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Sparse Project VCF: efficient encoding of population genotype matrices

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 reduct...

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Detalles Bibliográficos
Autores principales: Lin, Michael F, Bai, Xiaodong, Salerno, William J, Reid, Jeffrey G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016461/
https://www.ncbi.nlm.nih.gov/pubmed/33300997
http://dx.doi.org/10.1093/bioinformatics/btaa1004
Descripción
Sumario: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. AVAILABILITY AND IMPLEMENTATION: Apache-licensed reference implementation: github.com/mlin/spVCF. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.