopyNumberRegions(fit)
    + print(cnr)
    + drawLevels(cnr, col="red", lwd=3)
    + legend <- c(legend, red="CBS")
    + }
    Loading required package: DNAcopy
    CopyNumberRegions:
    Number of regions: 5
    >
    > if (require("GLAD") && packageVersion("GLAD") != "9.9.9") {
    + fit <- segmentByGLAD(cn)
    + cnr <- extractCopyNumberRegions(fit)
    + print(cnr)
    + drawLevels(cnr, col="blue", lwd=3)
    + legend <- c(legend, blue="GLAD")
    + }
    Loading required package: GLAD
    
    ######################################################################################
    
    Have fun with GLAD
    
    For smoothing it is possible to use either
    the AWS algorithm (Polzehl and Spokoiny, 2002,
    or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
    If you use the package with AWS, please cite:
    Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,
    
    If you use the package with HaarSeg, please cite:
    Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
    For fast computation it is recommanded to use
    the daglad function with smoothfunc=haarseg
    
    ######################################################################################
    
    New options are available in daglad: see help for details.
    
    Error in UseMethod("as.profileCGH") :
     no applicable method for 'as.profileCGH' applied to an object of class "data.frame"
    Calls: segmentByGLAD -> segmentByGLAD.RawGenomicSignals -> <Anonymous>
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 3.1.1
Check: tests
Result: ERROR
     Running ‘PairedPSCNData,SEG.R’ [0s/0s]
     Running ‘PairedPSCNData.R’ [0s/0s]
     Running ‘RawCopyNumbers,states.R’ [2s/2s]
     Running ‘RawCopyNumbers.R’ [2s/2s]
     Running ‘RawGenomicSignals.R’ [1s/1s]
     Running ‘RawGenomicSignals.SEG,MP.R’ [1s/1s]
     Running ‘RawGenomicSignals.SEG.R’ [1s/1s]
    Running the tests in ‘tests/RawGenomicSignals.SEG.R’ failed.
    Complete output:
     > library("aroma.core")
     Loading required package: R.utils
     Loading required package: R.oo
     Loading required package: R.methodsS3
     R.methodsS3 v1.7.1 (2016-02-15) successfully loaded. See ?R.methodsS3 for help.
     R.oo v1.22.0 (2018-04-21) successfully loaded. See ?R.oo for help.
    
     Attaching package: 'R.oo'
    
     The following objects are masked from 'package:methods':
    
     getClasses, getMethods
    
     The following objects are masked from 'package:base':
    
     attach, detach, gc, load, save
    
     R.utils v2.6.0 (2017-11-04) successfully loaded. See ?R.utils for help.
    
     Attaching package: 'R.utils'
    
     The following object is masked from 'package:utils':
    
     timestamp
    
     The following objects are masked from 'package:base':
    
     cat, commandArgs, getOption, inherits, isOpen, parse, warnings
    
     Loading required package: R.filesets
     R.filesets v2.12.1 successfully loaded. See ?R.filesets for help.
    
     Attaching package: 'R.filesets'
    
     The following objects are masked from 'package:R.utils':
    
     extract, validate
    
     The following objects are masked from 'package:base':
    
     append, readLines
    
     Loading required package: R.devices
     R.devices v2.15.1 (2016-11-09) successfully loaded. See ?R.devices for help.
     aroma.core v3.1.1 (2017-09-12) successfully loaded. See ?aroma.core for help.
    
     Attaching package: 'aroma.core'
    
     The following objects are masked from 'package:base':
    
