tessa
TESSA (TCR and Expression Joint Clustering) is a Bayesian model that integrates T-cell receptor (TCR) sequence profiling with transcriptomes of T cells. It maps the functional landscape of the TCR repertoire by learning unified representations across modalities. The process employs BriseisEncoder to capture TCR sequence features, creating numerical embeddings that reconstruct Atchley Factor matrices and CDR3 sequences.
npx skills add majiayu000/claude-skill-registry --skill tessa --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# TESSA Process Configuration ## Purpose TESSA (TCR and Expression Joint Clustering) is a Bayesian model that integrates T-cell receptor (TCR) sequence profiling with transcriptomes of T cells. It maps the functional landscape of the TCR repertoire by learning unified representations across modalities. The process employs BriseisEncoder to capture TCR sequence features, creating numerical embeddings that reconstruct Atchley Factor matrices and CDR3 sequences. This enables discovery of functional T-cell clusters based on combined TCR and gene expression information. ## When to Use - **Antigen-specific TCR analysis**: When analyzing T cells recognizing specific antigens (viral, tumor, etc.) - **Functional landscape mapping**: To understand the functional heterogeneity of TCR repertoire - **Multi-dataset integration**: When combining TCR and RNA data across multiple samples/batches - **Bystander vs specific T cells**: To distinguish antigen-specific T cells from bystanders in immune responses - **Required upstream**: After `ScRepCombiningExpression` with data that has both TRA and TRB chains - **NOT for**: BCR data analysis (TESSA is TCR-specific only) ## Configuration Structure ### P
- Purpose
- When to Use
- Configuration Structure
- Process Enablement
- Input Specification
- Environment Variables
- Configuration Examples
- Minimal Configuration
- Standard Cross-Sample Analysis
- Within-Sample Analysis (Multiple Patients)
- Debugging Mode
- High-Throughput Mode
- Common Patterns
- Pattern 1: Viral-Specific T Cell Analysis
What does the tessa skill do?
TESSA (TCR and Expression Joint Clustering) is a Bayesian model that integrates T-cell receptor (TCR) sequence profiling with transcriptomes of T cells. It maps the functional landscape of the TCR repertoire by learning unified representations across modalities. The process employs BriseisEncoder to capture TCR sequence features, creating numerical embeddings that reconstruct Atchley Factor matrices and CDR3 sequences.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill tessa --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.