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.
- Version2.2.5
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- SignacX citation info
- Last release11/18/2021
Documentation
- VignetteMapping homologous gene symbols
- VignetteBenchmarking SignacX and SingleR with flow-sorted data
- VignetteAnalysis of Kidney lupus data from AMP
- VignetteAnalysis of CITE-seq PBMCs from 10X Genomics
- VignetteAnalysis of PBMCs from 10X Genomics
- VignetteMapping cells from CITE-seq PBMCs from 10X Genomics to another data set
- VignetteBenchmarking SignacFast with flow-sorted data
- MaterialREADME
- MaterialNEWS
- In ViewsOmics
Team
Mathew Chamberlain
Virginia Savova
Show author detailsRolesAuthorRicha Hanamsagar
Show author detailsRolesAuthorFrank Nestle
Show author detailsRolesAuthorEmanuele de Rinaldis
Show author detailsRolesAuthorSanofi US
Show author detailsRolesfnd
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- Imports9 packages
- Suggests4 packages