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This package is for version 3.3 of Bioconductor; for the stable, up-to-date release version, see pRoloc.

A unifying bioinformatics framework for spatial proteomics

Bioconductor version: 3.3

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>

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PDF R Script A transfer learning algorithm for spatial proteomics
PDF R Script HUPO 2011 poster: pRoloc -- A unifying bioinformatics framework for organelle proteomics
PDF R Script HUPO 2014 poster: A state-of-the-art machine learning pipeline for the analysis of spatial proteomics data
PDF Machine learning techniques available in pRoloc
PDF pRoloc tutorial
HTML R Script Annotating spatial proteomics data
PDF   Reference Manual
Text   NEWS
Video   pRoloc, pRolocdata and pRolocGUI


biocViews Classification, Clustering, MassSpectrometry, Proteomics, QualityControl, Software
Version 1.12.4
In Bioconductor since BioC 2.12 (R-3.0) (3.5 years)
License GPL-2
Depends R (>= 2.15), MSnbase(>= 1.19.20), MLInterfaces(>= 1.37.1), methods, Rcpp (>= 0.10.3), BiocParallel
Imports Biobase, mclust (>= 4.3), caret, e1071, sampling, class, kernlab, lattice, nnet, randomForest, proxy, FNN, BiocGenerics, stats, RColorBrewer, scales, MASS, knitr, mvtnorm, gtools, plyr, ggplot2, biomaRt, utils, grDevices, graphics
LinkingTo Rcpp, RcppArmadillo
Suggests testthat, pRolocdata(>= 1.9.4), roxygen2, synapter, xtable, tsne, BiocStyle, hpar, dplyr, GO.db, AnnotationDbi
Depends On Me pRolocGUI
Imports Me
Suggests Me MSnbase, pRolocdata, RforProteomics
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