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SubCellBarCode: Integrated workflow for robust mapping and visualizing whole human spatial proteome

Bioconductor version: Release (3.19)

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.

Author: Taner Arslan

Maintainer: Taner Arslan <taner.arslan at>

Citation (from within R, enter citation("SubCellBarCode")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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:

SubCellBarCode R Markdown vignettes HTML R Script
Reference Manual PDF


biocViews Classification, MassSpectrometry, Proteomics, Software
Version 1.20.0
In Bioconductor since BioC 3.9 (R-3.6) (5 years)
License GPL-2
Depends R (>= 3.6)
Imports Rtsne, scatterplot3d, caret, e1071, ggplot2, gridExtra, networkD3, ggrepel, graphics, stats,, AnnotationDbi
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Suggests knitr, rmarkdown, BiocStyle
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Follow Installation instructions to use this package in your R session.

Source Package SubCellBarCode_1.20.0.tar.gz
Windows Binary
macOS Binary (x86_64) SubCellBarCode_1.20.0.tgz
macOS Binary (arm64) SubCellBarCode_1.20.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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Old Source Packages for BioC 3.19 Source Archive