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https://github.com/lgatto/proloc

A unifying bioinformatics framework for organelle proteomics
https://github.com/lgatto/proloc

bioconductor proteomics proteomics-data r spatial-proteomics visualisation

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A unifying bioinformatics framework for organelle proteomics

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README 

        
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# A unifying bioinformatics framework for spatial proteomics






The `pRoloc` suite set of software offers a complete software pipeline

to analyse, visualise and interpret mass spectrometry-based spatial

proteomics data such, for example, as LOPIT (Localization of Organelle

Proteins by Isotope Tagging), PCP (Protein Correlation Profiling) or

hyperLOPIT (hyperplexed LOPIT). The suite includes

[`pRoloc`](http://www.bioconductor.org/packages/release/bioc/html/pRoloc.html),

the mail software that focuses on data analysis using state-of-the-art

machine learning,

[`pRolocdata`](http://bioconductor.org/packages/release/data/experiment/html/pRolocdata.html),

that distributes numerous datasets, and [`pRolocGUI`](https://lgatto.github.io/pRolocGUI/), that offers

interactive visualisations dedicated to spatial proteomics. The

software are distributed as part of the

R/[Bioconductor](http://bioconductor.org/) project.



## Getting started



The `pRoloc` software comes with ample

documentation. The

[main tutorial](https://lgatto.github.io/pRoloc/articles/v01-pRoloc-tutorial.html) provides

a broad overview of the package and its functionality.  See the

*Articles* tab for additional manuals.



[`pRolocGUI`](http://www.bioconductor.org/packages/release/bioc/html/pRolocGUI.html)

also offer several documentation files.



Here are a set of

[video tutorial](https://www.youtube.com/playlist?list=PLvIXxpatSLA2loV5Srs2VBpJIYUlVJ4ow)

that illustrate the `pRoloc` framework.



## Help



Post your questions on the

[Bioconductor support site](https://support.bioconductor.org/),

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](https://github.com/lgatto/pRoloc/issues) on the github

development page.



## Installation



The preferred installation procedure uses the Bioconductor

infrastructure:



```c

## unless BiocManager is already installed

install.packages("BiocManager")

## then

BiocManager::install("pRoloc")

BiocManager::install("pRolocdata")

BiocManager::install("pRolocGUI")

```



### Pre-release/development version



The pre-release/development code on github can also be installed using

`BiocManager::install`, as shown below. Note that this requires a

working R build environment (i.e `Rtools` on Windows - see

[here](https://github.com/lgatto/teachingmaterial/wiki/R-package)). New

pre-release features might not be documented not thoroughly tested and

could substantially change prior to release. Use at your own risks.



```c

## unless BiocManager is already installed

install.packages("BiocManager")

## then, install from github

BiocManager::install("lgatto/pRoloc")

BiocManager::install("lgatto/pRolocdata")

BiocManager::install("lgatto/pRolocGUI")

```



## References:



For refences about the software, how to use it and spatial proteomics

data analysis:



* Crook OM, Breckels LM, Lilley KS, Kirk PWD, Gatto L. A Bioconductor

  workflow for the Bayesian analysis of spatial proteomics [version 1;

  peer review: awaiting peer review]. F1000Research 2019, 8:446

  (https://doi.org/10.12688/f1000research.18636.1)



* Breckels LM, Mulvey CM, Lilley KS and Gatto L. A Bioconductor

  workflow for processing and analysing spatial proteomics data

  [version 2; peer review: 2 approved]. F1000Research 2018, 5:2926

  (https://doi.org/10.12688/f1000research.10411.2)



* 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](http://www.ncbi.nlm.nih.gov/pubmed/24846987)



* 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](http://www.ncbi.nlm.nih.gov/pubmed/24413670).



Specific algorithms available in the software:



* 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](http://www.ncbi.nlm.nih.gov/pubmed/23523639).



* 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: http://dx.doi.org/10.1101/022152



* Oliver M Crook, Claire M Mulvey, Paul D. W. Kirk, Kathryn S Lilley,

 Laurent Gatto *A Bayesian Mixture Modelling Approach For Spatial

 Proteomics* PLOS Computational Biology

 doi:[10.1371/journal.pcbi.1006516](https://doi.org/10.1371/journal.pcbi.1006516)



#### More resource



* R and Bioconductor for proteomics

  [web page](http://lgatto.github.io/RforProteomics/) and

  [package](http://www.bioconductor.org/packages/release/data/experiment/html/RforProteomics.html)



* Bioconductor proteomics [workflow](http://bioconductor.org/help/workflows/proteomics/)



## Contributing



Contributions to the package are more than welcome. If you want to

contribute to this package, you should follow the same conventions as

the rest of the functions whenever it makes sense to do so. Feel free

to get in touch (preferable opening a

[github issue](https://github.com/lgatto/pRoloc/issues/)) to discuss

any suggestions.



Please note that this project is released with a

[Contributor Code of Conduct](https://github.com/lgatto/pRoloc/blob/master/CONDUCT.md).

By participating in this project you agree to abide by its terms.