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SCINA: A Semi-Supervised Category Identification and Assignment Tool

An automatic cell type detection and assignment algorithm for single cell RNA-Seq and Cytof/FACS data. 'SCINA' is capable of assigning cell type identities to a pool of cells profiled by scRNA-Seq or Cytof/FACS data with prior knowledge of markers, such as genes and protein symbols that are highly or lowly expressed in each category. See Zhang Z, et al (2019) <doi:10.3390/genes10070531> for more details.

Version: 1.2.0
Depends: R (≥ 2.15.0), MASS, gplots
Published: 2019-07-18
DOI: 10.32614/CRAN.package.SCINA
Author: Ze Zhang
Maintainer: Ze Zhang <Ze.Zhang at utsouthwestern.edu>
License: GPL-2
URL: http://lce.biohpc.swmed.edu/scina/ https://github.com/jcao89757/SCINA
NeedsCompilation: no
Materials: NEWS
CRAN checks: SCINA results

Documentation:

Reference manual: SCINA.pdf

Downloads:

Package source: SCINA_1.2.0.tar.gz
Windows binaries: r-devel: SCINA_1.2.0.zip, r-release: SCINA_1.2.0.zip, r-oldrel: SCINA_1.2.0.zip
macOS binaries: r-release (arm64): SCINA_1.2.0.tgz, r-oldrel (arm64): SCINA_1.2.0.tgz, r-release (x86_64): SCINA_1.2.0.tgz, r-oldrel (x86_64): SCINA_1.2.0.tgz
Old sources: SCINA archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.