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) for more details.


Reference manual

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2.2.5 by Mathew Chamberlain, 20 days ago


Report a bug at https://github.com/mathewchamberlain/SignacX/issues

Browse source code at https://github.com/cran/SignacX

Authors: Mathew Chamberlain [aut, cre] , Virginia Savova [aut] , Richa Hanamsagar [aut] , Frank Nestle [aut] , Emanuele de Rinaldis [aut] , Sanofi US [fnd]

Documentation:   PDF Manual  

GPL-3 license

Imports neuralnet, lme4, methods, Matrix, pbmcapply, Seurat, RJSONIO, igraph, jsonlite, RColorBrewer, stats

Suggests hdf5r, rhdf5, knitr, rmarkdown, formatR

See at CRAN