Last data update: 2014.03.03

Data Source

R Release (3.2.3)

Data Type

Data set


Results 1 - 10 of 40 found.
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leeBamViews : leeBamViews -- multiple yeast RNAseq samples excerpted from Lee 2009

Package: leeBamViews
Title: leeBamViews -- multiple yeast RNAseq samples excerpted from Lee
Version: 1.8.0
Author: VJ Carey <>
Description: data from PMID 19096707; prototype for managing multiple NGS samples
Depends: R (>= 2.15.0), Biobase, Rsamtools (>= 0.1.50), BSgenome
Imports: GenomicRanges, GenomicAlignments, methods
Suggests: GenomeGraphs, biomaRt, org.Sc.sgd.db, edgeR
Enhances: multicore
Maintainer: VJ Carey <>
License: Artistic 2.0
LazyLoad: yes
biocViews: ExperimentData, Saccharomyces_cerevisiae_Data,
SequencingData, RNASeqData, SNPData
NeedsCompilation: no
Packaged: 2016-05-07 20:18:17 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: ExperimentData, RNASeqData, SNPData, Saccharomyces_cerevisiae_Data, SequencingData
● 0 images, 2 functions, 3 datasets
● Reverse Depends: 0

contiBAIT : Improves Early Build Genome Assemblies using Strand-Seq Data

Package: contiBAIT
Type: Package
Title: Improves Early Build Genome Assemblies using Strand-Seq Data
Version: 1.0.0
Date: 2016-02-02
Author: Kieran O'Neill, Mark Hills, Mike Gottlieb
Maintainer: Kieran O'Neill <>
Description: Using strand inheritance data from multiple single cells
from the organism whose genome is to be assembled, contiBAIT
can cluster unbridged contigs together into putative
chromosomes, and order the contigs within those chromosomes.
License: BSD_2_clause + file LICENSE
Depends: BH (>= 1.51.0-3), Rsamtools (>= 1.21)
LinkingTo: Rcpp, BH
Imports: grDevices, clue, cluster, gplots, IRanges, GenomicRanges,
S4Vectors, Rcpp, TSP, GenomicFiles, gtools, rtracklayer,
BiocParallel, DNAcopy, colorspace, reshape2, ggplot2, methods,
exomeCopy, diagram
Suggests: BiocStyle
biocViews: CellBasedAssays, QualityControl, WholeGenome, Genetics,
Collate: 'AllClasses.R' 'AllGenerics.R' 'BAIT.R'
'barplotLinkageGroupCalls.R' 'clusterContigs.R'
'computeConsensus.R' 'computeSim.R' 'contiBAIT.R'
'ideogramPlot.R' 'makeBoxPlot.R' 'makeChrTable.R'
'mapGapFromOverlap.R' 'mergeLinkageGroups.R'
'orderAllLinkageGroups.R' 'orderContigsGreedy.R'
'orderContigsTSP.R' 'plotContigOrder.R' 'plotLGDistances.R'
'plotWCdistribution.R' 'preprocessStrandTable.R'
'reorientLinkageGroups.R' 'strandSeqFreqTable.R' 'writeBed.R'
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-05-04 06:48:07 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CellBasedAssays, Genetics, GenomeAssembly, QualityControl, WholeGenome
7 images, 40 functions, 0 datasets
● Reverse Depends: 0

rfPred : Assign rfPred functional prediction scores to a missense variants list

Package: rfPred
Type: Package
Title: Assign rfPred functional prediction scores to a missense
variants list
Version: 1.10.0
Date: 2013-07-17
Author: Fabienne Jabot-Hanin, Hugo Varet and Jean-Philippe Jais
Depends: Rsamtools, GenomicRanges, IRanges, data.table, methods,
Suggests: BiocStyle
Maintainer: Hugo Varet <>
Description: Based on external numerous data files where rfPred scores
are pre-calculated on all genomic positions of the human exome,
the package gives rfPred scores to missense variants identified
by the chromosome, the position (hg19 version), the referent
and alternative nucleotids and the uniprot identifier of the
protein. Note that for using the package, the user has to be
connected on the Internet or to download the TabixFile and
index (approximately 3.3 Go).
License: GPL (>=2 )
biocViews: Software, Annotation, Classification
NeedsCompilation: yes
Packaged: 2016-05-04 05:02:18 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Annotation, Classification, Software
● 0 images, 3 functions, 2 datasets
● Reverse Depends: 0

rnaSeqMap : rnaSeq secondary analyses

Package: rnaSeqMap
Type: Package
Title: rnaSeq secondary analyses
Version: 2.30.0
Date: 2014-09-30
Author: Anna Lesniewska <>; Michal
Okoniewski <>
Maintainer: Michal Okoniewski <>
Depends: R (>= 2.11.0), methods, Biobase, Rsamtools, GenomicAlignments
Imports: GenomicRanges , IRanges, edgeR, DESeq, DBI
Description: The rnaSeqMap library provides classes and functions to
analyze the RNA-sequencing data using the coverage profiles in
multiple samples at a time
License: GPL-2
Collate: zzz.R utils.R plots.R NucleotideDistr.R SeqReads.R NDplots.R
NDtransforms.R bam2sig.R parseGff3.R pipelines.R
normalizations.R measures.R generators.R camelWrapper.R
biocViews: Annotation, ReportWriting, Transcription, GeneExpression,
DifferentialExpression, Sequencing, RNASeq, SAGE, Visualization
NeedsCompilation: yes
Packaged: 2016-05-04 03:45:55 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Annotation, DifferentialExpression, GeneExpression, RNASeq, ReportWriting, SAGE, Sequencing, Transcription, Visualization
● 0 images, 37 functions, 1 datasets
Reverse Depends: 1