     .Machine, colMeans, colSums, library, require, write
    
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Simulating copy-number data
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Number of loci
     > J <- 500
     >
     > mu <- double(J)
     > mu[100:150] <- mu[100:150] + 1
     > mu[320:400] <- mu[320:400] - 1
     > eps <- rnorm(J, sd=1/2)
     > y <- mu + eps
     > x <- sort(runif(length(y), max=length(y))) * 1e5;
     > w <- runif(J)
     > w[320:400] <- 0.001
     >
     >
     > cn <- RawCopyNumbers(y, x)
     > print(cn)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 500
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: 0 [1]
     Number of loci: 500
     Position range: [40110.2,4.99912e+07]
     Mean distance between loci: 100102
     >
     > plot(cn, ylim=c(-3,3), col="#aaaaaa", xlab="Position (Mb)")
     >
     > cnS <- binnedSmoothing(cn, by=500e3)
     > print(cnS)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 100
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: [0]
     Number of loci: 100
     > lines(cnS, col="black", lwd=3)
     >
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Segment
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > legend <- c()
     >
     > if (require("DNAcopy")) {
     + fit <- segmentByCBS(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="red", lwd=3)
     + legend <- c(legend, red="CBS")
     + }
     Loading required package: DNAcopy
     CopyNumberRegions:
     Number of regions: 5
     >
     > if (require("GLAD") && packageVersion("GLAD") != "9.9.9") {
     + fit <- segmentByGLAD(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="blue", lwd=3)
     + legend <- c(legend, blue="GLAD")
     + }
     Loading required package: GLAD
    
     ######################################################################################
    
     Have fun with GLAD
    
     For smoothing it is possible to use either
     the AWS algorithm (Polzehl and Spokoiny, 2002,
     or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     If you use the package with AWS, please cite:
     Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,
    
     If you use the package with HaarSeg, please cite:
     Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     For fast computation it is recommanded to use
     the daglad function with smoothfunc=haarseg
    
     ######################################################################################
    
     New options are available in daglad: see help for details.
    
     Error in UseMethod("as.profileCGH") :
     no applicable method for 'as.profileCGH' applied to an object of class "data.frame"
     Calls: segmentByGLAD -> segmentByGLAD.RawGenomicSignals -> <Anonymous>
     Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 3.1.1
Check: tests
Result: ERROR
     Running ‘PairedPSCNData,SEG.R’ [0s/1s]
     Running ‘PairedPSCNData.R’ [0s/1s]
     Running ‘RawCopyNumbers,states.R’ [1s/2s]
     Running ‘RawCopyNumbers.R’ [2s/2s]
     Running ‘RawGenomicSignals.R’ [1s/2s]
     Running ‘RawGenomicSignals.SEG,MP.R’ [1s/2s]
     Running ‘RawGenomicSignals.SEG.R’ [1s/2s]
    Running the tests in ‘tests/RawGenomicSignals.SEG.R’ failed.
    Complete output:
     > library("aroma.core")
     Loading required package: R.utils
     Loading required package: R.oo
     Loading required package: R.methodsS3
     R.methodsS3 v1.7.1 (2016-02-15) successfully loaded. See ?R.methodsS3 for help.
     R.oo v1.22.0 (2018-04-21) successfully loaded. See ?R.oo for help.
    
     Attaching package: 'R.oo'
    
     The following objects are masked from 'package:methods':
    
     getClasses, getMethods
    
     The following objects are masked from 'package:base':
    
     attach, detach, gc, load, save
    
     R.utils v2.6.0 (2017-11-04) successfully loaded. See ?R.utils for help.
    
     Attaching package: 'R.utils'
    
     The following object is masked from 'package:utils':
    
     timestamp
    
     The following objects are masked from 'package:base':
    
     cat, commandArgs, getOption, inherits, isOpen, parse, warnings
    
     Loading required package: R.filesets
     R.filesets v2.12.1 successfully loaded. See ?R.filesets for help.
    
     Attaching package: 'R.filesets'
    
     The following objects are masked from 'package:R.utils':
    
     extract, validate
    
     The following objects are masked from 'package:base':
    
     append, readLines
    
     Loading required package: R.devices
     R.devices v2.15.1 (2016-11-09) successfully loaded. See ?R.devices for help.
     aroma.core v3.1.1 (2017-09-12) successfully loaded. See ?aroma.core for help.
    
