Ragas: integration and enhanced visualization for single cell subcluster analysis.
Bioinformatics
; 40(6)2024 Jun 03.
Article
en En
| MEDLINE
| ID: mdl-38867706
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.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Programas Informáticos
/
Análisis de la Célula Individual
Límite:
Humans
Idioma:
En
Año:
2024
Tipo del documento:
Article