ssviz : A small RNA-seq visualizer and analysis toolkit

Package: ssviz
Type: Package
Title: A small RNA-seq visualizer and analysis toolkit
Version: 1.6.2
Date: 2014-07-15
Author: Diana Low
Maintainer: Diana Low <>
Description: Small RNA sequencing viewer
License: GPL-2
Depends: R (>=
2.15.1), methods, Rsamtools, Biostrings, reshape, ggplot2, RColorBrewer
biocViews: Sequencing,RNASeq,Visualization,MultipleComparison,Genetics
Collate: AllClasses.R AllGenerics.R helper.R
VignetteBuilder: knitr
Suggests: knitr
NeedsCompilation: no
Packaged: 2016-05-16 04:36:39 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Genetics, MultipleComparison, RNASeq, Sequencing, Visualization
4 images, 18 functions, 5 datasets
● Reverse Depends: 0

systemPipeR : systemPipeR: NGS workflow and report generation environment

Package: systemPipeR
Type: Package
Title: systemPipeR: NGS workflow and report generation environment
Version: 1.6.2
Date: 2016-02-26
Author: Thomas Girke
Maintainer: Thomas Girke <>
biocViews: Genetics, Infrastructure, DataImport, Sequencing, RNASeq,
RiboSeq, ChIPSeq, MethylSeq, SNP, GeneExpression, Coverage,
GeneSetEnrichment, Alignment, QualityControl
Description: R package for building and running automated end-to-end analysis workflows for a wide range of next generation sequence (NGS) applications such as RNA-Seq, ChIP-Seq, VAR-Seq and Ribo-Seq. Important features include a uniform workflow interface across different NGS applications, automated report generation, and support for running both R and command-line software, such as NGS aligners or peak/variant callers, on local computers or compute clusters. Efficient handling of complex sample sets and experimental designs is facilitated by a consistently implemented sample annotation infrastructure. Instructions for using systemPipeR are given in the Overview Vignette (HTML). The remaining Vignettes, linked below, are workflow templates for common NGS use cases.
Depends: Rsamtools, Biostrings, ShortRead, methods
Imports: BiocGenerics, GenomicRanges, GenomicFeatures,
SummarizedExperiment, VariantAnnotation, rjson, ggplot2, grid,
limma, edgeR, DESeq2, GOstats, GO.db, annotate, pheatmap,
Suggests: ape, RUnit, BiocStyle, knitr, rmarkdown, biomaRt,
VignetteBuilder: knitr
SystemRequirements: systemPipeR can be used to run external
command-line software (e.g. short read aligners), but the
corresponding tool needs to be installed on a system.
License: Artistic-2.0
NeedsCompilation: no
Packaged: 2016-05-16 04:51:50 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Alignment, ChIPSeq, Coverage, DataImport, GeneExpression, GeneSetEnrichment, Genetics, Infrastructure, MethylSeq, QualityControl, RNASeq, RiboSeq, SNP, Sequencing
33 images, 39 functions, 0 datasets
● Reverse Depends: 0

wavClusteR : Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data

Package: wavClusteR
Type: Package
Title: Sensitive and highly resolved identification of RNA-protein
interaction sites in PAR-CLIP data
Version: 2.6.2
Date: 2016-02-11
Depends: R (>= 3.2), GenomicRanges (>= 1.23.16), Rsamtools
Imports: methods, BiocGenerics, S4Vectors (>= 0.9.25), IRanges (>=
2.5.27), Biostrings, foreach, GenomicFeatures, ggplot2, Hmisc,
mclust, rtracklayer, seqinr, stringr, wmtsa
Suggests: BiocStyle, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19
Enhances: doMC
VignetteBuilder: knitr
Author: Federico Comoglio and Cem Sievers
Maintainer: Federico Comoglio <>
Description: The package provides an integrated pipeline for the analysis
of PAR-CLIP data. PAR-CLIP-induced transitions are first discriminated from
sequencing errors, SNPs and additional non-experimental sources by a non-
parametric mixture model. The protein binding sites (clusters) are then resolved
at high resolution and cluster statistics are estimated using a rigorous
Bayesian framework. Post-processing of the results, data export for UCSC genome
browser visualization and motif search analysis are provided. In addition, the
package allows to integrate RNA-Seq data to estimate the False Discovery Rate
of cluster detection. Key functions support parallel multicore computing. Note:
while wavClusteR was designed for PAR-CLIP data analysis, it can be applied to
the analysis of other NGS data obtained from experimental procedures that induce
nucleotide substitutions (e.g. BisSeq).
License: GPL-2
biocViews: Sequencing, Technology, RIPSeq, RNASeq, Bayesian
LazyLoad: yes
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-05-16 04:35:06 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Bayesian, RIPSeq, RNASeq, Sequencing, Technology
6 images, 20 functions, 1 datasets
● Reverse Depends: 0

