Last data update: 2014.03.03

Data Source

R Release (3.2.3)
CranContrib
BioConductor
All

Data Type

Packages
Functions
Images
Data set

Classification

Results 1 - 8 of 8 found.
[1] < 1 > [1]  Sort:

snapCGH : Segmentation, normalisation and processing of aCGH data.

Package: snapCGH
Title: Segmentation, normalisation and processing of aCGH data.
Version: 1.42.0
Date: 2009-10-08
Author: Mike L. Smith, John C. Marioni, Steven McKinney, Thomas
Hardcastle, Natalie P. Thorne
Description: Methods for segmenting, normalising and processing aCGH
data; including plotting functions for visualising raw and
segmented data for individual and multiple arrays.
Maintainer: John Marioni <marioni@uchicago.edu>
Depends: limma, DNAcopy, methods
Imports: aCGH, cluster, DNAcopy, GLAD, graphics, grDevices, limma,
methods, stats, tilingArray, utils
License: GPL
biocViews: Microarray, CopyNumberVariation, TwoChannel, Preprocessing
NeedsCompilation: yes
Packaged: 2016-05-04 02:49:21 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, Microarray, Preprocessing, TwoChannel
● 0 images, 35 functions, 8 datasets
● Reverse Depends: 0

CRImage : CRImage a package to classify cells and calculate tumour cellularity

Package: CRImage
Type: Package
Title: CRImage a package to classify cells and calculate tumour
cellularity
Version: 1.20.0
Date: 2012-10-01
Author: Henrik Failmezger <failmezger@mpipz.mpg.de>, Yinyin Yuan <Yinyin.Yuan@cancer.org.uk>, Oscar Rueda <oscar.rueda@cancer.org.uk>, Florian Markowetz <Florian.Markowetz@cancer.org.uk>
Maintainer: Henrik Failmezger <failmezger@mpipz.mpg.de>, Yinyin Yuan
<Yinyin.Yuan@cancer.org.uk>
Description: CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity.
License: Artistic-2.0
LazyLoad: yes
Imports: MASS, e1071, foreach, sgeostat
Depends: EBImage, DNAcopy, aCGH
Collate: plotCorrectedCN.R correctCopyNumber.R writeDensityImage.R
convertRGBToHSV.R convertHSVToRGB.R imageCompression.R
createBinaryImage.R colorCorrection.R searchStructures.R
segmentStructures.R classifyStructures.R numberOfNeighbors.R
segmentCytoplasma.R segmentImage.R createClassifier.R
kernelSmoother.R paintCells.R classifyCells.R
determineCellularity.R calculateCellularity.R findSlices.R
parseFinalScan.R classificationAperio.R processAperio.R
Phansalkar_threshold.R SauvolaThreshold.R
calculateMeanStdTarget.R convertLABToRGB.R convertRGBToLAB.R
localORThreshold.R oregonThreshold.R localThreshold.R
calculateOtsu.R classifyPen.R getImageDistance.R hist3d.R
labelCells.R plotImage.R
biocViews: CellBiology, Classification
Packaged: 2016-05-04 03:45:46 UTC; biocbuild
NeedsCompilation: no

● Data Source: BioConductor
● BiocViews: CellBiology, Classification
1 images, 19 functions, 0 datasets
● Reverse Depends: 0

Clonality : Clonality testing

Package: Clonality
Type: Package
Title: Clonality testing
Version: 1.20.0
Date: 2012-20-04
Author: Irina Ostrovnaya
Maintainer: Irina Ostrovnaya <ostrovni@mskcc.org>
Depends: R (>= 2.12.2), DNAcopy
Imports: DNAcopy, grDevices, graphics, stats, utils
Suggests: gdata, DNAcopy
Description: Statistical tests for clonality versus independence of
tumors from the same patient based on their LOH or genomewide
copy number profiles
License: GPL-3
LazyLoad: yes
biocViews: Microarray, CopyNumberVariation, Classification, aCGH
NeedsCompilation: no
Packaged: 2016-05-04 03:55:40 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Classification, CopyNumberVariation, Microarray, aCGH
● 0 images, 11 functions, 0 datasets
● Reverse Depends: 0

CopyNumber450k : R package for calling CNV from Illumina 450k methylation microarrays

Package: CopyNumber450k
Title: R package for calling CNV from Illumina 450k methylation
microarrays
Version: 1.8.0
Date: 2014-02-04
Author: Simon Papillon-Cavanagh, Jean-Philippe Fortin, Nicolas De Jay
Maintainer: Simon Papillon-Cavanagh
<simon.papillon-cavanagh@mail.mcgill.ca>
Description: This package contains a set of functions that allow CNV
calling from Illumina 450k methylation microarrays.
License: Artistic-2.0
Imports: methods
Depends: Biobase, minfi, DNAcopy, preprocessCore, BiocGenerics
Suggests: CopyNumber450kData, minfiData
LinkingTo:
LazyData: yes
Collate: AllClasses.R AllGenerics.R CNV450kSet-accessors.R
CNV450kSet-actions.R CNV450kSet-comparison.R
CNV450kSet-initialize.R CNV450kSet-plot.R extract.R
normalization.functional.R normalization.quantile.R
biocViews: DNAMethylation, Microarray, Preprocessing, QualityControl,
CopyNumberVariation
NeedsCompilation: no
Packaged: 2016-05-04 05:20:08 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, DNAMethylation, Microarray, Preprocessing, QualityControl
4 images, 1 functions, 0 datasets
● Reverse Depends: 0

