---
title: "TileDB-VCF"
type: skill
id: "k-dense-scientific/scientific-python/tiledbvcf"
category: "Research"
publisher: "K-Dense"
license: "MIT"
source: "https://github.com/K-Dense-AI/claude-scientific-skills/tree/a25cf9e"
canonical: "https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/tiledbvcf"
open_in_pho: "https://pho.chat/customize?item=k-dense-scientific%2Fscientific-python%2Ftiledbvcf&utm_source=labs&utm_medium=skill-page&utm_campaign=skills-library"
---

# TileDB-VCF

Stores and retrieves genomic variant calls with TileDB-VCF. Use for indexed single-sample VCF/BCF ingestion, incremental cohorts, region and sample queries, streaming results, allele statistics, QC, and VCF/BCF export locally or through TileDB Cloud.

Source: K-Dense (MIT), copied at a pinned commit. Free to use. Part of the Phở Skills library (https://labs.pho.chat/en/skills).
Skill set: Scientific Python (https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python.md).

## What it covers
- When to use
- Install and verify the native stack
- Prepare and create a cohort
- Query completely and interpret coordinates correctly
- Export and validate
- Cohort statistics and QC
- Object storage and TileDB Cloud
- Official references

## Other skills in this set
- [CZ CELLxGENE Census](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/cellxgene-census.md): Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census…
- [Cirq - Quantum Computing with Python](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/cirq.md): Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise…
- [Datamol Cheminformatics Skill](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/datamol.md): Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering…
- [Histolab](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/histolab.md): Extracts and preprocesses whole-slide histology image tiles with Histolab. Use for WSI inspection, tissue masks, random/grid/score-based tile extraction, H&E stain normalization, and tile dataset…
- [LaminDB](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/lamindb.md): Manages biological datasets and models with LaminDB, including artifact registration, lineage tracking, schema validation, Bionty ontology annotation, query/search, collections, branches, storage…
- [Molecular Dynamics](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/molecular-dynamics.md): Runs and analyzes molecular dynamics simulations with OpenMM and MDAnalysis. Sets up protein/small molecule systems, defines force fields, runs energy minimization and production MD, and analyzes…
- [Molfeat — Small-molecule featurization](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/molfeat.md): Featurizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML. Covers ECFP/MACCS fingerprints, RDKit descriptors, pharmacophores, pretrained…
- [GPU Optimization for Python with NVIDIA](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/optimize-for-gpu.md): GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX…
- [PennyLane](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/pennylane.md): Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator…
- [polars-bio](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/polars-bio.md): Performs genomic interval overlap, nearest, merge, coverage, complement and subtraction on Polars DataFrames, and reads or writes BED, VCF, BCF, BAM, CRAM, GFF, GTF, FASTA and FASTQ data. Use for…
- [PyTorch Geometric (PyG)](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/torch-geometric.md): Supports PyTorch Geometric (PyG) graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use…
- [TorchDrug](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/torchdrug.md): Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and…
- [Transformers](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/transformers.md): Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with…
- [Vaex](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/vaex.md): Processes large tabular scientific datasets with Vaex expressions, filtered views, streamed statistics, binned visualizations, and file conversion. Use for larger-than-RAM HDF5, Arrow, CSV, or…
- [Zarr Python](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/zarr-python.md): Stores and queries chunked N-D scientific arrays with Zarr-Python 3, including codecs, sharding, S3/GCS storage, and NumPy/Dask/Xarray integration. Use for array layout, bounded I/O, format…

## Use it
- In Phở: open https://pho.chat/customize?item=k-dense-scientific%2Fscientific-python%2Ftiledbvcf&utm_source=labs&utm_medium=skill-page&utm_campaign=skills-library and press Try, or add it so Phở loads it whenever a request matches. Phở works with your own API key (OpenAI, Anthropic, Google and others).
- Full instructions (original SKILL.md, unchanged): https://labs.pho.chat/skills/raw/k-dense-scientific/scientific-python/skills/tiledbvcf/SKILL.md
- Original files: https://github.com/K-Dense-AI/claude-scientific-skills/tree/a25cf9e (MIT).
- Full machine-readable index: https://labs.pho.chat/skills.json