tiledbvcf

Store, ingest, and query genomic variant data with TileDB-VCF.

1|Updated Mar 11, 2026

Search Tags:#genomics #ingestion #query #export #cohort #vcf #tiledb-vcf

Ready to run

npx skills add https://github.com/SciMate-AI/scicli --skill tiledbvcf-scimate-ai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tiledbvcf
Source: https://github.com/SciMate-AI/scicli/tree/main/internal/skills/bundled/claude-scientific-skills/skills/tiledbvcf
Command: npx skills add https://github.com/SciMate-AI/scicli --skill tiledbvcf-scimate-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

TileDB-VCF provides high-performance storage and retrieval of genomic variant data, enabling scalable ingestion, querying, and export for large cohorts.

Core Features & Use Cases

Ingest single-sample VCFs and manage cohorts efficiently
Fast region-based queries across thousands of samples
Export VCF/TSV/other formats for downstream analyses
Suitable for population genomics workflows, GWAS preparation, and cohort management

Quick Start

Create a TileDB-VCF dataset, ingest samples, and perform a read to retrieve variant data.

Frequently Asked Questions about tiledbvcf

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

FAQPage Schema

How do I ingest and query large cohorts of VCF files efficiently?▼

You can ingest and query large cohorts of VCF files efficiently by storing them in a TileDB-backed sparse array, which supports incremental single-sample ingestion and fast parallel region-based queries across thousands of samples.

What is the best way to manage population genomics variant data for cloud-based pipelines?▼

Managing population genomics variant data for cloud-based pipelines is best handled by using a TileDB-VCF sparse array data model that enables scalable storage, incremental sample ingestion, and multi-format export for downstream GWAS analyses.

Can I export queried genomic variant data to formats other than VCF?▼

Yes, you can export queried genomic variant data to other formats. The system supports exporting retrieved variant data into VCF, TSV, and other formats to facilitate downstream analyses and integration with various bioinformatics tools.

Does TileDB-VCF support region-based queries across thousands of samples?▼

Yes, TileDB-VCF supports region-based queries across thousands of samples. It enforces a sparse array data model designed for fast parallel querying, allowing you to retrieve specific genomic variants from large cohorts efficiently.

What interfaces are available for end-to-end genomic variant data workflows?▼

Available interfaces for end-to-end genomic variant data workflows include Python, C++, and CLI options. These interfaces allow you to create datasets, ingest single-sample VCFs, and perform read operations to retrieve variant data programmatically or via command line.

When should I use a sparse array model for genomic variant storage instead of traditional files?▼

You should use a sparse array model for genomic variant storage when you need incremental sample ingestion, fast parallel querying across large cohorts, and cloud-based scalability that traditional flat VCF file storage cannot efficiently provide.