HIPPO: Heterogeneity-Induced Pre-Processing tOol

For scRNA-seq data, it selects features and clusters the cells simultaneously for single-cell UMI data. It has a novel feature selection method using the zero inflation instead of gene variance, and computationally faster than other existing methods since it only relies on PCA+Kmeans rather than graph-clustering or consensus clustering.

Package details

AuthorTae Kim [aut, cre], Mengjie Chen [aut]
Bioconductor views Clustering DifferentialExpression GeneExpression Sequencing SingleCell
MaintainerTae Kim <tk382@uchicago.edu>
LicenseGPL (>=2)
URL https://github.com/tk382/HIPPO
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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HIPPO documentation built on Nov. 8, 2020, 5:05 p.m.