pRoloc is a Bioconductor package for the analysis of experimental spatial proteomics data. It is available from Bioconductor >= 2.12 and requires R (>= 3.0.0).

Current build status:

  • release
  • devel

The pRoloc suite set of software are distributed as part of the R/Bioconductor project and are developed at the Computational Proteomics Unit and Cambridge Centre for Proteomics labs, at the University of Cambridge.

Getting started

The pRoloc software comes with ample documentation. The main tutorial (release and devel) provides a broad overview of the package and its functionality. See the package page (release and devel) for additional manuals.

Two associated packages, pRolocdata (devel and release) and pRolocGUI (release and devel) offer spatial proteomics data and a graphical user interface to interactively explore the data.

Here are a set of video tutorial that illustrate the pRoloc framework.


Post your questions on the Bioconductor support site, tagging it with the package name pRoloc (the maintainer will automatically be notified by email). If you identify a bug or have a feature request, please open an issue on the github development page.


The preferred installation procedure uses the Bioconductor infrastructure:


Pre-release/development version

The pre-release/development code on github can be installed using biocLite. Note that this requires a working R build environment (i.e Rtools on Windows - see here). New pre-release features might not be documented not thoroughly tested and could substantially change prior to release. Use at your own risks.

## install from github


Gatto L, Breckels LM, Wieczorek S, Burger T, Lilley KS. Mass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata. Bioinformatics. 2014 May 1;30(9):1322-4. doi: 10.1093/bioinformatics/btu013. Epub 2014 Jan 11. PubMed PMID: 24413670.

Breckels LM, Gatto L, Christoforou A, Groen AJ, Lilley KS, Trotter MW. The effect of organelle discovery upon sub-cellular protein localisation. J Proteomics. 2013 Aug 2;88:129-40. doi: 10.1016/j.jprot.2013.02.019. Epub 2013 Mar 21. PubMed PMID: 23523639.

Gatto L, Breckels LM, Burger T, Nightingale DJ, Groen AJ, Campbell C, Nikolovski N, Mulvey CM, Christoforou A, Ferro M, Lilley KS. A foundation for reliable spatial proteomics data analysis. Mol Cell Proteomics. 2014 Aug;13(8):1937-52. doi: 10.1074/mcp.M113.036350. Epub 2014 May 20. PubMed PMID: 24846987

Breckels LM, Holden S, Wojnar D, Mulvey CMM, Christoforou A, Groen AJ, Kohlbacher O, Lilley KS and Gatto L. Learning from heterogeneous data sources: an application in spatial proteomics. 2015 biorXiv, doi:

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Last Published

January 1st, 1970

Functions in pRoloc (1.12.4)