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This is the development version of SubCellBarCode; for the stable release version, see SubCellBarCode.

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

Bioconductor version: Development (3.20)

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))

# The following initializes usage of Bioc devel


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 1.21.0
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_1.21.0.tar.gz
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macOS Binary (x86_64) SubCellBarCode_1.21.0.tgz
macOS Binary (arm64) SubCellBarCode_1.21.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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