To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("NuPoP")
In most cases, you don't need to download the package archive at all.
NuPoP
An R package for nucleosome positioning prediction
Bioconductor version: 3.0
NuPoP is an R package for Nucleosome Positioning Prediction.This package is built upon a duration hidden Markov model proposed in Xi et al, 2010; Wang et al, 2008. The core of the package was written in Fotran. In addition to the R package, a stand-alone Fortran software tool is also available at http://nucleosome.stats.northwestern.edu.
Author: Ji-Ping Wang <jzwang at northwestern.edu>; Liqun Xi <lxi700 at northwestern.edu>
Maintainer: Ji-Ping Wang<jzwang at northwestern.edu>
Citation (from within R,
enter citation("NuPoP")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("NuPoP")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("NuPoP")
| R Script | An R package for Nucleosome positioning prediction | |
| Reference Manual |
Details
| biocViews | Classification, Genetics, Software, Visualization |
| Version | 1.16.0 |
| In Bioconductor since | BioC 2.7 (R-2.12) |
| License | GPL-2 |
| Depends | R (>= 2.10) |
| Imports | |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| 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 | NuPoP_1.16.0.tar.gz |
| Windows Binary | NuPoP_1.16.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | NuPoP_1.16.0.tgz |
| Mac OS X 10.9 (Mavericks) | NuPoP_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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