CRAN/E | SignacX

SignacX

Cell Type Identification and Discovery from Single Cell Gene Expression Data

Installation

About

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.

Citation SignacX citation info
github.com/mathewchamberlain/SignacX
Bug report File report

Key Metrics

Version 2.2.5
R ≥ 3.5.0
Published 2021-11-18 496 days ago
Needs compilation? no
License GPL-3
CRAN checks SignacX results

Downloads

Last 24 hours 0 -100%
Last 7 days 54 -48%
Last 30 days 244 +4%
Last 90 days 685 -13%
Last 365 days 3.450 -35%

Maintainer

Maintainer

Mathew Chamberlain

chamberlainphd@gmail.com

Authors

Mathew Chamberlain

aut / cre

Virginia Savova

aut

Richa Hanamsagar

aut

Frank Nestle

aut

Emanuele de Rinaldis

aut

Sanofi US

fnd

Material

README
NEWS
Reference manual
Package source

Vignettes

Mapping homologous gene symbols
Benchmarking SignacX and SingleR with flow-sorted data
Analysis of Kidney lupus data from AMP
Analysis of CITE-seq PBMCs from 10X Genomics
Analysis of PBMCs from 10X Genomics
Mapping cells from CITE-seq PBMCs from 10X Genomics to another data set
Benchmarking SignacFast with flow-sorted data

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

SignacX archive

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