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Results 1 - 10 of 12 found.
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iPAC : Identification of Protein Amino acid Clustering

Package: iPAC
Type: Package
Title: Identification of Protein Amino acid Clustering
Version: 1.16.0
Date: 2012-06-06
Author: Gregory Ryslik, Hongyu Zhao
Maintainer: Gregory Ryslik <gregory.ryslik@yale.edu>
Description: iPAC is a novel tool to identify somatic amino acid
mutation clustering within proteins while taking into account
protein structure.
License: GPL-2
Depends: R (>= 2.15), gdata, scatterplot3d, Biostrings, multtest
Repository: Bioconductor
Packaged: 2016-05-04 04:38:22 UTC; biocbuild
biocViews: Clustering, Proteomics
NeedsCompilation: no

● Data Source: BioConductor
● BiocViews: Clustering, Proteomics
● 4 images, 9 functions, 2 datasets
● Reverse Depends: 3

siggenes : Multiple testing using SAM and Efron's empirical Bayes approaches

Package: siggenes
Version: 1.46.0
Date: 2012-03-05
Title: Multiple testing using SAM and Efron's empirical Bayes
approaches
Author: Holger Schwender
Maintainer: Holger Schwender <holger.schw@gmx.de>
Depends: methods, Biobase, multtest, splines, graphics
Imports: stats4
Suggests: affy, annotate, genefilter, KernSmooth, scrime (>= 1.2.5)
Description: Identification of differentially expressed genes and
estimation of the False Discovery Rate (FDR) using both the
Significance Analysis of Microarrays (SAM) and the Empirical
Bayes Analyses of Microarrays (EBAM).
License: LGPL (>= 2)
biocViews: MultipleComparison, Microarray, GeneExpression, SNP,
ExonArray, DifferentialExpression
NeedsCompilation: no
Packaged: 2016-05-04 02:38:53 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: DifferentialExpression, ExonArray, GeneExpression, Microarray, MultipleComparison, SNP
● 0 images, 40 functions, 0 datasets
● Reverse Depends: 2

webbioc : Bioconductor Web Interface

Package: webbioc
Version: 1.44.0
Date: 2009-02-05
Title: Bioconductor Web Interface
Author: Colin A. Smith <colin@colinsmith.org>
Maintainer: Colin A. Smith <colin@colinsmith.org>
Depends: R (>= 1.8.0), Biobase, affy, multtest, annaffy, vsn, gcrma,
qvalue
Imports: multtest, qvalue, stats, utils, BiocInstaller
SystemRequirements: Unix, Perl (>= 5.6.0), Netpbm
Description: An integrated web interface for doing microarray analysis
using several of the Bioconductor packages. It is intended to
be deployed as a centralized bioinformatics resource for use
by many users. (Currently only Affymetrix oligonucleotide
analysis is supported.)
License: GPL (>= 2)
URL: http://www.bioconductor.org/
LazyLoad: yes
biocViews: Infrastructure, Microarray, OneChannel,
DifferentialExpression
NeedsCompilation: no
Packaged: 2016-05-04 02:39:29 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: DifferentialExpression, Infrastructure, Microarray, OneChannel
● 0 images, 2 functions, 0 datasets
● Reverse Depends: 0

rain : Rhythmicity Analysis Incorporating Non-parametric Methods

Package: rain
Type: Package
Title: Rhythmicity Analysis Incorporating Non-parametric Methods
Version: 1.6.0
Date: 2015-09-01
Author: Paul F. Thaben, PÃ¥l O. Westermark
Maintainer: Paul F. Thaben <paul.thaben@charite.de>
Description: This package uses non-parametric methods to detect rhythms
in time series. It deals with outliers, missing values and is
optimized for time series comprising 10-100 measurements. As it
does not assume expect any distinct waveform it is optimal or
detecting oscillating behavior (e.g. circadian or cell cycle)
in e.g. genome- or proteome-wide biological measurements such
as: micro arrays, proteome mass spectrometry, or metabolome
measurements.
License: GPL-2
Depends: R (>= 2.10), gmp, multtest
biocViews: TimeCourse, Genetics, SystemsBiology, Proteomics,
Microarray, MultipleComparison
Suggests: lattice, BiocStyle
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2016-05-04 05:44:50 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Genetics, Microarray, MultipleComparison, Proteomics, SystemsBiology, TimeCourse
● 1 images, 3 functions, 0 datasets
● Reverse Depends: 0

REDseq : Analysis of high-throughput sequencing data processed by restriction enzyme digestion

