Abstract
DropClust leverages Locality Sensitive Hashing (LSH) to speed up clustering of large scale single cell expression data. Here we present the improved dropClust, a complete R package that is, fast, interoperable and minimally resource intensive. The new dropClust features a novel batch effect removal algorithm that allows integrative analysis of single cell RNA-seq (scRNA-seq) datasets. Availability and implementation: dropClust is freely available at https://github.com/debsin/dropClust as an R package. A lightweight online version of the dropClust is available at https://debsinha.shinyapps.io/dropClust/.
Cite
CITATION STYLE
Sinha, D., Sinha, P., Saha, R., Bandyopadhyay, S., & Sengupta, D. (2020). Improved dropClust R package with integrative analysis support for scRNA-seq data. Bioinformatics, 36(6), 1946–1947. https://doi.org/10.1093/bioinformatics/btz823
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