lamindb

Featured

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 platforms (W&B, MLflow), and deployment strategies.

AI & Automation 723 stars 62 forks Updated 1 weeks ago MIT

Install

View on GitHub

Quality Score: 92/100

Stars 20%
95
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# 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 biological ontologies**: Genes, proteins, cell types, tissues, diseases, pathways (via Bionty) - **Building data lakehouses**: Unified query interface across multiple datasets - **Ensuring reproducibility**: Automatic versioning, lineage tracking, environment capture - **Integrating ML pipelines**: ...

Details

Author
LeonChaoX
Repository
LeonChaoX/qinyan-academic-skills
Created
5 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

Similar Skills

Semantically similar based on skill content — not just same category