Improved dropClust R package with integrative analysis support for scRNA-seq data

Authors

Debajyoti Sinha, Indian Statistical Institute, Kolkata
Pradyumn Sinha, Delhi Technological University
Ritwik Saha, Delhi Technological University
Sanghamitra Bandyopadhyay, Indian Statistical Institute, Kolkata
Debarka Sengupta, Indraprastha Institute of Information Technology, Delhi

Article Type

Research Article

Publication Title

Bioinformatics

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/.

First Page

1946

Last Page

1947

DOI

10.1093/bioinformatics/btz823

Publication Date

1-1-2020

Recommended Citation

Sinha, Debajyoti; Sinha, Pradyumn; Saha, Ritwik; Bandyopadhyay, Sanghamitra; and Sengupta, Debarka, "Improved dropClust R package with integrative analysis support for scRNA-seq data" (2020). Journal Articles. 477.
https://digitalcommons.isical.ac.in/journal-articles/477