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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("chipseq")
In most cases, you don't need to download the package archive at all.
chipseq
chipseq: A package for analyzing chipseq data
Bioconductor version: 3.0
Tools for helping process short read data for chipseq experiments
Author: Deepayan Sarkar, Robert Gentleman, Michael Lawrence, Zizhen Yao
Maintainer: Bioconductor Package Maintainer <maintainer at bioconductor.org>
Citation (from within R,
enter citation("chipseq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("chipseq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("chipseq")
| R Script | A Sample ChIP-Seq analysis workflow | |
| Reference Manual |
Details
| biocViews | ChIPSeq, Coverage, DataImport, QualityControl, Sequencing, Software |
| Version | 1.16.0 |
| In Bioconductor since | BioC 2.5 (R-2.10) |
| License | Artistic-2.0 |
| Depends | R (>= 2.10), methods, BiocGenerics(>= 0.1.0), S4Vectors(>= 0.0.1), IRanges(>= 1.99.1), GenomicRanges(>= 1.17.7), BSgenome, ShortRead |
| Imports | methods, BiocGenerics, IRanges, BSgenome, GenomicRanges, lattice, ShortRead, stats |
| LinkingTo | |
| Suggests | GenomicFeatures, TxDb.Mmusculus.UCSC.mm9.knownGene |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | PING |
| Imports Me | ChIPQC, HTSeqGenie |
| Suggests Me | ggbio, oneChannelGUI |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | chipseq_1.16.0.tar.gz |
| Windows Binary | chipseq_1.16.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | chipseq_1.16.0.tgz |
| Mac OS X 10.9 (Mavericks) | chipseq_1.16.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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