DeRR
DeRR detects dual T cell receptors (TCRs) in single-cell TCR sequencing (scTCR-Seq) and single-cell RNA sequencing (scRNA-Seq) data to enable systematic characterization of dual-TCR T cell populations.
Key Features:
- Dual-TCR detection in scTCR-Seq: Identifies T cells expressing two distinct TCR α-chains or β-chains from single-cell TCR sequencing data.
- Dual-TCR detection in scRNA-Seq: Detects dual-TCR expression from single-cell RNA sequencing data.
- Large-scale analysis capability: Evaluated on over 600,000 single T cells from 147 samples.
- Cross-reactivity assessment: Enables evaluation of T cell cross-reactivity patterns mediated by secondary TCR chains in dual-TCR T cells.
- Dynamic expression analysis: Quantifies relative expression levels of the two TCRs within individual dual-TCR T cells.
Scientific Applications:
- Cancer immunology: Revealed elevated dual-TCR frequency in cancer compared to other conditions.
- Autoimmune disease research: Demonstrated positive association between dual-TCR frequency and disease duration in autoimmune disorders.
- T cell subtype characterization: Showed uniform distribution of dual-TCR T cells across all T cell subtypes.
- T cell receptor repertoire analysis: Provides first systematic landscape of dual-TCR T cells at single-cell resolution.
Methodology:
DeRR employs a computational pipeline for detection of TCRs in single-cell sequencing data, with specific algorithms to identify dual-TCR α-chains and dual-TCR β-chains in both scTCR-seq and scRNA-seq data.
Topics
Details
- Maturity:
- Mature
- Cost:
- Free of charge (with restrictions)
- Tool Type:
- command-line tool
- Programming Languages:
- Python
- Added:
- 6/12/2026
- Last Updated:
- 6/12/2026
Operations
Data Inputs & Outputs
Aggregation
Inputs
Data filtering
Inputs
Outputs
Publications
PMID: 41051256
Documentation
Quick start guide
https://github.com/GuoBioinfoLab/DeRR/blob/main/README.mdDownloads
- Source codehttps://github.com/GuoBioinfoLab/DeRR
Links
Repository
https://github.com/GuoBioinfoLab/DeRR