ASURAT

ASURAT is a computational tool to address the challenges in analyzing single-cell RNA sequencing (scRNA-seq) data, where conventional gene-based analyses often require extensive manual curation to interpret computational results. ASURAT offers a solution by simultaneously performing unsupervised clustering and functional annotation of individual cells based on disease, cell type, biological process, and signaling pathway activity. The tool utilizes a correlation graph decomposition for genes in database-derived functional terms.

Topic

Transcriptomics;Molecular interactions, pathways and networks;RNA-Seq;Pathology;Oncology

Detail

  • Operation: Gene-set enrichment analysis;Clustering;Essential dynamics

  • Software interface: Workflow, Library

  • Language: R

  • License: The GNU General Public License v3.0

  • Cost: Free

  • Version name: 1.6.0

  • Credit: The JSPS KAKENHI, the Honjo International Scholarship Foundation, the Shin Bunya Kaitaku Shien Program of Institute for Protein Research, Osaka University, JST-Mirai program, JST CREST program, the P-CREATE, Japan Agency for Medical Research and Development, the JST Moonshot R&D.

  • Input: -

  • Output: -

  • Contact: Keita Iida kiida@protein.osaka-u.ac.jp

  • Collection: -

  • Maturity: Stable

Publications

  • ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomes.
  • Iida K, et al. ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomes. ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomes. 2022; 38:4330-4336. doi: 10.1093/bioinformatics/btac541
  • https://doi.org/10.1093/BIOINFORMATICS/BTAC541
  • PMID: 35924984
  • PMC: PMC9477531

Download and documentation

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