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

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>

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)
Package Downloads Report	Download Stats