Ragas: integration and enhanced visualization for single cell subcluster analysis.

TitleRagas: integration and enhanced visualization for single cell subcluster analysis.
Publication TypeJournal Article
Year of Publication2024
AuthorsBalaji U, Rodriguez-Alcazar J, Balasubramanian P, Smitherman C, Baisch J, Pascual V, Gu J
JournalBioinformatics
Volume40
Issue6
Date Published2024 Jun 03
ISSN1367-4811
KeywordsAlgorithms, Cluster Analysis, Humans, RNA-Seq, Sequence Analysis, RNA, Single-Cell Analysis, Software
Abstract

SUMMARY: Subcluster analysis is a powerful means to improve clustering and characterization of single cell RNA-Seq data. However, there are no existing tools to systematically integrate results from multiple subclusters, which creates hurdles for accurate data quantification, visualization, and interpretation in downstream analysis. To address this issue, we developed Ragas, an R package that integrates multi-level subclustering objects for streamlined analysis and visualization. A new data structure was implemented to seamlessly connect and assemble miscellaneous single cell analyses from different levels of subclustering, along with several new or enhanced visualization functions. Moreover, a re-projection algorithm was developed to integrate nearest-neighbor graphs from multiple subclusters in order to maximize their separability on the combined cell embeddings, which significantly improved the presentation of rare and homogeneous subpopulations.

AVAILABILITY AND IMPLEMENTATION: The Ragas package and its documentation can be accessed through https://github.com/jig4003/Ragas and its source code is also available at https://zenodo.org/records/11244921.

DOI10.1093/bioinformatics/btae366
Custom 1

https://www.ncbi.nlm.nih.gov/pubmed/38867706?dopt=Abstract

Alternate JournalBioinformatics
PubMed ID38867706
Grant ListU19AI082715 / / Autoimmunity Centers of Excellence /
P50AR070594 / / Center for Lupus Research /

Weill Cornell Medicine Gale and Ira Drukier Institute for Children's Health 413 E. 69th Street New York, NY 10021