lamindb
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps p
npx skills add LeonChaoX/qinyan-academic-skills --skill lamindb --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.
# LaminDB ## Overview LaminDB is an open-source data framework for biology designed to make data queryable, traceable, reproducible, and FAIR (Findable, Accessible, Interoperable, Reusable). It provides a unified platform that combines lakehouse architecture, lineage tracking, feature stores, biological ontologies, LIMS (Laboratory Information Management System), and ELN (Electronic Lab Notebook) capabilities through a single Python API. **Core Value Proposition:** - **Queryability**: Search and filter datasets by metadata, features, and ontology terms - **Traceability**: Automatic lineage tracking from raw data through analysis to results - **Reproducibility**: Version control for data, code, and environment - **FAIR Compliance**: Standardized annotations using biological ontologies ## When to Use This Skill Use this skill when: - **Managing biological datasets**: scRNA-seq, bulk RNA-seq, spatial transcriptomics, flow cytometry, multi-modal data, EHR data - **Tracking computational workflows**: Notebooks, scripts, pipeline execution (Nextflow, Snakemake, Redun) - **Curating and validating data**: Schema validation, standardization, ontology-based annotation - **Working with biolog
- Overview
- When to Use This Skill
- Core Capabilities
- 1. Core Concepts and Data Lineage
- 2. Data Management and Querying
- 3. Annotation and Validation
- 4. Biological Ontologies
- 5. Integrations
- 6. Setup and Deployment
- Common Use Case Workflows
- Use Case 1: Single-Cell RNA-seq Analysis with Ontology Validation
- Use Case 2: Building a Queryable Data Lakehouse
- Use Case 3: ML Pipeline with W&B Integration
- Use Case 4: Nextflow Pipeline Integration
What does the lamindb skill do?
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps p
How do I install it?
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill lamindb --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 LeonChaoX/qinyan-academic-skills, a repository with 759 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.