# mbkmeans: Mini-batch k-means clustering for single-cell RNA-seq
[](http://www.repostatus.org/#active)
[](https://bioconductor.org/checkResults/release/bioc-LATEST/mbkmeans)
[](https://bioconductor.org/checkResults/devel/bioc-LATEST/mbkmeans)
[](https://github.com/drisso/mbkmeans/actions)
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.](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008625)
## Installation
In virtually all cases, installing from Bioconductor is recommended.
```{r}
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.
```{r}
library(devtools)
BiocManager::install("drisso/mbkmeans")
```