A unifying bioinformatics framework for spatial proteomics

Bioconductor version: Development (3.0)

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>

To install this package, start R and enter:


To cite this package in a publication, start R and enter:



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   NEWS


biocViews Classification, Clustering, MassSpectrometry, Proteomics, Software
Version 1.5.1
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), 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
Depends On Me
Imports Me
Suggests Me pRolocdata

Package Downloads

Package Source pRoloc_1.5.1.tar.gz
Windows Binary (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) pRoloc_1.5.1.tgz
Mac OS X 10.9 (Mavericks)
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