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Decontamination of single cell genomics data

Bioconductor version: Release (3.19)

This package contains implementation of DecontX (Yang et al. 2020), a decontamination algorithm for single-cell RNA-seq, and DecontPro (Yin et al. 2023), a decontamination algorithm for single cell protein expression data. DecontX is a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. DecontPro is a Bayesian method that estimates the level of contamination from ambient and background sources in CITE-seq ADT dataset and decontaminate the dataset.

Author: Yuan Yin [aut, cre] , Masanao Yajima [aut] , Joshua Campbell [aut]

Maintainer: Yuan Yin <yuan_yin at>

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


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:

decontPro HTML R Script
Estimate and remove cross-contamination from ambient RNA in single-cell data with DecontX HTML R Script
Reference Manual PDF


biocViews Bayesian, SingleCell, Software
Version 1.2.0
In Bioconductor since BioC 3.18 (R-4.3) (0.5 years)
License MIT + file LICENSE
Depends R (>= 4.3.0)
Imports celda, dbscan, DelayedArray, ggplot2, Matrix (>= 1.5.3), MCMCprecision, methods, patchwork, plyr, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), reshape2, rstan (>= 2.18.1), rstantools (>= 2.2.0), S4Vectors, scater, Seurat, SingleCellExperiment, SummarizedExperiment, withr
System Requirements GNU make
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Suggests BiocStyle, dplyr, knitr, rmarkdown, scran, SingleCellMultiModal, TENxPBMCData, testthat (>= 3.0.0)
Linking To BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>=, RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
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Source Package decontX_1.2.0.tar.gz
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macOS Binary (x86_64) decontX_1.2.0.tgz
macOS Binary (arm64) decontX_1.2.0.tgz
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