scBatchQC
Batch-Aware Cell Quality Control for Single-Cell RNA-seq
Bioconductor version: 3.24 · Package version: 0.99.3
scBatchQC provides a hierarchical empirical Bayes framework for quality control in multi-sample, multi-batch single-cell RNA-seq experiments. Unlike per-sample QC tools, scBatchQC jointly models QC metric distributions (library size, gene count, mitochondrial fraction) and doublet rates across batches, enabling calibrated cell-level QC calls that account for batch structure. The package operates natively on SingleCellExperiment objects and returns augmented colData with per-cell QC flags and batch-adjusted doublet scores.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scBatchQC") Details
| Maintainer | Subhadip Jana <subhadipjana1409@gmail.com> |
| Author | Subhadip Jana [aut, cre] (ORCID: <https://orcid.org/0009-0003-7860-2853>) |
| License | MIT + file LICENSE |
| URL | https://github.com/SubhadipJana1409/scBatchQC |
| Bug Reports | https://github.com/SubhadipJana1409/scBatchQC/issues |
| Downloads rank | 45 |
| Source branch | devel |
| biocViews | BatchEffect, CellBasedAssays, GeneExpression, QualityControl, Sequencing, SingleCell, Software, StatisticalMethod, Transcriptomics, WorkflowStep |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | scBatchQC_0.99.3.tar.gz |
| Windows binary (x86_64) | scBatchQC_0.99.3.zip |
| macOS binary (arm64) | scBatchQC_0.99.3.tgz |
| macOS binary (x86_64) | scBatchQC_0.99.3.tgz |
Dependencies
Depends: R (>= 4.5.0)
Imports: SingleCellExperiment, SummarizedExperiment, BiocParallel, scrapper, methods, stats, S4Vectors, ggplot2, rlang
Suggests: scDblFinder, BiocStyle, knitr, rmarkdown, testthat (>= 3.0.0), TENxPBMCData, withr