podkat : Position-Dependent Kernel Association Test

Package: podkat
Type: Package
Title: Position-Dependent Kernel Association Test
Version: 1.4.2
Date: 2016-04-12
Author: Ulrich Bodenhofer
Maintainer: Ulrich Bodenhofer <>
Description: This package provides an association test that is capable
of dealing with very rare and even private variants. This is
accomplished by a kernel-based approach that takes the
positions of the variants into account. The test can be used
for pre-processed matrix data, but also directly for variant
data stored in VCF files. Association testing can be performed
whole-genome, whole-exome, or restricted to pre-defined regions
of interest. The test is complemented by tools for analyzing
and visualizing the results.
License: GPL (>= 2)
Depends: R (>= 3.2.0), methods, Rsamtools, GenomicRanges
Imports: Rcpp (>= 0.11.1), parallel, stats, graphics, grDevices, utils,
Biobase, BiocGenerics, Matrix, GenomeInfoDb, IRanges,
Biostrings, BSgenome (>= 1.32.0)
Suggests: BSgenome.Hsapiens.UCSC.hg38.masked,
BSgenome.Mmusculus.UCSC.mm10.masked, GWASTools (>= 1.13.24),
VariantAnnotation, knitr
LinkingTo: Rcpp, Rsamtools
VignetteBuilder: knitr
Collate: AllGenerics.R AllClasses.R inputChecks.R sort-methods.R
show-methods.R print-methods.R summary-methods.R
p.adjust-methods.R c-methods.R access-methods.R
coerce-methods.R resampling.R unmaskedRegions.R
partitionRegions-methods.R genotypeMatrix-methods.R
computeKernel.R computePvalues.R readGenotypeMatrix-methods.R
readVariantInfo-methods.R readSampleNamesFromVcfHeader.R
readRegionsFromBedFile.R weightFuncs.R assocTest-methods.R
nullModel-methods.R qqplot-methods.R plot-methods.R
filterResult-methods.R split-methods.R computeWeights.R
biocViews: Genetics, WholeGenome, Annotation, VariantAnnotation,
Sequencing, DataImport
NeedsCompilation: yes
Packaged: 2016-05-16 05:21:25 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Annotation, DataImport, Genetics, Sequencing, VariantAnnotation, WholeGenome
22 images, 25 functions, 2 datasets
● Reverse Depends: 0

qrqc : Quick Read Quality Control

Package: qrqc
Version: 1.26.0
Date: 2012-04-17
Title: Quick Read Quality Control
Author: Vince Buffalo
Maintainer: Vince Buffalo <>
Imports: reshape, ggplot2, Biostrings, biovizBase, graphics, methods,
plyr, stats
Depends: reshape, ggplot2, Biostrings, biovizBase, brew, xtable,
Rsamtools (>= 1.19.38), testthat
LinkingTo: Rsamtools
Description: Quickly scans reads and gathers statistics on base and
quality frequencies, read length, k-mers by position, and
frequent sequences. Produces graphical output of statistics for
use in quality control pipelines, and an optional HTML quality
report. S4 SequenceSummary objects allow specific tests and
functionality to be written around the data collected.
License: GPL (>=2)
biocViews: Sequencing, QualityControl, DataImport, Preprocessing,
NeedsCompilation: yes
Packaged: 2016-05-04 04:01:43 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: DataImport, Preprocessing, QualityControl, Sequencing, Visualization
29 images, 27 functions, 0 datasets
● Reverse Depends: 0

r3Cseq : Analysis of Chromosome Conformation Capture and Next-generation Sequencing (3C-seq)

Package: r3Cseq
Version: 1.18.0
Title: Analysis of Chromosome Conformation Capture and Next-generation
Sequencing (3C-seq)
Author: Supat Thongjuea, MRC Molecular Haematology Unit, Weatherall
Institute of Molecular Medicine, University of Oxford, UK
Maintainer: Supat Thongjuea <>
Depends: GenomicRanges, Rsamtools, rtracklayer, VGAM, qvalue
Imports: methods, GenomeInfoDb, IRanges, Biostrings, data.table, sqldf,
Suggests: BSgenome.Mmusculus.UCSC.mm9.masked,
Description: This package is an implementation of data analysis for the
long-range interactions from 3C-seq assay.
License: GPL-3
Collate: AllClasses.R AllGenerics.R Export.R FunctionInCommon.R
FunctionsForBatchAnalysis.R RestrictionEnzymeFunctions.R
FunctionsForNoReplicationAnalysis.R Report.R Visualize3Cseq.R
biocViews: Preprocessing, Sequencing
NeedsCompilation: no
Packaged: 2016-05-04 04:17:49 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Preprocessing, Sequencing
● 0 images, 37 functions, 8 datasets
● Reverse Depends: 0