lamindb

Manage biological data artifacts with versioning and lineage tracking.

94|11|Updated Mar 26, 2026
One-click install
npx skills add https://github.com/swaruplab/operon --skill lamindb-swaruplab
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: lamindb
Source: https://github.com/swaruplab/operon/tree/main/src-tauri/protocols/lamindb
Command: npx skills add https://github.com/swaruplab/operon --skill lamindb-swaruplab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

LaminDB provides an integrated platform to manage biological data artifacts, track data provenance, and enforce reproducible workflows across local and cloud environments.

Core Features & Use Cases

  • Artifact management with versioning and keys, enabling provenance and auditability.
  • Ontology management and annotation through Bionty, enabling standardized metadata across studies.
  • End-to-end workflow integration with popular tools (Nextflow, Snakemake) and ML platforms, plus seamless storage and retrieval.

Quick Start

Track an analysis by creating an artifact, linking its transform, and querying by features for reproducible results.

Frequently Asked Questions about lamindb

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

FAQPage Schema
How do I track data provenance and lineage for single-cell biology workflows?

Manage biological data with lineage by creating versioned artifacts and linking them to their transforms and runs. This tracks data provenance end-to-end, making analysis reproducible and queryable by features.

How does ontology-backed metadata standardize biological data management?

Ontology-backed metadata standardizes biological data management by using Bionty to annotate artifacts with controlled vocabularies. This enforces consistent metadata across studies, enabling accurate querying and cross-project collaboration.

Can I integrate data lineage tracking with Nextflow and Snakemake pipelines?

Yes, you can integrate data lineage tracking with Nextflow and Snakemake pipelines. The platform provides workflow integrations that automatically capture transform records and artifact versions during pipeline execution.

Does LaminDB support deployment across local and cloud infrastructures?

Yes, LaminDB supports flexible deployment across local and cloud infrastructures. This data lakehouse-style organization facilitates seamless storage, retrieval, and cross-project collaboration without infrastructure lock-in.

What is the best way to organize a data lakehouse for spatial transcriptomics data?

Organize a spatial data lakehouse by using artifact versioning with keys and ontology-backed metadata records. This approach structures spatial transcriptomics workflows while maintaining auditability and standardized annotation.

Why use artifact versioning instead of standard file storage for bioinformatics reproducibility?

Use artifact versioning over standard file storage to maintain strict auditability and data provenance. By linking features and transforms to versioned artifacts, you enforce reproducible biological workflows that standard file storage cannot track.