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
| Maintainer | Joshua Campbell <camp@bu.edu> |
| Author | Yuan 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>) |
| License | MIT + file LICENSE |
| URL | https://github.com/campbio/decontX |
| Bug Reports | https://github.com/campbio/decontX/issues |
| System Requirements | GNU make |
| Downloads rank | 857 |
| Source branch | devel |
| biocViews | Bayesian, GeneExpression, Normalization, Preprocessing, Proteomics, QualityControl, RNASeq, SingleCell, Software |
Documentation
- Decontamination of single cell protein expression data with DecontPro
- Decontamination of ambient RNA in single-cell genomic data with DecontX
Download
Follow the installation instructions to use this package in your R session.
| Source package | decontX_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