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decontX

Decontamination of single cell genomics data

Bioconductor version: 3.24 · Package version: 1.11.1

This package contains implementation of DecontX (Yang et al. 2020), a decontamination algorithm for single-cell RNA-seq, and DecontPro (Yin et al. 2024), 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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("decontX")

Details

MaintainerJoshua Campbell <camp@bu.edu>
AuthorYuan Yin [aut] (ORCID: <https://orcid.org/0000-0001-9261-6061>), Masanao Yajima [aut] (ORCID: <https://orcid.org/0000-0002-7583-3707>), Joshua Campbell [aut, cre] (ORCID: <https://orcid.org/0000-0003-0780-8662>)
LicenseMIT + file LICENSE
URLhttps://github.com/campbio/decontX
Bug Reportshttps://github.com/campbio/decontX/issues
System RequirementsGNU make
Downloads rank857
Source branchdevel
biocViewsBayesian, GeneExpression, Normalization, Preprocessing, Proteomics, QualityControl, RNASeq, SingleCell, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagedecontX_1.11.1.tar.gz
Windows binary (x86_64)decontX_1.11.1.zip
macOS binary (arm64)decontX_1.11.1.tgz
macOS binary (x86_64)decontX_1.11.1.tgz
Dependencies

Depends: R (>= 4.3.0)

Imports: dbscan, DelayedArray, ggplot2 (>= 3.5.0), 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, scrapper (>= 1.2.0), SeuratObject, SingleCellExperiment, SummarizedExperiment, withr

LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)

Suggests: BiocStyle, covr, dplyr, knitr, rmarkdown, scater, Seurat, scran, SingleCellMultiModal, TENxPBMCData, testthat (>= 3.0.0)

Reverse dependencies

Suggests Me (1): celda