To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("nucleR")
In most cases, you don't need to download the package archive at all.
nucleR
Nucleosome positioning package for R
Bioconductor version: 3.0
Nucleosome positioning for Tiling Arrays and Next Generation Sequencing Experiments
Author: Oscar Flores, David Rossell
Maintainer: Oscar Flores <oflores at mmb.pcb.ub.es>
Citation (from within R,
enter citation("nucleR")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("nucleR")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("nucleR")
| R Script | Quick analysis of nucleosome positioning experiments | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | ChIPSeq, Genetics, Microarray, Sequencing, Software |
| Version | 1.14.0 |
| In Bioconductor since | BioC 2.9 (R-2.14) |
| License | LGPL (>= 3) |
| Depends | methods, BiocGenerics(>= 0.1.0), IRanges(>= 1.13.5), Biobase(>= 2.15.1), ShortRead, parallel |
| Imports | methods, BiocGenerics, S4Vectors, IRanges, Biobase, ShortRead, GenomicRanges, stats |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | htSeqTools |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | nucleR_1.14.0.tar.gz |
| Windows Binary | nucleR_1.14.0.zip |
| Mac OS X 10.6 (Snow Leopard) | nucleR_1.14.0.tgz |
| Mac OS X 10.9 (Mavericks) | nucleR_1.14.0.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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