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Results 1 - 10 of 20 found.
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deepSNV : Detection of subclonal SNVs in deep sequencing data.

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]

● Data Source: BioConductor
● BiocViews: DataImport, GeneticVariability, Genetics, SNP, Sequencing
27 images, 35 functions, 0 datasets
● Reverse Depends: 0

ensemblVEP : R Interface to Ensembl Variant Effect Predictor

Package: ensemblVEP
Version: 1.12.0
Title: R Interface to Ensembl Variant Effect Predictor
Author: Valerie Obenchain
Maintainer: Bioconductor Package Maintainer <maintainer@bioconductor.org>
Depends: methods, BiocGenerics, GenomicRanges, VariantAnnotation
Imports: S4Vectors (>= 0.9.25), Biostrings, SummarizedExperiment
Suggests: RUnit
Description: Query the Ensembl Variant Effect Predictor via the perl API
SystemRequirements: Ensembl VEP (API version 84) and the Perl package
DBD::mysql must be installed. See the package README and
Ensembl web site,
http://www.ensembl.org/info/docs/tools/vep/index.html for
installation instructions.
License: Artistic-2.0
LazyLoad: yes
biocViews: Annotation, VariantAnnotation, SNP
NeedsCompilation: no
Packaged: 2016-05-04 04:49:45 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Annotation, SNP, VariantAnnotation
● 0 images, 4 functions, 0 datasets
● Reverse Depends: 0

GoogleGenomics : R Client for Google Genomics API

Package: GoogleGenomics
Version: 1.4.2
Date: 2015-07-13
Title: R Client for Google Genomics API
Authors@R: c(person("Cassie", "Doll", role = c("aut")),
person("Nicole", "Deflaux", role = c("aut")),
person("Siddhartha", "Bagaria", role = c("aut", "cre"),
email="sidb@google.com"))
Depends: R (>= 3.1.0), GenomicAlignments (>= 1.0.1), VariantAnnotation
Imports: Biostrings, GenomeInfoDb, GenomicRanges, IRanges, httr, rjson,
Rsamtools, S4Vectors (>= 0.9.25)
Suggests: BiocStyle, httpuv, knitr, rmarkdown, testthat, ggbio,
ggplot2, BSgenome.Hsapiens.UCSC.hg19, org.Hs.eg.db,
TxDb.Hsapiens.UCSC.hg19.knownGene
Description: Provides an R package to interact with the Google Genomics API.
VignetteBuilder: knitr
License: Apache License (== 2.0) | file LICENSE
URL: https://cloud.google.com/genomics/
BugReports: https://github.com/Bioconductor/GoogleGenomics/issues
biocViews: DataImport, ThirdPartyClient
NeedsCompilation: no
Packaged: 2016-05-16 05:25:22 UTC; biocbuild
Author: Cassie Doll [aut],
Nicole Deflaux [aut],
Siddhartha Bagaria [aut, cre]
Maintainer: Siddhartha Bagaria <sidb@google.com>

● Data Source: BioConductor
● BiocViews: DataImport, ThirdPartyClient
● 0 images, 10 functions, 0 datasets
● Reverse Depends: 0

HTSeqGenie : A NGS analysis pipeline.

Package: HTSeqGenie
Imports: BiocGenerics (>= 0.2.0), S4Vectors (>= 0.9.25), IRanges (>=
1.21.39), GenomicRanges (>= 1.23.21), Rsamtools (>= 1.8.5),
Biostrings (>= 2.24.1), chipseq (>= 1.6.1), hwriter (>= 1.3.0),
Cairo (>= 1.5.5), GenomicFeatures (>= 1.9.31), BiocParallel,
parallel, tools, rtracklayer (>= 1.17.19), GenomicAlignments,
VariantTools (>= 1.7.7), GenomeInfoDb, SummarizedExperiment,
methods
Maintainer: Jens Reeder <reeder.jens@gene.com>
License: Artistic-2.0
Title: A NGS analysis pipeline.
Type: Package
LazyLoad: yes
Author: Gregoire Pau, Jens Reeder
Description: Libraries to perform NGS analysis.
Version: 4.2.0
Depends: R (>= 3.0.0), gmapR (>= 1.8.0), ShortRead (>= 1.19.13),
VariantAnnotation (>= 1.8.3)
Suggests: TxDb.Hsapiens.UCSC.hg19.knownGene, LungCancerLines,
org.Hs.eg.db
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-05-04 04:46:04 UTC; biocbuild

