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: Release (2.14)

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>

To install this package, start R and enter:

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

Installation

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 Classification, Clustering, MassSpectrometry, Proteomics, Software
Version 1.4.0
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), BiocParallel
Imports mclust (>= 4.3), 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_1.4.0.tar.gz
Windows Binary pRoloc_1.4.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) pRoloc_1.4.0.tgz
Mac OS X 10.9 (Mavericks) pRoloc_1.4.0.tgz
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