Can I use this for single-cell genomics?

Yes, it includes specific patterns for curating and validating AnnData, MuData, and SpatialData objects commonly used in genomics.

How does it ensure reproducibility?

LaminDB automatically tracks data lineage, versioning both the data artifacts and the specific code transforms that created them to ensure full pipeline transparency.

How does this skill help with biological ontologies?

It provides specialized guidance on using the Bionty integration to map datasets to standardized terms for genes, cell types, tissues, and diseases.

Does it support cloud storage?

Yes, the skill covers deployment and management across AWS S3, Google Cloud Storage, and local filesystems using SQLite or PostgreSQL.

LaminDB is an open-source data framework for biology that makes data queryable, traceable, and FAIR (Findable, Accessible, Interoperable, Reusable) via a unified Python API.

LaminDB Biological Data Management

Name: LaminDB Biological Data Management
Author: pur3v4d3r

bypur3v4d3r

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Data Science & ML

Manage, validate, and trace biological datasets using a FAIR-compliant data framework and standardized biological ontologies.

LaminDB provides a comprehensive Python-based framework for biological data management, transforming raw datasets into queryable, traceable, and reproducible assets. It bridges the gap between biological experimental data and computational workflows by integrating biological ontologies for standardized annotation, maintaining automatic lineage tracking from source to analysis, and providing robust schema validation for complex data types like scRNA-seq or spatial transcriptomics. This skill enables researchers and bioinformaticians to build reliable data lakehouses that adhere to FAIR principles while integrating seamlessly with common workflow managers and MLOps platforms.

Key Features

01Biological ontology integration for standardized metadata

02Unified query interface for multi-modal biological lakehouses

031 GitHub stars

04Automatic data lineage and provenance tracking

05Integration with Nextflow, Snakemake, and ML platforms

06Data validation and curation for complex biological schemas

Use Cases

01Ensuring reproducibility in computational biology pipelines

02Building a searchable database for multi-modal biological experiments

03Validating and annotating scRNA-seq datasets with cell type ontologies

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pur3v4d3r/pur3-pkb-codebase lamindb

For use in Claude.ai and ChatGPT

Download Skill