Package: REDseq
Type: Package
Title: Analysis of high-throughput sequencing data processed by
restriction enzyme digestion
Version: 1.18.0
Date: 2013-10-21
Author: Lihua Julie Zhu and Thomas Fazzio
Maintainer: Lihua Julie Zhu <julie.zhu@umassmed.edu>
Depends: R (>= 2.15.0), BiocGenerics (>= 0.1.0),
BSgenome.Celegans.UCSC.ce2, multtest, Biostrings, BSgenome,
ChIPpeakAnno
Imports: BiocGenerics, AnnotationDbi, Biostrings, ChIPpeakAnno,
graphics, IRanges (>= 1.13.5), multtest, stats, utils
biocViews: Sequencing, SequenceMatching, Preprocessing
Description: The package includes functions to build restriction enzyme cut site (RECS) map, distribute mapped sequences on the map with five different approaches, find enriched/depleted RECSs for a sample, and identify differentially enriched/depleted RECSs between samples.
License: GPL (>=2)
NeedsCompilation: no
Packaged: 2016-05-04 04:03:50 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Preprocessing, SequenceMatching, Sequencing
● 6 images, 11 functions, 3 datasets
● Reverse Depends: 0

SAGx : Statistical Analysis of the GeneChip

Package: SAGx
Type: Package
Title: Statistical Analysis of the GeneChip
Version: 1.46.0
Author: Per Broberg
Maintainer: Per Broberg, <pi.broberg@gmail.com>
Depends: R (>= 2.5.0), stats, multtest, methods
Suggests: KEGG.db, hu6800.db, MASS
Imports: Biobase, stats4
Description: A package for retrieval, preparation and analysis of data
from the Affymetrix GeneChip. In particular the issue of
identifying differentially expressed genes is addressed.
License: GPL-3
LazyLoad: yes
URL: http://home.swipnet.se/pibroberg/expression_hemsida1.html
biocViews: Microarray, OneChannel, Preprocessing, DataImport,
DifferentialExpression, Clustering, MultipleComparison,
GeneExpression, GeneSetEnrichment, Pathways, Regression, KEGG
NeedsCompilation: yes
Packaged: 2016-05-04 02:53:47 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Clustering, DataImport, DifferentialExpression, GeneExpression, GeneSetEnrichment, KEGG, Microarray, MultipleComparison, OneChannel, Pathways, Preprocessing, Regression
● 1 images, 32 functions, 0 datasets
● Reverse Depends: 1

PREDA : Position RElated Data Anlysis

Package: PREDA
Version: 1.18.0
Title: Position RElated Data Anlysis
Author: Francesco Ferrari <francesco.ferrari@unimore.it>
Maintainer: Francesco Ferrari <francesco.ferrari@unimore.it>
License: GPL-2
Depends: R (>= 2.9.0), Biobase, lokern (>= 1.0.9), multtest, stats,
methods, annotate
Suggests: quantsmooth, qvalue, samr, limma, caTools, affy,
PREDAsampledata
Enhances: Rmpi, rsprng
Description: Package for the position related analysis of quantitative
functional genomics data.
Collate: AllClasses.R AllGenerics.R analysesNames.R
CleanNAAnnotationDataframe.R
compareFunctionFromStatisticsForPREDA.R
computeDatasetSignature.R DataForPREDA2dataframe.R
DataForPREDA2GenomicAnnotationsForPREDA.R
DataForPREDA2StatisticsForPREDA.R datasetSignatureFromFlags.R
eset2GenomicAnnotations.R GE_computeStatistic.R
GEhighWeakExpressionWorkflow.R genomePlot_improved.R
genomePlot.R GenomicAnnotations2dataframe.R
GenomicAnnotations2GenomicAnnotationsForPREDA.R
GenomicAnnotations2reference_positions.R
GenomicAnnotationsExtract.R GenomicAnnotationsFilter_neg.R
GenomicAnnotationsFilter_pos.R
GenomicAnnotationsForPREDA2dataframe.R
GenomicAnnotationsForPREDA2GenomicAnnotations.R
GenomicAnnotationsForPREDA2PREDAResults.R
GenomicAnnotationsForPREDAFromfile.R
GenomicAnnotationsForPREDAGetExpectedFlags.R
GenomicAnnotationsFromdataframe.R GenomicAnnotationsFromfile.R
GenomicAnnotationsFromLibrary.R
GenomicAnnotationsSortAndCleanNA.R GenomicRegions2dataframe.R
GenomicRegionsAnnotate.R GenomicRegionsChrNumber.R
GenomicRegionsComparison.R GenomicRegionsCreateRegionsIds.R
GenomicRegionsFilter_neg.R GenomicRegionsFilter_pos.R
GenomicRegionsFindOverlap.R GenomicRegionsFromdataframe.R
GenomicRegionsFromfile.R GenomicRegionsNumber.R
GenomicRegionsSpan.R GenomicRegionsTotalSpan.R
GEsimulationsWorkflow.R getExpectedSmoothFunction.R
getExpectedSmoothFunction_runmean.R getObservedSmoothFunction.R
getObservedSmoothFunction_runmean.R getStatisticByName.R
initialize-methods.R MergeStatisticAnnotations2DataForPREDA.R
PREDADataAndResults2dataframe.R PREDA_main_permRows.R
PREDA_main_permSamples.R PREDA_main.R
PREDA_multTestCorrection.R PREDA_quantsmoothStatPerm.R
PREDA_quantsmoothStat.R PREDAResults2dataframe.R
PREDAResults2GenomicRegions.R
PREDAResults2GenomicRegionsSingle.R
PREDAResults2PREDADataAndResults.R
PREDAResultsGetObservedFlags.R PREDA_smoothStatPerm.R
PREDA_smoothStat.R PREDA_splineStatPerm.R PREDA_splineStat.R
preprocessingGE.R RMAwithCDFfilter.R simulations.R
SODEGIR_GEstatistics.R SODEGIRpreprocessingGE.R
SortAnnotationDataframe.R StatisticsForPREDA2dataframe.R
StatisticsForPREDAFilterColumns_neg.R
StatisticsForPREDAFilterColumns_pos.R
StatisticsForPREDAFromdataframe.R statisticsForPREDAfromEset.R
StatisticsForPREDAFromfile.R
biocViews: Software, CopyNumberVariation, GeneExpression, Genetics
NeedsCompilation: no
Packaged: 2016-05-05 03:04:10 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, GeneExpression, Genetics, Software
● 0 images, 60 functions, 0 datasets
● Reverse Depends: 1

