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Differential Composition Analysis Transformed by a Similarity matrix

Bioconductor version: Release (3.18)

Methods to detect the differential composition abundances between conditions in singel-cell RNA-seq experiments, with or without replicates. It aims to correct bias introduced by missclaisification and enable controlling of confounding covariates. To avoid the influence of proportion change from big cell types, DCATS can use either total cell number or specific reference group as normalization term.

Author: Xinyi Lin [aut, cre] , Chuen Chau [aut], Yuanhua Huang [aut], Joshua W.K. Ho [aut]

Maintainer: Xinyi Lin <linxy29 at connect.hku.hk>

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


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


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Differential Composition Analysis with DCATS HTML R Script
Reference Manual PDF


biocViews Normalization, SingleCell, Software
Version 1.0.0
In Bioconductor since BioC 3.18 (R-4.3) (< 6 months)
License MIT + file LICENSE
Depends R (>= 4.1.0), stats
Imports MCMCpack, matrixStats, robustbase, aod, e1071
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Suggests testthat (>= 3.0.0), knitr, Seurat, SeuratObject, tidyverse, rmarkdown, BiocStyle
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Follow Installation instructions to use this package in your R session.

Source Package DCATS_1.0.0.tar.gz
Windows Binary DCATS_1.0.0.zip
macOS Binary (x86_64) DCATS_1.0.0.tgz
macOS Binary (arm64) DCATS_1.0.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/DCATS
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/DCATS
Bioc Package Browser https://code.bioconductor.org/browse/DCATS/
Package Short Url https://bioconductor.org/packages/DCATS/
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