pRoloc
A unifying bioinformatics framework for spatial proteomics
Bioconductor version: 3.23 · Package version: 1.52.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("pRoloc")Details
| Maintainer | Lisa Breckels <lms79@cam.ac.uk> |
| Author | Laurent Gatto [aut], Lisa Breckels [aut, cre], Thomas Burger [ctb], Samuel Wieczorek [ctb], Charlotte Hutchings [ctb], Oliver Crook [aut] |
| License | GPL-2 |
| URL | https://github.com/lgatto/pRoloc |
| Bug Reports | https://github.com/lgatto/pRoloc/issues |
| Downloads rank | 926 |
| Source branch | RELEASE_3_23 |
| biocViews | Classification, Clustering, ImmunoOncology, MassSpectrometry, Proteomics, QualityControl, Software |
Documentation
- A transfer learning algorithm for spatial proteomics
- Bayesian Analysis of Spatial Proteomics data using pRoloc
- Machine learning techniques available in pRoloc
- Using pRoloc for spatial proteomics data analysis
Download
Dependencies
Depends: R (>= 3.5), MSnbase (>= 1.19.20), MLInterfaces (>= 1.67.10), methods, Rcpp (>= 0.10.3), BiocParallel
Imports: stats4, Biobase, mclust (>= 4.3), caret, e1071, sampling, class, kernlab, lattice, nnet, randomForest, proxy, FNN, hexbin, BiocGenerics, stats, dendextend, RColorBrewer, scales, MASS, knitr, mvtnorm, LaplacesDemon, coda, mixtools, gtools, plyr, ggplot2, biomaRt, utils, grDevices, graphics, colorspace
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, rmarkdown, pRolocdata (>= 1.43.2), roxygen2, xtable, rgl, BiocStyle (>= 2.5.19), hpar (>= 1.41.0), dplyr, akima, fields, vegan, GO.db, AnnotationDbi, Rtsne (>= 0.13), nipals, reshape, magick, umap
Reverse dependencies
Depends On Me (2): bandle, pRolocGUI
Suggests Me (3): MSnbase, pRolocdata, RforProteomics