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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

MaintainerSubhadip Jana <subhadipjana1409@gmail.com>
AuthorSubhadip Jana [aut, cre] (ORCID: <https://orcid.org/0009-0003-7860-2853>)
LicenseMIT + file LICENSE
URLhttps://github.com/SubhadipJana1409/scBatchQC
Bug Reportshttps://github.com/SubhadipJana1409/scBatchQC/issues
Downloads rank45
Source branchdevel
biocViewsBatchEffect, CellBasedAssays, GeneExpression, QualityControl, Sequencing, SingleCell, Software, StatisticalMethod, Transcriptomics, WorkflowStep

Documentation

Download

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

Source packagescBatchQC_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