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K-means clustering for large single-cell datasets

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mbkmeans: Mini-batch k-means clustering for single-cell RNA-seq

Project Status: Active - The project has reached a stable, usable state and is being actively developed. BioC release BioC devel R-CMD-check

This package implements the mini-batch k-means algorithm for large datasets, including support for on-disk data representation.

The method is described in details in the paper:

S. Hicks, R. Liu, Y. Ni, E. Purdom, D. Risso (2021). mbkmeans: Fast clustering for single cell data using mini-batch k-means. PLOS Computational Biology.

Installation

In virtually all cases, installing from Bioconductor is recommended.

if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("mbkmeans")

In the rare event you need the development version from GitHub, use the following.

library(devtools)
BiocManager::install("drisso/mbkmeans")

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