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.
|Author||Mahmoud M Ibrahim|
|Maintainer||Mahmoud M Ibrahim <[email protected]>|
|License||GPL-3 + file LICENSE|
|Package repository||View on GitHub|
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