Sparse Project VCF: efficient encoding of population genotype matrices

preprint OA: closed CC-BY-4.0
📄 Open PDF View at publisher
AI-generated summary by claude@2026-07, 2026-07-16

Sparse Project VCF (spVCF) reduces the size of population genotype matrices by over 10X using entropy reduction and run-length encoding while maintaining interoperability and random access.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

Abstract

Summary Variant Call Format (VCF), the prevailing representation for germline genotypes in population sequencing, suffers rapid size growth as larger cohorts are sequenced and more rare variants are discovered. We present Sparse Project VCF (spVCF), an evolution of VCF with judicious entropy reduction and run-length encoding, delivering >10X size reduction for modern studies with practically minimal information loss. spVCF interoperates with VCF efficiently, including tabix-based random access. Availability and Implementation Freely available at github.com/mlin/spVCF Contact [email protected]

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-24T02:00:01.246996+00:00
License: CC-BY-4.0