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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MSnbase")
In most cases, you don't need to download the package archive at all.
MSnbase
MSnbase: Base Functions and Classes for MS-based Proteomics
Bioconductor version: 2.14
Basic plotting, data manipulation and processing of MS-based Proteomics data
Author: Laurent Gatto <lg390 at cam.ac.uk> with contributions from Guangchuang Yu, Samuel Wieczorek, Vasile-Cosmin Lazar, Vladislav Petyuk and Sebastian Gibb.
Maintainer: Laurent Gatto <lg390 at cam.ac.uk>
Citation (from within R,
enter citation("MSnbase")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MSnbase")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MSnbase")
| R Script | Base Functions and Classes for MS-based Proteomics | |
| R Script | MSnbase development | |
| R Script | MSnbase IO capabilities | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Infrastructure, MassSpectrometry, Proteomics, QualityControl, Software |
| Version | 1.12.1 |
| In Bioconductor since | BioC 2.8 (R-2.13) |
| License | Artistic-2.0 |
| Depends | R (>= 3.1), methods, BiocGenerics(>= 0.7.1), Biobase(>= 2.15.2), ggplot2, mzR |
| Imports | plyr, IRanges, preprocessCore, vsn, grid, reshape2, stats4, affy, impute, pcaMethods, mzID(>= 1.1.5) |
| Suggests | testthat, zoo, knitr (>= 1.1.0), rols, Rdisop, pRolocdata(>= 1.0.7), msdata |
| System Requirements | |
| URL | |
| Depends On Me | msmsEDA, msmsTests, MSstats, ProCoNA, pRoloc, pRolocdata, synapter |
| Imports Me | |
| Suggests Me | isobar, qcmetrics, RforProteomics, rpx |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | MSnbase_1.12.1.tar.gz |
| Windows Binary | MSnbase_1.12.1.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | MSnbase_1.12.1.tgz |
| Mac OS X 10.9 (Mavericks) | MSnbase_1.12.1.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
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