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 (2021) <doi:10.1101/2021.07.07.451498>
for more details.
Version: |
0.3.3 |
Depends: |
R (≥ 3.5.0) |
Imports: |
dplyr, magrittr, MASS, Matrix, methods, future.apply, future, ggplot2, reshape2, rlang, gridExtra, matrixStats |
LinkingTo: |
RcppArmadillo, Rcpp (≥ 0.11.0) |
Suggests: |
irlba, testthat, knitr |
Enhances: |
glmGamPoi |
Published: |
2022-01-13 |
Author: |
Christoph Hafemeister
[aut],
Saket Choudhary
[aut, cre],
Rahul Satija
[ctb] |
Maintainer: |
Saket Choudhary <schoudhary at nygenome.org> |
BugReports: |
https://github.com/satijalab/sctransform/issues |
License: |
GPL-3 | file LICENSE |
URL: |
https://github.com/satijalab/sctransform |
NeedsCompilation: |
yes |
SystemRequirements: |
C++11 |
Citation: |
sctransform citation info |
Materials: |
README NEWS |
CRAN checks: |
sctransform results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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