 
  
 
   
   This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see pRoloc.
Bioconductor version: 3.15
The pRoloc package implements machine learning and visualisation methods for the analysis and interogation of quantitiative mass spectrometry data to reliably infer protein sub-cellular localisation.
Author: Laurent Gatto, Oliver Crook and Lisa M. Breckels with contributions from Thomas Burger and Samuel Wieczorek
Maintainer: Laurent Gatto <laurent.gatto at uclouvain.be>
Citation (from within R,
      enter citation("pRoloc")):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("pRoloc")
    For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pRoloc")
    
| HTML | R Script | A transfer learning algorithm for spatial proteomics | 
| HTML | R Script | Annotating spatial proteomics data | 
| HTML | R Script | Bayesian spatial proteomics with pRoloc | 
| HTML | R Script | Machine learning techniques available in pRoloc | 
| HTML | R Script | Using pRoloc for spatial proteomics data analysis | 
| Reference Manual | ||
| Text | NEWS | |
| Video | pRoloc, pRolocdata and pRolocGUI | 
Follow Installation instructions to use this package in your R session.
| Source Package | pRoloc_1.36.0.tar.gz | 
| Windows Binary | pRoloc_1.36.0.zip | 
| macOS Binary (x86_64) | pRoloc_1.36.0.tgz | 
| Source Repository | git clone https://git.bioconductor.org/packages/pRoloc | 
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/pRoloc | 
| Package Short Url | https://bioconductor.org/packages/pRoloc/ | 
| Package Downloads Report | Download Stats | 
 
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