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RamanEbrahimi
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lamindb

Manage and integrate biological datasets with lineage tracking and FAIR practices.

3|Updated Apr 17, 2026
Search Tags:#data management#reproducibility#biological data#FAIR data#biological ontologies
One-click install
npx skills add https://github.com/RamanEbrahimi/raman-marketplace --skill lamindb-ramanebrahimi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lamindb
Source: https://github.com/RamanEbrahimi/raman-marketplace/tree/main/plugins/agentic-research/skills/scientific-skills/lamindb
Command: npx skills add https://github.com/RamanEbrahimi/raman-marketplace --skill lamindb-ramanebrahimi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, anndata, bionty, nextflow, snakemake, wandb, mlflow, huggingface, tiledb, duckdb, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill simplifies the management of complex biological datasets, ensuring reproducibility, FAIR data practices, and efficient workflow tracking.

Core Features & Use Cases

  • Data Management: Handle scRNA-seq, spatial, flow cytometry, and other biological datasets.
  • Workflow Tracking: Monitor computational workflows with lineage tracking and version control.
  • Data Curation: Curate and validate datasets with biological ontologies.
  • Integrations: Connect with workflow managers like Nextflow and Snakemake, MLOps platforms like W&B, and storage systems.
  • Use Case: For a single-cell RNA-seq analysis, use this Skill to validate and annotate the data, integrate with analysis tools, and ensure reproducibility.

Quick Start

To begin, install lamindb using pip install lamindb and follow the provided tutorials to set up your local or cloud instance.

Frequently Asked Questions about lamindb

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

FAQPage Schema
How do I manage biological datasets with FAIR data practices and reproducibility?▼

Managing biological datasets with FAIR data practices involves tracking data lineage, curating with biological ontologies, and integrating with workflow managers like Nextflow or Snakemake to ensure full computational reproducibility.

What is the best way to track lineage for single-cell RNA-seq analysis workflows?▼

Tracking lineage for single-cell RNA-seq workflows requires validating and annotating data with biological ontologies, then connecting pipeline execution with MLOps platforms to monitor version control and data transformations.

Can I use pandas and anndata to curate datasets with biological ontologies?▼

Yes, you can use pandas and anndata to structure biological datasets for curation, leveraging the Bionty library to validate and annotate records against standard biological ontologies for FAIR compliance.

Does this approach integrate with Nextflow and Snakemake for workflow tracking?▼

Yes, this approach integrates directly with workflow managers like Nextflow and Snakemake, allowing you to monitor computational workflows, maintain version control, and ensure data lineage tracking across pipelines.

How do I connect biological data management with MLOps platforms like W&B and MLflow?▼

You can connect biological data management with MLOps platforms by integrating lineage tracking and version control outputs directly into W&B and MLflow, ensuring computational workflows and data transformations are fully reproducible.

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