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scCompoundDE

This is the development version of scCompoundDE; to use it, please install the devel version of Bioconductor.

Compositional and Transcriptional Decomposition of Pseudo-Bulk Differential Expression


Bioconductor version: Development (3.24)

scCompoundDE decomposes pseudo-bulk differential expression (DE) signals into two orthogonal components: transcriptional changes (cell-intrinsic expression shifts) and compositional changes (shifts in the relative abundance of cell subtypes). Standard pseudo-bulk DE tools confound these two sources of signal, producing spurious DE calls when subtype proportions differ between conditions. scCompoundDE fits per-subtype limma-voom models, estimates subtype proportion shifts, and uses a z-score-normalized decomposition to assign each gene a TC_ratio score — the fraction of its DE signal attributable to transcription versus composition. Genes are then classified as transcriptional (real biology), compositional (artifact), or mixed (requires caution). All functions operate natively on SingleCellExperiment objects and return a CDEResult S4 object that extends the standard DE output with full decomposition statistics.

Author: Subhadip Jana [aut, cre] ORCID iD ORCID: 0009-0003-7860-2853

Maintainer: Subhadip Jana <subhadipjana1409 at gmail.com>

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

Installation

To install this package, start R (version "4.6") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("scCompoundDE")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("scCompoundDE")
Decomposing pseudo-bulk DE with scCompoundDE HTML R Script
Reference Manual PDF

Details

biocViews CellBasedAssays, DifferentialExpression, GeneExpression, Sequencing, SingleCell, Software, StatisticalMethod, Transcription, Transcriptomics, WorkflowStep
Version 0.99.1
In Bioconductor since BioC 3.24 (R-4.6)
License MIT + file LICENSE
Depends R (>= 4.6.0)
Imports SingleCellExperiment, SummarizedExperiment, S4Vectors, BiocParallel, Matrix, limma, methods, stats, ggplot2, rlang, utils
System Requirements
URL https://github.com/SubhadipJana1409/scCompoundDE
Bug Reports https://github.com/SubhadipJana1409/scCompoundDE/issues
See More
Suggests BiocStyle, knitr, rmarkdown, testthat (>= 3.0.0), scuttle, withr
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package scCompoundDE_0.99.1.tar.gz
Windows Binary (x86_64)
macOS Binary (big-sur-x86_64)
macOS Binary (sonoma-arm64)
Source Repository git clone https://git.bioconductor.org/packages/scCompoundDE
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scCompoundDE
Bioc Package Browser https://code.bioconductor.org/browse/scCompoundDE/
Package Short Url https://bioconductor.org/packages/scCompoundDE/
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