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tcr-repertoire-analysis-agent

Maintainer FreedomIntelligence · Last updated April 1, 2026

TCR repertoire analysis: V(D)J usage, clonotype dynamics, antigen specificity.

OpenClawNanoClawAnalysisReproductiontcr-repertoire-analysis-agent🧠 bioos extended suiteimmunology & cell therapytcr

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tcr-repertoire-analysis-agent

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • The TCR Repertoire Analysis Agent provides comprehensive T-cell receptor repertoire analysis for cancer immunology applications. It leverages deep learning and multi-layer machine learning approaches to analyze TCR diversity, predict immunotherapy response, identify tumor-reactive TCRs, and support therapeutic TCR selection for cancer immunotherapy.
  • When analyzing TCR repertoire for cancer diagnosis and staging.
  • For predicting immunotherapy (anti-PD-1/PD-L1) response from TCR profiles.
  • To identify tumor-reactive TCRs for adoptive cell therapy.
  • When monitoring treatment response through TCR clonality changes.

Source Doc

Excerpt From SKILL.md

Core Capabilities

  1. Repertoire Diversity Analysis: Quantify TCR diversity, clonality, and convergence.

  2. Cancer Diagnosis: Distinguish cancer types from TCR signatures.

  3. Immunotherapy Response Prediction: Predict checkpoint inhibitor response.

  4. Tumor-Reactive TCR Identification: Find neoantigen-specific TCRs.

  5. TCR-pMHC Binding Prediction: Predict TCR epitope specificity.

  6. Clonal Dynamics Tracking: Monitor TCR clones during treatment.

TCR Repertoire Metrics

MetricDefinitionClinical Significance
ClonalityGini coefficient of clone sizesImmune focusing
Shannon EntropyDiversity measureImmune breadth
RichnessUnique clonotypesRepertoire depth
Top Clone %Largest clone fractionDominant response
Convergent TCRsShared across patientsPublic epitope response
Tumor-Infiltrating %TIL-derived TCRsTumor reactivity

Workflow

  1. Input: TCR-seq data (bulk or single-cell), clinical metadata.

  2. Preprocessing: CDR3 extraction, error correction, clustering.

  3. Repertoire Analysis: Calculate diversity, clonality, convergence.

  4. ML Classification: Cancer type, stage, response prediction.

  5. TCR Prioritization: Rank tumor-reactive TCR candidates.

  6. TCR-pMHC Prediction: Predict epitope specificity.

  7. Output: Repertoire metrics, predictions, therapeutic candidates.

Use cases

  • Use tcr-repertoire-analysis-agent for clinical, translational, or medical research tasks.
  • Apply tcr-repertoire-analysis-agent when healthcare-specific guidance is required.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

  • TCR_pMHC_Prediction_Agent - Detailed TCR-epitope prediction
  • Neoantigen_Prediction_Agent - Neoantigen identification
  • TME_Immune_Profiling_Agent - Broader immune context
  • TCell_Exhaustion_Analysis_Agent - T cell phenotyping

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