This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see singleCellTK.
Bioconductor version: 3.13
Run common single cell analysis in the R console or directly through your browser. Includes many functions for import, quality control, normalization, batch correction, clustering, differential expression, and visualization..
Author: David Jenkins [aut] , Vidya Akavoor [aut], Salam Alabdullatif [aut], Shruthi Bandyadka [aut], Emma Briars [aut] , Xinyun Cao [aut], Sebastian Carrasco Pro [aut], Tyler Faits [aut], Rui Hong [aut], Mohammed Muzamil Khan [aut], Yusuke Koga [aut, cre], Anastasia Leshchyk [aut], Irzam Sarfraz [aut], Yichen Wang [aut], Zhe Wang [aut], W. Evan Johnson [aut] , Joshua David Campbell [aut]
Maintainer: Yusuke Koga <ykoga07 at bu.edu>
Citation (from within R,
enter citation("singleCellTK")
):
To install this package, start R (version "4.1") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("singleCellTK")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("singleCellTK")
HTML | R Script | 1. Introduction to singleCellTK |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
Follow Installation instructions to use this package in your R session.
Source Package | singleCellTK_2.2.0.tar.gz |
Windows Binary | singleCellTK_2.2.0.zip |
macOS 10.13 (High Sierra) | singleCellTK_2.2.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/singleCellTK |
Source Repository (Developer Access) | git clone [email protected]:packages/singleCellTK |
Package Short Url | https://bioconductor.org/packages/singleCellTK/ |
Package Downloads Report | Download Stats |
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