Package: consensusSeekeR
Version: 1.0.2
Date: 2015-05-01
Title: Detection of consensus regions inside a group of experiences
using genomic positions and genomic ranges
Description: This package compares genomic positions and genomic ranges from
multiple experiments to extract common regions. The size of the analyzed region
is adjustable as well as the number of experiences in which a feature must be
present in a potential region to tag this region as a consensus region.
Author: Astrid Deschenes [cre, aut], Fabien Claude Lamaze [ctb], Pascal Belleau
[aut], Arnaud Droit [aut]
Author@R: c(person("Astrid", "Deschenes", email="Astrid-
Louise.Deschenes@crchudequebec.ulaval.ca",
role=c("cre","aut")), person("Fabien Claude", "Lamaze",
email="fabien.lamaze.1@ulaval.ca", role=c("ctb")),
person("Pascal", "Belleau",
email="pascal.belleau@crchuq.ulaval.ca", role=c("aut")),
person("Arnaud", "Droit",
email="arnaud.droit@crchuq.ulaval.ca", role=c("aut")))
Depends: R (>= 2.10), BiocGenerics, IRanges, GenomicRanges, BiocParallel
Imports: GenomeInfoDb, rtracklayer, stringr, S4Vectors
Suggests: BiocStyle, ggplot2, knitr, RUnit
License: Artistic-2.0
URL: https://github.com/ArnaudDroitLab/consensusSeekeR
BugReports: https://github.com/ArnaudDroitLab/consensusSeekeR/issues
VignetteBuilder: knitr
NeedsCompilation: no
biocViews: BiologicalQuestion, ChIPSeq, Genetics, MultipleComparison,
Transcription, PeakDetection, Sequencing, Coverage
Maintainer: Astrid Louise Deschenes <Astrid-Louise.Deschenes@crchudequebec.ulaval.ca>
RoxygenNote: 5.0.1
Packaged: 2016-05-16 05:51:37 UTC; biocbuild
Package: deepSNV
Maintainer: Moritz Gerstung <mg14@sanger.ac.uk>
License: GPL-3
Title: Detection of subclonal SNVs in deep sequencing data.
biocViews: GeneticVariability, SNP, Sequencing, Genetics, DataImport
LinkingTo: Rhtslib
Type: Package
LazyLoad: yes
Authors@R: c( person("Niko","Beerenwinkel", role="ths"),
person("David", "Jones", role = "ctb"),
person("Inigo", "Martincorena", role = "ctb"),
person("Moritz","Gerstung",
email = "mg14@sanger.ac.uk", role= c("aut","cre")) )
Description: This package provides provides quantitative variant callers for
detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing
experiments. The deepSNV algorithm is used for a comparative setup with a
control experiment of the same loci and uses a beta-binomial model and a
likelihood ratio test to discriminate sequencing errors and subclonal SNVs.
The shearwater algorithm computes a Bayes classifier based on a
beta-binomial model for variant calling with multiple samples for
precisely estimating model parameters such as local error rates and
dispersion and prior knowledge, e.g. from variation data bases such as
COSMIC.
Version: 1.18.1
URL: http://github.com/mg14/deepSNV
Depends: R (>= 2.13.0), methods, graphics, parallel, Rhtslib, IRanges, GenomicRanges, SummarizedExperiment, Biostrings, VGAM, VariantAnnotation (>= 1.13.44),
Imports: Rhtslib
Suggests: RColorBrewer, knitr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2016-05-12 03:17:01 UTC; biocbuild
Author: Niko Beerenwinkel [ths],
David Jones [ctb],
Inigo Martincorena [ctb],
Moritz Gerstung [aut, cre]
Package: epigenomix
Type: Package
Title: Epigenetic and gene transcription data normalization and
integration with mixture models
Version: 1.12.0
Date: 2016-02-08
Author: Hans-Ulrich Klein, Martin Schaefer
Maintainer: Hans-Ulrich Klein <h.klein@uni-muenster.de>
Depends: R (>= 3.2.0), methods, Biobase, S4Vectors, IRanges, GenomicRanges, SummarizedExperiment
Imports: BiocGenerics, MCMCpack, Rsamtools, parallel, GenomeInfoDb, beadarray
Description: A package for the integrative analysis of RNA-seq or
microarray based gene transcription and histone modification
data obtained by ChIP-seq. The package provides methods for
data preprocessing and matching as well as methods for fitting
bayesian mixture models in order to detect genes with
differences in both data types.
License: LGPL-3
biocViews: ChIPSeq, GeneExpression, DifferentialExpression,
Classification
NeedsCompilation: no
Packaged: 2016-05-04 04:53:55 UTC; biocbuild
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, parallel
Suggests: BiocStyle
Maintainer: Hugo Varet <varethugo@gmail.com>
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 )
URL: http://www.sbim.fr/rfPred
biocViews: Software, Annotation, Classification
NeedsCompilation: yes
Packaged: 2016-05-04 05:02:18 UTC; biocbuild
Package: scsR
Type: Package
Title: SiRNA correction for seed mediated off-target effect
Version: 1.8.0
Date: 2014-10-28
Author: Andrea Franceschini
Maintainer: Andrea Franceschini <andrea.franceschini@isb-sib.ch>, Roger Meier <roger.meier@lmsc.ethz.ch>, Christian von Mering <mering@imls.uzh.ch>
Description: Corrects genome-wide siRNA screens for seed mediated off-target effect. Suitable functions to identify the effective seeds/miRNAs and to visualize their effect are also provided in the package.
License: GPL-2
Depends: R (>= 2.14.0), STRINGdb, methods, BiocGenerics, Biostrings, IRanges, plyr, tcltk
Imports: sqldf, hash, ggplot2, graphics, grDevices, RColorBrewer
Suggests: RUnit
biocViews: Preprocessing
NeedsCompilation: no
Packaged: 2016-05-04 05:20:40 UTC; biocbuild
Package: segmentSeq
Type: Package
Title: Methods for identifying small RNA loci from high-throughput
sequencing data
Version: 2.6.0
Date: 2010-01-20
Author: Thomas J. Hardcastle
Maintainer: Thomas J. Hardcastle <tjh48@cam.ac.uk>
Description: High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery.
License: GPL-3
LazyLoad: yes
Depends: R (>= 2.3.0), methods, baySeq (>= 1.99.0), ShortRead, GenomicRanges, IRanges, S4Vectors
Suggests: BiocStyle, BiocGenerics
Imports: graphics, grDevices, utils
biocViews: MultipleComparison, Sequencing, Alignment,
DifferentialExpression, QualityControl, DataImport
Packaged: 2016-05-04 04:02:57 UTC; biocbuild
NeedsCompilation: no
providing 
.