tiledbvcf

Ingest VCF/BCF files into TileDB sparse arrays for genomic variant queries.

4|Updated Mar 2, 2026
One-click install
npx skills add https://github.com/shushuzn/Rairos --skill tiledbvcf-shushuzn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tiledbvcf
Source: https://github.com/shushuzn/Rairos/tree/main/skills/tiledbvcf
Command: npx skills add https://github.com/shushuzn/Rairos --skill tiledbvcf-shushuzn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of storing and querying large genomic variant datasets efficiently while avoiding slow, costly re-merging and enabling fast region- and sample-scoped access.

Core Features & Use Cases

  • Scalable VCF/BCF ingestion: Ingest single-sample VCF/BCF files into a TileDB-backed sparse array model for high-performance persistence.
  • Incremental sample addition: Add new samples to an existing dataset without expensive rebuilding, supporting cohort growth over time.
  • Parallel querying and export: Retrieve variant attributes (e.g., genotypes, alleles, positions) for specific genomic regions and export subsets back to standard VCF/BCF outputs for downstream pipelines.

Use case examples:

  • Building a population genomics cohort database where samples arrive over time and you need to re-query only what changes.
  • Running region-focused analysis or QC where you repeatedly fetch variant attributes across many samples for specific intervals.
  • Creating shareable VCF subsets (by region and sample) for collaboration, benchmarking, or validation workflows.

Quick Start

Use the tiledbvcf skill to create a TileDB-VCF dataset and ingest indexed single-sample VCFs so you can query specific regions across chosen samples.

Frequently Asked Questions about tiledbvcf

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

FAQPage Schema
How do I store and query genomic variants from VCF files without slow re-merging?

To query genomic variants fast, ingest single-sample VCF/BCF files into a TileDB sparse array. This enables high-performance region- and sample-scoped reads without expensive dataset re-merging.

Can I add new samples to an existing genomic variant dataset incrementally?

Yes, you can add new samples to an existing TileDB-VCF dataset incrementally. This supports cohort growth over time by allowing population genomics samples to be ingested as they arrive without costly rebuilding.

How do I export VCF subsets for specific genomic regions and samples?

You can export VCF subsets by performing parallel querying across chosen genomic intervals and samples. The extracted variant attributes are generated as standard VCF or TSV outputs for downstream analysis pipelines.

Do I need indexed VCF files to ingest genomic data into a sparse array?

Yes, single-sample VCF or BCF inputs require accompanying index files to ingest genomic data into a TileDB sparse array. Inputs use 1-based VCF coordinate semantics for accurate variant positioning.

Can I access genomic variant datasets stored on cloud storage like S3 or Azure?

Yes, TileDB-VCF supports scalable local or cloud dataset access across S3, Azure, and GCS. This enables querying and exporting genomic variant data directly from cloud storage platforms.