This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see pRoloc.
Bioconductor version: 3.9
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 "3.6") and enter:
if (!requireNamespace("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_1.24.1.tar.gz |
Windows Binary | pRoloc_1.24.1.zip (32- & 64-bit) |
Mac OS X 10.11 (El Capitan) | pRoloc_1.24.1.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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