markerpen: Marker Gene Detection via Penalized Principal Component Analysis

Implementation of the 'MarkerPen' algorithm, short for marker gene detection via penalized principal component analysis, described in the paper by Qiu, Wang, Lei, and Roeder (2020, <doi:10.1101/2020.11.07.373043>). 'MarkerPen' is a semi-supervised algorithm for detecting marker genes by combining prior marker information with bulk transcriptome data.

Version: 0.1.1
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.1), RSpectra, stats
LinkingTo: Rcpp, RcppEigen, RSpectra
Suggests: knitr, rmarkdown, prettydoc, scales
Published: 2021-03-17
Author: Yixuan Qiu, Jiebiao Wang, Jing Lei, and Kathryn Roeder
Maintainer: Yixuan Qiu <yixuan.qiu at cos.name>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README NEWS
CRAN checks: markerpen results

Documentation:

Reference manual: markerpen.pdf
Vignettes: MarkerPen: Marker Gene Detection via Penalized Principal Component Analysis

Downloads:

Package source: markerpen_0.1.1.tar.gz
Windows binaries: r-devel: markerpen_0.1.1.zip, r-devel-UCRT: markerpen_0.1.1.zip, r-release: markerpen_0.1.1.zip, r-oldrel: markerpen_0.1.1.zip
macOS binaries: r-release (arm64): markerpen_0.1.1.tgz, r-release (x86_64): markerpen_0.1.1.tgz, r-oldrel: markerpen_0.1.1.tgz
Old sources: markerpen archive

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