ArticlebioRxiv : the preprint server for biology2024
The Scalable Variant Call Representation: Enabling Genetic Analysis Beyond One Million Genomes.
Timothy Poterba, Christopher Vittal, Daniel King, Daniel Goldstein, Jacqueline I Goldstein, Patrick Schultz, Konrad J Karczewski, Cotton Seed, Benjamin M Neale
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In one paragraphArticle in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 · Who and what moneyAuthors and funding
9 authors.
Timothy PoterbaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Christopher VittalProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Daniel KingProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0003-3319-9733 Daniel GoldsteinProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Jacqueline I GoldsteinProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Patrick SchultzProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Konrad J KarczewskiProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Cotton SeedProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Benjamin M NealeProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0003-1513-6077 Funding
Pilot & Feasibility ProgramP30DK043351 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI RAYMOND T CHUNG · 1991 to 2026
$35.3MThe Genome Aggregation Database (gnomAD)U24HG011450 · NHGRI · BROAD INSTITUTE, INC. · PI Mark Joseph Daly, Konrad Karczewski · 2021 to 2026
$22.3MGenetic neuroscience: How human genes and alleles shape neuronal phenotypesU01MH115727 · NIMH · BROAD INSTITUTE, INC. · PI ARLOTTA, PAOLA, BABADI, MEHRTASH · 2017 to 2021
$20.8MJoint Center for Mendelian GenomicsUM1HG008900 · NHGRI · BROAD INSTITUTE, INC. · PI O'DONNELL-LURIA, ANNE, REHM, HEIDI L · 2016 to 2020
$16.5MComputational resources for genomic interpretation of type 2 diabetesU54DK105566 · NIDDK · BROAD INSTITUTE, INC. · PI MACARTHUR, DANIEL G, NEALE, BENJAMIN MICHAEL · 2014 to 2017
$8.6MStatistical methods to localize disease heritability and identify biological mechanismsR37MH107649 · NIMH · BROAD INSTITUTE, INC. · PI Benjamin Michael Neale · 2019 to 2026
$7.0MPowering whole genome sequence-based genetic discovery for common human diseases- Extended 2021-2022.U01HG009088 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIN, XIHONG, NEALE, BENJAMIN MICHAEL · 2016 to 2021
$5.1MStatistical methods to localize disease heritability and identify biological mechanismsR01MH107649 · NIMH · BROAD INSTITUTE, INC. · PI NEALE, BENJAMIN MICHAEL · 2015 to 2018
$2.9MNHGRI NIH HHS U01 HG009088NHGRI NIH HHS U24 HG011450NHGRI NIH HHS UM1 HG008900NIDDK NIH HHS P30 DK043351NIDDK NIH HHS U54 DK105566NIMH NIH HHS R01 MH107649NIMH NIH HHS R37 MH107649NIMH NIH HHS U01 MH115727
6 · The paper itselfAbstract
The Variant Call Format (VCF) is widely used in genome sequencing but scales poorly. For instance, we estimate a 150,000 genome VCF would occupy 900 TiB, making it both costly and complicated to produce and analyze. The issue stems from VCF's requirement to densely represent both reference-genotypes and allele-indexed arrays. These requirements lead to unnecessary data duplication and, ultimately, very large files. To address these challenges, we introduce the Scalable Variant Call Representation (SVCR). This representation reduces file sizes by ensuring they scale linearly with samples. SVCR achieves this by adopting reference blocks from the Genomic Variant Call Format (GVCF) and employing local allele indices. SVCR is also lossless and mergeable, allowing for N+1 and N+K incremental joint-calling. We present two implementations of SVCR: SVCR-VCF, which encodes SVCR in VCF format, and VDS, which uses Hail's native format. Our experiments confirm the linear scalability of SVCR-VCF and VDS, in contrast to the super-linear growth seen with standard VCF files. We also discuss the VDS Combiner, a scalable, open-source tool for producing a VDS from GVCFs and unique features of VDS which enable rapid data analysis. SVCR, and VDS in particular, ensure the scientific community can generate, analyze, and disseminate genetics datasets with millions of samples.
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PMID38260295
PMCPMC10802441
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