TCRex

TCRex predicts recognition of pathogenic and cancer epitopes by human T cell receptors (TCRs) from high-throughput TCR sequencing data to characterize individual TCR repertoires and assess antigen-specific immune states.

Key Features:

• Supported data: Accepts high-throughput TCR sequencing data including Immunoseq and MiXCR outputs and focuses on TCR beta chain sequences.
• Machine learning-based annotation: Employs a machine learning algorithm trained on known epitope-specific patterns to identify sequence motifs associated with recognition of specific epitopes and annotate full TCR repertoires by linking sequenced TCRs to their antigenic targets.
• Statistical analysis integration: Combines machine learning results with statistical analyses to evaluate the prevalence of epitope-reactive TCR sequences within repertoire datasets.
• Cross-dataset epitope identification: Identifies epitopes targeted by an individual's TCR repertoire across different datasets to enable comparative repertoire analyses.

Scientific Applications:

• Vaccine monitoring: Detection and tracking of epitope-specific TCRs to evaluate vaccine-induced immune responses.
• Infectious disease diagnostics: Identification of pathogen-epitope-reactive TCR sequences for diagnostic and surveillance purposes.
• Cancer epitope profiling: Analysis of TCR recognition of cancer epitopes to study tumor-associated immune responses.

Methodology:

Integration of machine learning trained on known epitope-specific patterns with statistical analyses to annotate TCR repertoires and evaluate prevalence of epitope-reactive TCR sequences.