     Attaching package: 'aroma.core'
    
     The following objects are masked from 'package:base':
    
     .Machine, colMeans, colSums, library, require, write
    
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Simulating copy-number data
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Number of loci
     > J <- 500
     >
     > mu <- double(J)
     > mu[100:150] <- mu[100:150] + 1
     > mu[320:400] <- mu[320:400] - 1
     > eps <- rnorm(J, sd=1/2)
     > y <- mu + eps
     > x <- sort(runif(length(y), max=length(y))) * 1e5;
     > w <- runif(J)
     > w[320:400] <- 0.001
     >
     >
     > cn <- RawCopyNumbers(y, x)
     > print(cn)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 500
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: 0 [1]
     Number of loci: 500
     Position range: [118421,4.96732e+07]
     Mean distance between loci: 99308.2
     >
     > plot(cn, ylim=c(-3,3), col="#aaaaaa", xlab="Position (Mb)")
     >
     > cnS <- binnedSmoothing(cn, by=500e3)
     > print(cnS)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 100
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: [0]
     Number of loci: 100
     > lines(cnS, col="black", lwd=3)
     >
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Segment
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > legend <- c()
     >
     > if (require("DNAcopy")) {
     + fit <- segmentByCBS(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="red", lwd=3)
     + legend <- c(legend, red="CBS")
     + }
     Loading required package: DNAcopy
     CopyNumberRegions:
     Number of regions: 5
     >
     > if (require("GLAD") && packageVersion("GLAD") != "9.9.9") {
     + fit <- segmentByGLAD(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="blue", lwd=3)
     + legend <- c(legend, blue="GLAD")
     + }
     Loading required package: GLAD
    
     ######################################################################################
    
     Have fun with GLAD
    
     For smoothing it is possible to use either
     the AWS algorithm (Polzehl and Spokoiny, 2002,
     or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     If you use the package with AWS, please cite:
     Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,
    
     If you use the package with HaarSeg, please cite:
     Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     For fast computation it is recommanded to use
     the daglad function with smoothfunc=haarseg
    
     ######################################################################################
    
     New options are available in daglad: see help for details.
    
     Error in UseMethod("as.profileCGH") :
     no applicable method for 'as.profileCGH' applied to an object of class "data.frame"
     Calls: segmentByGLAD -> segmentByGLAD.RawGenomicSignals -> <Anonymous>
     Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 3.1.1
Check: package dependencies
Result: NOTE
    Packages suggested but not available for checking:
     ‘Cairo’ ‘GLAD’ ‘sfit’ ‘expectile’ ‘HaarSeg’ ‘mpcbs’
Flavor: r-devel-osx-x86_64

Version: 3.1.1
Check: Rd cross-references
Result: NOTE
    Package unavailable to check Rd xrefs: ‘GLAD’
Flavor: r-devel-osx-x86_64

Version: 3.1.1
Check: tests
Result: ERROR
     Running ‘PairedPSCNData,SEG.R’ [0s/1s]
     Running ‘PairedPSCNData.R’ [0s/1s]
     Running ‘RawCopyNumbers,states.R’ [2s/2s]
     Running ‘RawCopyNumbers.R’ [2s/2s]
     Running ‘RawGenomicSignals.R’ [1s/2s]
     Running ‘RawGenomicSignals.SEG,MP.R’ [2s/2s]
     Running ‘RawGenomicSignals.SEG.R’ [2s/2s]
    Running the tests in ‘tests/RawGenomicSignals.SEG.R’ failed.
    Complete output:
     > library("aroma.core")
     Loading required package: R.utils
     Loading required package: R.oo
     Loading required package: R.methodsS3
     R.methodsS3 v1.7.1 (2016-02-15) successfully loaded. See ?R.methodsS3 for help.
     R.oo v1.22.0 (2018-04-21) successfully loaded. See ?R.oo for help.
    
     Attaching package: 'R.oo'
    
     The following objects are masked from 'package:methods':
    
     getClasses, getMethods
    
     The following objects are masked from 'package:base':
    
     attach, detach, gc, load, save
    
     R.utils v2.6.0 (2017-11-04) successfully loaded. See ?R.utils for help.
    
     Attaching package: 'R.utils'
    
     The following object is masked from 'package:utils':
    
     timestamp
    
     The following objects are masked from 'package:base':
    
     cat, commandArgs, getOption, inherits, isOpen, parse, warnings
    
     Loading required package: R.filesets
     R.filesets v2.12.1 successfully loaded. See ?R.filesets for help.
    
