mahmoudibrahim/genesorteR: Feature Ranking in Clustered Single Cell Data

The main purpose of this R extension is to select features in (possibly very large) single cell data including scRNA-Seq and potentially 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.

Getting started

Package details

AuthorMahmoud M Ibrahim
MaintainerMahmoud M Ibrahim <[email protected]>
LicenseGPL-3 + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
mahmoudibrahim/genesorteR documentation built on Aug. 12, 2019, 2:15 p.m.