sctransform: Variance Stabilizing Transformations for Single Cell UMI Data

A normalization method for single-cell UMI count data using a variance stabilizing transformation. The transformation is based on a negative binomial regression model with regularized parameters. As part of the same regression framework, this package also provides functions for batch correction, and data correction. See Hafemeister and Satija (2019) <doi:10.1186/s13059-019-1874-1>, and Choudhary and Satija (2022) <doi:10.1186/s13059-021-02584-9> for more details.

Version: 0.4.1
Depends: R (≥ 3.6.0)
Imports: dplyr, magrittr, MASS, Matrix (≥ 1.5-0), methods, future.apply, future, ggplot2, reshape2, rlang, gridExtra, matrixStats
LinkingTo: RcppArmadillo, Rcpp (≥ 0.11.0)
Suggests: irlba, testthat, knitr
Enhances: glmGamPoi
Published: 2023-10-19
DOI: 10.32614/CRAN.package.sctransform
Author: Christoph Hafemeister ORCID iD [aut], Saket Choudhary ORCID iD [aut, cre], Rahul Satija ORCID iD [ctb]
Maintainer: Saket Choudhary <schoudhary at>
License: GPL-3 | file LICENSE
NeedsCompilation: yes
SystemRequirements: C++17
Citation: sctransform citation info
Materials: README NEWS
CRAN checks: sctransform results


Reference manual: sctransform.pdf


Package source: sctransform_0.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sctransform_0.4.1.tgz, r-oldrel (arm64): sctransform_0.4.1.tgz, r-release (x86_64): sctransform_0.4.1.tgz, r-oldrel (x86_64): sctransform_0.4.1.tgz
Old sources: sctransform archive

Reverse dependencies:

Reverse imports: muscat, Seurat
Reverse suggests: CAMML, EWCE, RESET, SCdeconR, VAM


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