SignacX: Cell Type Identification and Discovery from Single Cell Gene Expression Data

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
DOI:	10.32614/CRAN.package.SignacX
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
In views:	Omics
CRAN checks:	SignacX results

Documentation:

Reference manual:	SignacX.html , SignacX.pdf
Vignettes:	Mapping homologous gene symbols (source) Benchmarking SignacX and SingleR with flow-sorted data (source) Analysis of Kidney lupus data from AMP (source) Analysis of CITE-seq PBMCs from 10X Genomics (source) Analysis of PBMCs from 10X Genomics (source) Mapping cells from CITE-seq PBMCs from 10X Genomics to another data set (source) Benchmarking SignacFast with flow-sorted data (source)

Downloads:

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

Linking:

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