GIANA
GIANA performs rapid alignment and clustering of up to 10^7 T-cell receptor (TCR) hypervariable CDR3 amino acid sequences by encoding sequences with a geometric isometry framework for large-scale immune repertoire analysis.
Key Features:
- Computational Efficiency: Achieves sequence alignment and clustering at speeds reported to be approximately 600 times faster than methods such as TCRdist while maintaining specificity.
- Isometric Encoding: Encodes amino acid sequences using a geometric isometry-based mathematical representation to preserve sequence similarity relationships.
- Rapid Query Capability: Enables rapid querying of extensive reference cohorts within minutes for large-scale comparative analyses.
Scientific Applications:
- Identification of Shared Antigen Specificity: Clusters TCR sequences to identify shared antigen specificities among receptors.
- Disease-Specific Receptor Discovery: Facilitates identification of candidate disease-specific TCRs from large-scale repertoire datasets.
- Multi-Disease Diagnostic Comparison: Allows comparison of unseen TCR-seq samples against reference cohorts to differentiate samples across cohorts associated with cancer, infectious diseases, and autoimmune conditions.
Methodology:
GIANA transforms amino acid CDR3 sequences into an isometric geometric encoding and performs sequence alignment and high-speed clustering based on that geometric representation.
Topics
Details
- License:
- Other
- Cost:
- Free of charge (with restrictions)
- Tool Type:
- command-line tool, workflow
- Operating Systems:
- Mac, Linux
- Programming Languages:
- Python, R
- Added:
- 1/13/2022
- Last Updated:
- 1/13/2022
Operations
Publications
Zhang H, Zhan X, Li B. GIANA allows computationally-efficient TCR clustering and multi-disease repertoire classification by isometric transformation. Nature Communications. 2021;12(1). doi:10.1038/s41467-021-25006-7. PMID:34349111. PMCID:PMC8339063.
PMID: 34349111
PMCID: PMC8339063
Funding: - U.S. Department of Health & Human Services | NIH | National Cancer Institute: 1R01CA245318
- Cancer Prevention and Research Institute of Texas: RP190107, RR170079
- U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences: 5R01GM126479