| Title: | Sparse Project VCF: efficient encoding of population genotype matrices |
| Journal: | Bioinformatics |
| Published: | 10 Dec 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33300997/ |
| DOI: | https://doi.org/10.1093/bioinformatics/btaa1004 |
| URL: | https://academic.oup.com/bioinformatics/article-pdf/36/22-23/5537/36855912/btaa1004.pdf |
| Citations: | 6 (2 in last 2 years) as of 8 Aug 2024 |
Publication 5771
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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 >10× size reduction for modern studies with practically minimal information loss. spVCF interoperates with VCF efficiently, including tabix-based random access. We demonstrate its effectiveness with the DiscovEHR and UK Biobank whole-exome sequencing cohorts.</p>
AVAILABILITY AND IMPLEMENTATION: Apache-licensed reference implementation: github.com/mlin/spVCF.</p>
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.</p>
5 Keywords
- Base Sequence
- Genomics
- Genotype
- Germ Cells
- Software
4 Authors
- Michael F Lin
- Xiaodong Bai
- William J Salerno
- Jeffrey G Reid
Enabling scientific discoveries that improve human health