To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("pRoloc")

In most cases, you don't need to download the package archive at all.

pRoloc

A unifying bioinformatics framework for spatial proteomics

Bioconductor version: 2.13

This package implements pattern recognition techniques on quantitiative mass spectrometry data to infer protein sub-cellular localisation.

Author: Laurent Gatto and Lisa M. Breckels with contributions from Thomas Burger and Samuel Wieczorek

Maintainer: Laurent Gatto <lg390 at cam.ac.uk>

Citation (from within R, enter citation("pRoloc")):

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("pRoloc")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("pRoloc")

 

PDF R Script Machine learning techniques available in pRoloc
PDF R Script pRoloc -- A unifying bioinformatics framework for organelle proteomics
PDF R Script pRoloc tutorial
PDF   Reference Manual
Text   README
Text   NEWS

Details

biocViews Bioinformatics, Classification, Clustering, MassSpectrometry, Proteomics, Software
Version 1.2.1
In Bioconductor since BioC 2.12 (R-3.0)
License GPL-2
Depends R (>= 2.15), MSnbase(>= 1.7.23), MLInterfaces(>= 1.37.1), methods, Rcpp (>= 0.10.3)
Imports mclust, MSBVAR, caret, e1071, sampling, class, kernlab, lattice, nnet, randomForest, proxy, FNN, BiocGenerics, stats4, RColorBrewer, scales, MASS, knitr
Suggests testthat, pRolocdata, roxygen2, synapter, xtable
System Requirements
URL
Depends On Me
Imports Me
Suggests Me pRolocdata

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source pRoloc_1.2.1.tar.gz
Windows Binary pRoloc_1.2.1.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) pRoloc_1.2.1.tgz
Browse/checkout source (username/password: readonly)
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