     Attaching package: 'R.filesets'
    
     The following objects are masked from 'package:R.utils':
    
     extract, validate
    
     The following objects are masked from 'package:base':
    
     append, readLines
    
     Loading required package: R.devices
     R.devices v2.15.1 (2016-11-09) successfully loaded. See ?R.devices for help.
     aroma.core v3.1.1 (2017-09-12) successfully loaded. See ?aroma.core for help.
    
     Attaching package: 'aroma.core'
    
     The following objects are masked from 'package:base':
    
     .Machine, colMeans, colSums, library, require, write
    
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Simulating copy-number data
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Number of loci
     > J <- 500
     >
     > mu <- double(J)
     > mu[100:150] <- mu[100:150] + 1
     > mu[320:400] <- mu[320:400] - 1
     > eps <- rnorm(J, sd=1/2)
     > y <- mu + eps
     > x <- sort(runif(length(y), max=length(y))) * 1e5;
     > w <- runif(J)
     > w[320:400] <- 0.001
     >
     >
     > cn <- RawCopyNumbers(y, x)
     > print(cn)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 500
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: 0 [1]
     Number of loci: 500
     Position range: [54579,4.9937e+07]
     Mean distance between loci: 99964.9
     >
     > plot(cn, ylim=c(-3,3), col="#aaaaaa", xlab="Position (Mb)")
     >
     > cnS <- binnedSmoothing(cn, by=500e3)
     > print(cnS)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 100
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: [0]
     Number of loci: 100
     > lines(cnS, col="black", lwd=3)
     >
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Segment
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > legend <- c()
     >
     > if (require("DNAcopy")) {
     + fit <- segmentByCBS(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="red", lwd=3)
     + legend <- c(legend, red="CBS")
     + }
     Loading required package: DNAcopy
     CopyNumberRegions:
     Number of regions: 5
     >
     > if (require("GLAD") && packageVersion("GLAD") != "9.9.9") {
     + fit <- segmentByGLAD(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="blue", lwd=3)
     + legend <- c(legend, blue="GLAD")
     + }
     Loading required package: GLAD
    
     ######################################################################################
    
     Have fun with GLAD
    
     For smoothing it is possible to use either
     the AWS algorithm (Polzehl and Spokoiny, 2002,
     or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     If you use the package with AWS, please cite:
     Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,
    
     If you use the package with HaarSeg, please cite:
     Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     For fast computation it is recommanded to use
     the daglad function with smoothfunc=haarseg
    
     ######################################################################################
    
     New options are available in daglad: see help for details.
    
     Error in UseMethod("as.profileCGH") :
     no applicable method for 'as.profileCGH' applied to an object of class "data.frame"
     Calls: segmentByGLAD -> segmentByGLAD.RawGenomicSignals -> <Anonymous>
     Execution halted
Flavor: r-patched-linux-x86_64

Version: 3.1.1
Check: tests
Result: ERROR
     Running ‘PairedPSCNData,SEG.R’ [0s/1s]
     Running ‘PairedPSCNData.R’ [0s/0s]
     Running ‘RawCopyNumbers,states.R’ [2s/3s]
     Running ‘RawCopyNumbers.R’ [2s/2s]
     Running ‘RawGenomicSignals.R’ [1s/2s]
     Running ‘RawGenomicSignals.SEG,MP.R’ [2s/2s]
     Running ‘RawGenomicSignals.SEG.R’ [2s/3s]
    Running the tests in ‘tests/RawGenomicSignals.SEG.R’ failed.
    Complete output:
     > library("aroma.core")
     Loading required package: R.utils
     Loading required package: R.oo
     Loading required package: R.methodsS3
     R.methodsS3 v1.7.1 (2016-02-15) successfully loaded. See ?R.methodsS3 for help.
     R.oo v1.22.0 (2018-04-21) successfully loaded. See ?R.oo for help.
    
     Attaching package: 'R.oo'
    
     The following objects are masked from 'package:methods':
    
     getClasses, getMethods
    
     The following objects are masked from 'package:base':
    
     attach, detach, gc, load, save
    
     R.utils v2.6.0 (2017-11-04) successfully loaded. See ?R.utils for help.
    
