DESCRIPTION

Package: genesorteR
Type: Package
Title: Feature Ranking in Clustered Single Cell Data
Version: 0.4.3
Author: Mahmoud M Ibrahim
Maintainer: Mahmoud M Ibrahim <mmibrahim@pm.me>
Description: The main purpose of this R extension is to select features in (possibly very large) single cell data including scRNA-Seq and scATAC-Seq.
    The main idea is that the dropout rate of a gene is a good measure of its expression, and that empirical statistics calculated based on binarized expression matrices are sufficient to select marker genes in a way that is consistent with the expected definition of "marker gene" in experimental biology research.
    It can provide a ranking of genes specificity in each cell cluster, as well as select large or small sets of marker genes by a permutation test or using entropy-based feature selection.
    To assess cell clustering quality, some functions can also compute cell cluster quality metrics.
License: GPL-3 + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
URL: http://github.com/mahmoudibrahim/genesorteR
BugReports: http://github.com/mahmoudibrahim/genesorteR/issues
Imports:
    mclust,
    parallel,
    pheatmap,
    methods
Depends:
	R (>= 2.10),
    Matrix