Data & ReproBioinformatics & GenomicsK-Dense-AI/claude-scientific-skillsData & Reproduction

tiledbvcf

Maintainer Jeremy Leipzig · Last updated April 1, 2026

TileDB-VCF is a high-performance C++ library with Python and CLI interfaces for efficient storage and retrieval of genomic variant-call data. Built on TileDB's sparse array technology, it enables scalable ingestion of VCF/BCF files, incremental sample addition without expensive merging operations, and efficient parallel queries of variant data stored locally or in the cloud.

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Original source

K-Dense-AI/claude-scientific-skills

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/tiledbvcf

Maintainer: Jeremy Leipzig
License: MIT license
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

TileDB-VCF is a high-performance C++ library with Python and CLI interfaces for efficient storage and retrieval of genomic variant-call data. Built on TileDB's sparse array technology, it enables scalable ingestion of VCF/BCF files, incremental sample addition without expensive merging operations, and efficient parallel queries of variant data stored locally or in the cloud.
CONDA_SUBDIR=osx-64 conda config --env --set subdir osx-64.

Source Doc

Excerpt From SKILL.md

When to Use This Skill

This skill should be used when:

Learning TileDB-VCF concepts and workflows
Prototyping genomics analyses and pipelines
Working with small-to-medium datasets (< 1000 samples)
Need incremental addition of new samples to existing datasets
Require efficient querying of specific genomic regions across many samples
Working with cloud-stored variant data (S3, Azure, GCS)
Need to export subsets of large VCF datasets
Building variant databases for cohort studies
Educational projects and method development
Performance is critical for variant data operations

Installation

Preferred Method: Conda/Mamba


## Create the conda environment

conda create -n tiledb-vcf "python<3.10"
conda activate tiledb-vcf

Use cases

Learning TileDB-VCF concepts and workflows.
Prototyping genomics analyses and pipelines.
Working with small-to-medium datasets (< 1000 samples).
Need incremental addition of new samples to existing datasets.

Not for

Do not rely on this catalog entry alone for installation or maintenance details.
Do not assume this entry replaces the original database documentation or API notes.