PureCN : Estimating tumor purity, ploidy, LOH, and SNV status using hybrid capture NGS data

Package: PureCN
Type: Package
Title: Estimating tumor purity, ploidy, LOH, and SNV status using
hybrid capture NGS data
Version: 1.0.3
Date: 2016-06-04
Author: Markus Riester
Maintainer: Markus Riester <markus.riester@novartis.com>
Description: This package estimates tumor purity, copy number, loss of
heterozygosity (LOH), and status of single nucleotide variants (SNVs).
PureCN is designed for hybrid capture sequencing data, integrates
well with standard somatic variant detection pipelines,
and has support for tumor samples without matching normal samples.
Depends: R (>= 3.3), DNAcopy, VariantAnnotation (>= 1.14.1)
Imports: GenomicRanges (>= 1.20.3), IRanges (>= 2.2.1), RColorBrewer,
S4Vectors, data.table, grDevices, graphics, stats, utils,
SummarizedExperiment, GenomeInfoDb
Suggests: PSCBS, RUnit, BiocStyle, BiocGenerics, knitr
VignetteBuilder: knitr
License: Artistic-2.0
biocViews: CopyNumberVariation, Software, Sequencing,
VariantAnnotation, VariantDetection
NeedsCompilation: no
Packaged: 2016-06-06 06:04:50 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, Sequencing, Software, VariantAnnotation, VariantDetection
14 images, 20 functions, 2 datasets
● Reverse Depends: 0

SomatiCA : SomatiCA: identifying, characterizing, and quantifying somatic copy number aberrations from cancer genome sequencing

Package: SomatiCA
Type: Package
Title: SomatiCA: identifying, characterizing, and quantifying somatic
copy number aberrations from cancer genome sequencing
Version: 2.2.0
Date: 2016-04-15
Author: Mengjie Chen <mengjie.chen@yale.edu>, Hongyu Zhao
<hongyu.zhao@yale.edu>
Maintainer: Mengjie Chen <mengjie.chen@yale.edu>
Imports: foreach, lars, sn, DNAcopy, methods, rebmix, GenomicRanges,
IRanges
Depends: R (>= 2.14.0), lars, DNAcopy, foreach, methods, rebmix,
GenomicRanges, IRanges, doParallel
Enhances: sn, SomatiCAData
Description: SomatiCA is a software suite that is capable of
identifying, characterizing, and quantifying somatic CNAs from
cancer genome sequencing. First, it uses read depths and lesser
allele frequencies (LAF) from mapped short sequence reads to
segment the genome and identify candidate CNAs. Second,
SomatiCA estimates the admixture rate from the relative
copy-number profile of tumor-normal pair by a Bayesian finite
mixture model. Third, SomatiCA quantifies absolute somatic
copy-number and subclonality for each genomic segment to guide
its characterization. Results from SomatiCA can be further
integrated with single nucleotide variations (SNVs) to get a
better understanding of the tumor evolution.
License: GPL (>=2)
biocViews: Sequencing, CopyNumberVariation
PackageStatus: Deprecated
NeedsCompilation: no
Packaged: 2016-05-04 04:51:18 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, Sequencing
1 images, 18 functions, 2 datasets
● Reverse Depends: 0

cghMCR : Find chromosome regions showing common gains/losses

Package: cghMCR
Version: 1.30.0
Title: Find chromosome regions showing common gains/losses
Author: J. Zhang and B. Feng
Maintainer: J. Zhang <jzhang@jimmy.harvard.edu>
Depends: methods, DNAcopy, CNTools, limma
Imports: BiocGenerics (>= 0.1.6), stats4
Description: This package provides functions to identify genomic
regions of interests based on segmented copy number data from
multiple samples.
Keyword: arrayCGH
License: LGPL
LazyLoad: yes
biocViews: Microarray, CopyNumberVariation
NeedsCompilation: no
Packaged: 2016-05-04 02:52:38 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, Microarray
1 images, 6 functions, 0 datasets
● Reverse Depends: 0

CGHcall : Calling aberrations for array CGH tumor profiles.

Package: CGHcall
Type: Package
Title: Calling aberrations for array CGH tumor profiles.
Version: 2.34.0
Date: 2014-02-25
Author: Mark van de Wiel, Sjoerd Vosse
Maintainer: Mark van de Wiel <mark.vdwiel@vumc.nl>
Depends: R (>= 2.0.0), impute (>= 1.8.0), DNAcopy (>= 1.6.0), methods,
Biobase, CGHbase (>= 1.15.1), snowfall
Description: Calls aberrations for array CGH data using a six state mixture model as well as several biological concepts that are ignored by existing algorithms. Visualization of profiles is also provided.
License: GPL (http://www.gnu.org/copyleft/gpl.html)
biocViews: Microarray,Preprocessing,Visualization
NeedsCompilation: no
Packaged: 2016-05-04 03:02:20 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Microarray, Preprocessing, Visualization
● 0 images, 7 functions, 1 datasets
Reverse Depends: 3