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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.
Getting started
README.md
Benchmarking SignacFast with single cell flow-sorted data
Benchmarking SignacX and SingleR with synovial flow cytometry data
Cell type classification with SignacX: CITE-seq PBMCs from 10X Genomics
Cell type classification with SignacX: PBMCs from 10X Genomics
Mapping homologous gene symbols
Signac and SPRING: Learning CD56 NK cells from multi-modal analysis of CITE-seq PBMCs from 10X Genomics
SignacX, Seurat and MASC: Analysis of kidney cells from AMP
Browse package contents
Package details |
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| 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@gmail.com> |
| License | GPL-3 |
| Version | 2.2.5 |
| URL | https://github.com/mathewchamberlain/SignacX |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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