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DCATS

Differential Composition Analysis Transformed by a Similarity matrix

Bioconductor version: 3.23 · Package version: 1.10.0

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.

Installation

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

BiocManager::install("DCATS")

Details

MaintainerXinyi Lin <linxy29@connect.hku.hk>
AuthorXinyi Lin [aut, cre] (ORCID: <https://orcid.org/0000-0002-7780-2461>), Chuen Chau [aut], Yuanhua Huang [aut], Joshua W.K. Ho [aut]
LicenseMIT + file LICENSE
Downloads rank192
Source branchRELEASE_3_23
biocViewsNormalization, SingleCell, Software

Documentation

Download

Dependencies

Depends: R (>= 4.1.0), stats

Imports: MCMCpack, matrixStats, robustbase, aod, e1071

Suggests: testthat (>= 3.0.0), knitr, Seurat, SeuratObject, tidyverse, rmarkdown, BiocStyle