     Attaching package: 'R.utils'
    
     The following object is masked from 'package:utils':
    
     timestamp
    
     The following objects are masked from 'package:base':
    
     cat, commandArgs, getOption, inherits, isOpen, parse, warnings
    
     Loading required package: R.filesets
     R.filesets v2.12.1 successfully loaded. See ?R.filesets for help.
    
     Attaching package: 'R.filesets'
    
     The following objects are masked from 'package:R.utils':
    
     extract, validate
    
     The following objects are masked from 'package:base':
    
     append, readLines
    
     Loading required package: R.devices
     R.devices v2.15.1 (2016-11-09) successfully loaded. See ?R.devices for help.
     aroma.core v3.1.1 (2017-09-12) successfully loaded. See ?aroma.core for help.
    
     Attaching package: 'aroma.core'
    
     The following objects are masked from 'package:base':
    
     .Machine, colMeans, colSums, library, require, write
    
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Simulating copy-number data
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Number of loci
     > J <- 500
     >
     > mu <- double(J)
     > mu[100:150] <- mu[100:150] + 1
     > mu[320:400] <- mu[320:400] - 1
     > eps <- rnorm(J, sd=1/2)
     > y <- mu + eps
     > x <- sort(runif(length(y), max=length(y))) * 1e5;
     > w <- runif(J)
     > w[320:400] <- 0.001
     >
     >
     > cn <- RawCopyNumbers(y, x)
     > print(cn)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 500
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: 0 [1]
     Number of loci: 500
     Position range: [66803.3,4.99848e+07]
     Mean distance between loci: 100036
     >
     > plot(cn, ylim=c(-3,3), col="#aaaaaa", xlab="Position (Mb)")
     >
     > cnS <- binnedSmoothing(cn, by=500e3)
     > print(cnS)
     RawCopyNumbers:
     Name: <none>
     Number of rows: 100
     Number of columns: 3
     Columns: chromosome [numeric], x [numeric], cn [numeric]
     Chromosomes: [0]
     Number of loci: 100
     > lines(cnS, col="black", lwd=3)
     >
     >
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > # Segment
     > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     > legend <- c()
     >
     > if (require("DNAcopy")) {
     + fit <- segmentByCBS(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="red", lwd=3)
     + legend <- c(legend, red="CBS")
     + }
     Loading required package: DNAcopy
     CopyNumberRegions:
     Number of regions: 5
     >
     > if (require("GLAD") && packageVersion("GLAD") != "9.9.9") {
     + fit <- segmentByGLAD(cn)
     + cnr <- extractCopyNumberRegions(fit)
     + print(cnr)
     + drawLevels(cnr, col="blue", lwd=3)
     + legend <- c(legend, blue="GLAD")
     + }
     Loading required package: GLAD
    
     ######################################################################################
    
     Have fun with GLAD
    
     For smoothing it is possible to use either
     the AWS algorithm (Polzehl and Spokoiny, 2002,
     or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     If you use the package with AWS, please cite:
     Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,
    
     If you use the package with HaarSeg, please cite:
     Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,
    
     For fast computation it is recommanded to use
     the daglad function with smoothfunc=haarseg
    
     ######################################################################################
    
     New options are available in daglad: see help for details.
    
     Error in UseMethod("as.profileCGH") :
     no applicable method for 'as.profileCGH' applied to an object of class "data.frame"
     Calls: segmentByGLAD -> segmentByGLAD.RawGenomicSignals -> <Anonymous>
     Execution halted
Flavor: r-release-linux-x86_64

Version: 3.1.1
Check: package dependencies
Result: NOTE
    Packages suggested but not available for checking:
     ‘EBImage’ ‘aroma.light’ ‘GLAD’ ‘sfit’ ‘expectile’ ‘HaarSeg’ ‘mpcbs’
Flavor: r-release-osx-x86_64

Version: 3.1.1
Check: Rd cross-references
Result: NOTE
    Packages unavailable to check Rd xrefs: ‘aroma.light’, ‘GLAD’
Flavor: r-release-osx-x86_64