alterlab-lamindb

Manage biological data assets and workflows with LaminDB.

58|9|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-lamindb
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alterlab-lamindb
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/bioinformatics/alterlab-lamindb
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-lamindb

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

LaminDB provides a unified framework to manage, query, and track biological data workflows, ensuring provenance, reproducibility, and FAIR metadata across complex analyses.

Core Features & Use Cases

  • Core concepts and data lineage: artifacts, records, runs, and transforms with automatic lineage capture.
  • Data management and querying: registry exploration, feature-based queries, streaming, and cross-registry traversal.
  • Annotation, validation, and ontologies: schema designs, ontology integration via Bionty, and standardized metadata.
  • Integrations and deployment: connect with ML platforms, workflow managers, and cloud storage; supports local to cloud deployments.
  • Use cases include scRNA-seq data management, building a queryable data lakehouse, and end-to-end data governance for reproducibility.

Quick Start

Install LaminDB, initialize your instance, and start tracking your first dataset.

Frequently Asked Questions about alterlab-lamindb

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track data lineage for scRNA-seq workflows?▼

You can track data lineage for scRNA-seq workflows by capturing artifacts, records, runs, and transforms automatically. This framework ensures provenance and reproducibility for multi-omics analyses.

What is the best way to manage biological data assets with ontology annotations?▼

Manage biological data assets with ontology annotations by integrating Bionty for standardized metadata. This approach provides schema designs and cross-registry traversal for queryable data governance.

How do I query and validate clinical datasets for reproducibility?▼

Query and validate clinical datasets using registry exploration and feature-based queries. This provides standardized metadata, automatic lineage capture, and FAIR data governance for reproducibility.

Do I need to install LaminDB locally to build a queryable data lakehouse?▼

You need to install LaminDB to build a queryable data lakehouse, but deployment supports local to cloud environments. Optional modules like bionty extend ontology integration for your specific needs.

Can I integrate workflow managers and ML platforms with biological data registries?▼

You can integrate workflow managers and ML platforms with biological data registries through cross-tool integrations. This supports streaming, cloud storage connections, and cross-registry traversal for complex analyses.