KCsmart : Multi sample aCGH analysis package using kernel convolution

Package: KCsmart
Type: Package
Title: Multi sample aCGH analysis package using kernel convolution
Version: 2.30.0
Date: 2009-11-26
Author: Jorma de Ronde, Christiaan Klijn, Arno Velds
Maintainer: Jorma de Ronde <j.d.ronde@nki.nl>
Description: Multi sample aCGH analysis package using kernel
convolution
License: GPL-3
Depends: siggenes, multtest, KernSmooth
Imports: methods, BiocGenerics
Enhances: Biobase, CGHbase
Collate: 'AllClasses.R' 'access-methods.R' 'length-methods.R'
'plot-methods.R' 'show-methods.R' 'sort-methods.R'
'unlist-methods.R' 'write.table-methods.R' 'KC.R'
LazyLoad: yes
biocViews: CopyNumberVariation, Visualization, aCGH, Microarray
NeedsCompilation: no
Packaged: 2016-05-04 03:10:10 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, Microarray, Visualization, aCGH
● 19 images, 23 functions, 3 datasets
● Reverse Depends: 0

LMGene : LMGene Software for Data Transformation and Identification of Differentially Expressed Genes in Gene Expression Arrays

Package: LMGene
Version: 2.28.0
Date: 2013-07-24
Title: LMGene Software for Data Transformation and Identification of
Differentially Expressed Genes in Gene Expression Arrays
Author: David Rocke, Geun Cheol Lee, John Tillinghast, Blythe
Durbin-Johnson, and Shiquan Wu
Depends: R (>= 2.10.0), Biobase (>= 2.5.5), multtest, survival, affy
Suggests: affydata
Maintainer: Blythe Durbin-Johnson <bpdurbin@ucdavis.edu>
Description: LMGene package for analysis of microarray data using a
linear model and glog data transformation
License: LGPL
URL: http://dmrocke.ucdavis.edu/software.html
biocViews: Microarray, DifferentialExpression, Preprocessing
NeedsCompilation: no
Packaged: 2016-05-04 02:46:49 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: DifferentialExpression, Microarray, Preprocessing
● 2 images, 14 functions, 4 datasets
● Reverse Depends: 0

BicARE : Biclustering Analysis and Results Exploration

Package: BicARE
Version: 1.30.0
Date: 2008-06-05
Title: Biclustering Analysis and Results Exploration
Depends: R (>= 1.8.0), Biobase (>= 2.5.5), multtest, GSEABase
Author: Pierre Gestraud
Maintainer: Pierre Gestraud <pierre.gestraud@curie.fr>
Description: Biclustering Analysis and Results Exploration
License: GPL-2
URL: http://bioinfo.curie.fr
biocViews: Microarray, Transcription, Clustering
NeedsCompilation: yes
Packaged: 2016-05-04 03:12:29 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Clustering, Microarray, Transcription
● 2 images, 7 functions, 2 datasets
● Reverse Depends: 1