● Data Source: BioConductor
● 0 images, 129 functions, 0 datasets
● Reverse Depends: 0

CNVrd2 : CNVrd2: a read depth-based method to detect and genotype complex common copy number variants from next generation sequencing data.

Package: CNVrd2
Type: Package
Title: CNVrd2: a read depth-based method to detect and genotype complex
common copy number variants from next generation sequencing
data.
Version: 1.10.2
Date: 2014-10-04
Author: Hoang Tan Nguyen, Tony R Merriman and Mik Black
Depends: R (>= 3.0.0), methods, VariantAnnotation, parallel, rjags,
ggplot2, gridExtra
VignetteBuilder: knitr
Suggests: knitr
Maintainer: Hoang Tan Nguyen <hoangtannguyenvn@gmail.com>
Description: CNVrd2 uses next-generation sequencing data to measure human gene copy number for multiple samples,
indentify SNPs tagging copy number variants and detect copy
number polymorphic genomic regions.
License: GPL-2
Imports: DNAcopy, IRanges, Rsamtools
biocViews: CopyNumberVariation, SNP, Sequencing, Software, Coverage,
LinkageDisequilibrium, Clustering.
Collate: AllClasses.R AllGenerics.R countReadInWindow.R
segmentSamples.R segmentSamplesUsingPopInformation.R
identifyPolymorphicRegion.R plotPolymorphicRegion.R
emnormalCNV.R groupCNVs.R searchGroupCNVs.R groupBayesianCNVs.R
plotCNVrd2.R calculateLDSNPandCNV.R
URL: https://github.com/hoangtn/CNVrd2
Packaged: 2016-05-16 04:11:56 UTC; biocbuild
NeedsCompilation: no

● Data Source: BioConductor
● BiocViews: Clustering., CopyNumberVariation, Coverage, LinkageDisequilibrium, SNP, Sequencing, Software
4 images, 26 functions, 1 datasets
● Reverse Depends: 0

DOQTL : Genotyping and QTL Mapping in DO Mice

Package: DOQTL
Version: 1.8.0
Date: 2012-12-07
Title: Genotyping and QTL Mapping in DO Mice
Author: Daniel Gatti, Karl Broman, Andrey Shabalin, Petr Simecek
Maintainer: Daniel Gatti <Dan.Gatti@jax.org>
Depends: R (>= 3.0.0), BSgenome.Mmusculus.UCSC.mm10, GenomicRanges,
VariantAnnotation
Imports: annotate, annotationTools, biomaRt, Biobase, BiocGenerics,
corpcor, doParallel, foreach, fpc, hwriter, IRanges, iterators,
mclust, QTLRel, regress, rhdf5, Rsamtools, RUnit, XML
Suggests: MUGAExampleData, doMPI
Description: DOQTL is a quantitative trait locus (QTL) mapping pipeline designed for Diversity Outbred mice and other multi-parent outbred populations. The package reads in data from genotyping arrays and perform haplotype reconstruction using a hidden Markov model (HMM). The haplotype probabilities from the HMM are then used to perform linkage mapping. When founder sequences are available, DOQTL can use the haplotype reconstructions to impute the founder sequences onto DO genomes and perform association mapping.
biocViews: GeneticVariability, SNP, Genetics, HiddenMarkovModel
License: GPL-3
LazyData: true
ByteCompile: yes
URL: http://do.jax.org
NeedsCompilation: yes
Packaged: 2016-05-04 05:39:30 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: GeneticVariability, Genetics, HiddenMarkovModel, SNP
● 0 images, 85 functions, 7 datasets
● Reverse Depends: 0

