TCRMatch

TCRMatch predicts T-cell receptor (TCR) epitope specificity by comparing TCR sequences to characterized receptors in the Immune Epitope Database (IEDB) to infer targeted epitopes.

Key Features:

• Sequence similarity metrics: Employs six different metrics to evaluate sequence similarity between TCRs for prediction of shared epitope specificity.
• k-mer matching: Implements a comprehensive k-mer matching approach identified as the most effective metric for predicting epitope specificity.
• Input and database matching: Accepts TCR β-chain CDR3 sequences as input and identifies matches to epitope-specific TCRs curated in the Immune Epitope Database (IEDB).
• High-throughput sequencing compatibility: Leverages TCR sequences derived from high-throughput repertoire sequencing and single-cell sequencing datasets.

Scientific Applications:

• Repertoire analysis: Infers epitope targets from bulk TCR repertoire sequencing to characterize antigen-specific responses.
• Single-cell TCR annotation: Assigns putative epitope specificities to TCRs recovered from single-cell sequencing experiments.
• Disease and immunotherapy research: Supports identification of TCR-epitope pairs relevant to infectious diseases, allergies, autoimmune disorders, and cancer.
• Epitope mapping: Aids identification of epitopes recognized by receptors to inform targeted immunotherapy development and immune monitoring.

Methodology:

Performs detailed sequence-similarity comparisons using six metrics, including a k-mer matching approach, to identify matches to epitope-specific TCRs curated in the Immune Epitope Database (IEDB).