SubCellBarCode
SubCellBarCode: Integrated workflow for robust mapping and visualizing whole human spatial proteome
Bioconductor version: 3.24 · Package version: 1.29.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Mass-Spectrometry based spatial proteomics have enabled the proteome-wide mapping of protein subcellular localization (Orre et al. 2019, Molecular Cell). SubCellBarCode R package robustly classifies proteins into corresponding subcellular localization.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SubCellBarCode")Details
| Maintainer | Taner Arslan <taner.arslan@ki.se> |
| Author | Taner Arslan |
| License | GPL-2 |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | Classification, MassSpectrometry, Proteomics, Software |
| Package Short Url | https://bioconductor.org/packages/SubCellBarCode/ |
Citation
From within R, enter citation("SubCellBarCode"):
Taner Arslan. SubCellBarCode: SubCellBarCode: Integrated workflow for robust mapping and visualizing whole human spatial proteome. doi:10.18129/B9.bioc.SubCellBarCode, R package version 1.29.0, https://bioconductor.org/packages/SubCellBarCode.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | SubCellBarCode_1.29.0.tar.gz |
| Windows binary (x86_64) | SubCellBarCode_1.29.0.zip |
| macOS binary (arm64) | SubCellBarCode_1.29.0.tgz |
| macOS binary (x86_64) | SubCellBarCode_1.29.0.tgz |
Dependencies
Depends: R (>= 3.6)
Imports: Rtsne, scatterplot3d, caret, e1071, ggplot2, gridExtra, networkD3, ggrepel, graphics, stats, org.Hs.eg.db, AnnotationDbi