RareVariantVis : Visualization of rare variants in whole genome sequencing data

Package: RareVariantVis
Type: Package
Title: Visualization of rare variants in whole genome sequencing data
Version: 1.6.2
Date: 2016-04-23
Author: Tomasz Stokowy
Maintainer: Tomasz Stokowy <tomasz.stokowy@k2.uib.no>
Description: Genomic variants can be analyzed and visualized using many
tools. Unfortunately, number of tools for global interrogation
of variants is limited. Package RareVariantVis aims to present
genomic variants (especially rare ones) in a global, per
chromosome way. Visualization is performed in two ways -
standard that outputs png figures and interactive that uses
JavaScript d3 package. Interactive visualization allows to
analyze trio/family data, for example in search for causative
variants in rare Mendelian diseases.
License: Artistic-2.0
LazyData: TRUE
Depends: BiocGenerics, VariantAnnotation, googleVis
Imports: S4Vectors, IRanges, GenomeInfoDb, GenomicRanges
Suggests: knitr, AshkenazimSonChr21
VignetteBuilder: knitr
biocViews: GenomicVariation, Sequencing, WholeGenome
NeedsCompilation: no
Packaged: 2016-05-16 05:29:45 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: GenomicVariation, Sequencing, WholeGenome
● 0 images, 5 functions, 4 datasets
● Reverse Depends: 0

Rariant : Identification and Assessment of Single Nucleotide Variants through Shifts in Non-Consensus Base Call Frequencies

Package: Rariant
Type: Package
Title: Identification and Assessment of Single Nucleotide Variants
through Shifts in Non-Consensus Base Call Frequencies
Version: 1.8.3
Author: Julian Gehring, Simon Anders, Bernd Klaus
Maintainer: Julian Gehring <jg-bioc@gmx.com>
Imports: methods, S4Vectors, IRanges, GenomeInfoDb, ggbio, ggplot2,
exomeCopy, SomaticSignatures, Rsamtools, shiny, VGAM, dplyr,
reshape2
Depends: R (>= 3.0.2), GenomicRanges, VariantAnnotation
Suggests: h5vcData, testthat, knitr, optparse,
BSgenome.Hsapiens.UCSC.hg19
Description: The 'Rariant' package identifies single nucleotide variants from sequencing data based on the difference of binomially distributed mismatch rates between matched samples.
VignetteBuilder: knitr
Encoding: UTF-8
ByteCompile: TRUE
License: GPL-3
URL: https://github.com/juliangehring/Rariant
BugReports: https://support.bioconductor.org
LazyLoad: yes
biocViews: Sequencing, StatisticalMethod, GenomicVariation,
SomaticMutation, VariantDetection, Visualization
NeedsCompilation: no
Packaged: 2016-05-16 04:27:15 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: GenomicVariation, Sequencing, SomaticMutation, StatisticalMethod, VariantDetection, Visualization
6 images, 18 functions, 0 datasets
● Reverse Depends: 0

PolyPhen.Hsapiens.dbSNP131 : PolyPhen Predictions for Homo sapiens dbSNP build 131

Package: PolyPhen.Hsapiens.dbSNP131
Title: PolyPhen Predictions for Homo sapiens dbSNP build 131
Description: Database of PolyPhen predictions for Homo sapiens dbSNP build 131
Version: 1.0.2
Author: Valerie Obenchain
Maintainer: Valerie Obenchain <vobencha@fhcrc.org>
Depends: VariantAnnotation, RSQLite (>= 0.11.0)
Imports: AnnotationDbi
License: Artistic-2.0
organism: Homo sapiens
species: Human
provider: PolyPhen2
source_url: http://genetics.bwh.harvard.edu/pph2/dokuwiki/downloads
biocViews: AnnotationData, Genetics, Homo_sapiens
Packaged: 2012-03-13 23:16:49 UTC; vobencha

● Data Source: BioConductor
● BiocViews: AnnotationData, Genetics, Homo_sapiens
● 0 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