XSI—a genotype compression tool for compressive genomics in large biobanks

Wertenbroek, Rick; Rubinacci, Simone; Xénarios, Ioannis; Thoma, Yann; Delaneau, Olivier

doi:10.1093/bioinformatics/btac413

Cited by 12 publications

(7 citation statements)

References 30 publications

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“…49, 50, 51], and many methods have been suggested to improve on these properties. Most approaches balance compression with performance on particular types of queries, typically using a command line interface (CLI) and outputting VCF text [50, 51, 52, 53, 54, 55, 56, 57, 58, 59]. Several specialised algorithms for compressing the genotype matrix (i.e., just the genotype calls without additional VCF information) have been proposed [60, 61, 62, 63, 64, 65] most notably the Positional Burrows–Wheeler Transform (PBWT) [66].…”

Section: Resultsmentioning

confidence: 99%

Analysis-ready VCF at Biobank scale using Zarr

Czech,

Millar,

Tyler

et al. 2024

Preprint

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BackgroundVariant Call Format (VCF) is the standard file format for interchanging genetic variation data and associated quality control metrics. The usual row-wise encoding of the VCF data model (either as text or packed binary) emphasises efficient retrieval of all data for a given variant, but accessing data on a field or sample basis is inefficient. Biobank scale datasets currently available consist of hundreds of thousands of whole genomes and hundreds of terabytes of compressed VCF. Row-wise data storage is fundamentally unsuitable and a more scalable approach is needed.ResultsWe present the VCF Zarr specification, an encoding of the VCF data model using Zarr which makes retrieving subsets of the data much more efficient. Zarr is a cloud-native format for storing multi-dimensional data, widely used in scientific computing. We show how this format is far more efficient than standard VCF based approaches, and competitive with specialised methods for storing genotype data in terms of compression ratios and calculation performance. We demonstrate the VCF Zarr format (and the vcf2zarr conversion utility) on a subset of the Genomics England aggV2 dataset comprising 78,195 samples and 59,880,903 variants, with a 5X reduction in storage and greater than 300X reduction in CPU usage in some representative benchmarks.ConclusionsLarge row-encoded VCF files are a major bottleneck for current research, and storing and processing these files incurs a substantial cost. The VCF Zarr specification, building on widely-used, open-source technologies has the potential to greatly reduce these costs, and may enable a diverse ecosystem of next-generation tools for analysing genetic variation data directly from cloud-based object stores.

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Section: Resultsmentioning

confidence: 99%

Analysis-ready VCF at Biobank scale using Zarr

Czech,

Millar,

Tyler

et al. 2024

Preprint

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“… 16 , 17 ). To cope with the large numbers of rare variants, SHAPEIT5 uses a sparse data representation for rare variants: only genotypes carrying at least one copy of the minor allele are stored in memory and considered for computation, thereby discarding all genotypes being homozygous for the major allele 21 , 22 . SHAPEIT5 phases each rare heterozygous genotype conditioning on a small number of informative haplotypes (Fig.…”

Section: Resultsmentioning

confidence: 99%

Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank

et al. 2023

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Phasing involves distinguishing the two parentally inherited copies of each chromosome into haplotypes. Here, we introduce SHAPEIT5, a new phasing method that quickly and accurately processes large sequencing datasets and applied it to UK Biobank (UKB) whole-genome and whole-exome sequencing data. We demonstrate that SHAPEIT5 phases rare variants with low switch error rates of below 5% for variants present in just 1 sample out of 100,000. Furthermore, we outline a method for phasing singletons, which, although less precise, constitutes an important step towards future developments. We then demonstrate that the use of UKB as a reference panel improves the accuracy of genotype imputation, which is even more pronounced when phased with SHAPEIT5 compared with other methods. Finally, we screen the UKB data for loss-of-function compound heterozygous events and identify 549 genes where both gene copies are knocked out. These genes complement current knowledge of gene essentiality in the human genome.

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“…Once the first phasing stage is completed at common variants, the resulting haplotypes are used in a second stage as a scaffold onto which rare variants (MAF < 0.1%) are phased one after another. To cope with the large numbers of rare variants, SHAPEIT5 uses a sparse data representation: only genotypes carrying at least one copy of the minor allele are stored in memory and considered for computation, thereby discarding all genotypes being homozygous for the major allele 15,19,20 . SHAPEIT5 phases each rare heterozygous genotype conditioning on a small number of informative haplotypes in the dataset (Figure 1b).…”

Section: Resultsmentioning

confidence: 99%

Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank

Delaneau

Hofmeister

Ribeiro

et al. 2022

Preprint

Self Cite

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The UK Biobank performed whole-genome sequencing (WGS) and whole-exome sequencing (WES) across hundreds of thousands of individuals, allowing researchers to study the effects of both common and rare variants. Haplotype phasing distinguishes the two inherited copies of each chromosome into haplotypes and unlocks novel analyses at the haplotype level. In this work, we describe a new phasing method, SHAPEIT5, that accurately and rapidly phases large sequencing datasets and illustrates its key features on the UK Biobank WGS and WES data. First, we show that it phases rare variants with high accuracy. For instance, variants found in 1 sample out of 100,000 in the WES data are phased with accuracy above 95%. Second, we show that it can phase singletons, although with moderate accuracy, thereby making their inclusion in downstream analyses possible. Third, we show that the use of UK Biobank as a reference panel increases the accuracy of genotype imputation, an increase that is more pronounced when phased with SHAPEIT5 compared to other methods. Finally, we screen the phased WES data for loss-of-functon(LoF) compound heterozygous (CH) events and identify 549 genes in which both gene copies are found knocked out. This list of genes complements current knowledge of gene essentiality in the human genome. We provide SHAPEIT5 in an open-source format, providing researchers with the means to leverage haplotype information in genetic studies.

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XSI—a genotype compression tool for compressive genomics in large biobanks

Cited by 12 publications

References 30 publications

Analysis-ready VCF at Biobank scale using Zarr

Analysis-ready VCF at Biobank scale using Zarr

Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank

Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank

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