An implementation of neural networks trained with flow-sorted gene expression data to classify cellular phenotypes in single cell RNA-sequencing data. See Chamberlain M et al. (2021) <doi:10.1101/2021.02.01.429207> for more details.
Version: | 2.2.5 |
Depends: | R (≥ 3.5.0) |
Imports: | neuralnet, lme4, methods, Matrix, pbmcapply, Seurat (≥ 3.2.0), RJSONIO, igraph (≥ 1.2.1), jsonlite (≥ 1.5), RColorBrewer (≥ 1.1.2), stats |
Suggests: | hdf5r, rhdf5, knitr, rmarkdown, formatR |
Published: | 2021-11-18 |
Author: | Mathew Chamberlain [aut, cre], Virginia Savova [aut], Richa Hanamsagar [aut], Frank Nestle [aut], Emanuele de Rinaldis [aut], Sanofi US [fnd] |
Maintainer: | Mathew Chamberlain <chamberlainphd at gmail.com> |
BugReports: | https://github.com/mathewchamberlain/SignacX/issues |
License: | GPL-3 |
URL: | https://github.com/mathewchamberlain/SignacX |
NeedsCompilation: | no |
Citation: | SignacX citation info |
Materials: | README NEWS |
CRAN checks: | SignacX results |
Package source: | SignacX_2.2.5.tar.gz |
Windows binaries: | r-devel: SignacX_2.2.5.zip, r-release: SignacX_2.2.5.zip, r-oldrel: SignacX_2.2.5.zip |
macOS binaries: | r-release (arm64): SignacX_2.2.5.tgz, r-oldrel (arm64): SignacX_2.2.5.tgz, r-release (x86_64): SignacX_2.2.5.tgz, r-oldrel (x86_64): SignacX_2.2.5.tgz |
Old sources: | SignacX archive |
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