Linkage Disequilibrium, Recombination and Haplotype Structure

McVean, Gil; Kelleher, Jerome

doi:10.1002/9781119487845.ch2

Cited by 2 publications

(2 citation statements)

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“…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]. See [67] for a review of the techniques employed in genetic data compression. The widely-used PLINK binary format stores genotypes in a packed binary representation, supporting only biallelic variants without phase information.…”

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

Self Cite

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“…The LS model is used in a wide variety of applications in genomics, including modern approaches to statistical genotype phasing and imputation (Delaneau et al, 2019;Browning et al, 2021Browning et al, , 2018Rubinacci et al, 2020), and estimation of parameters such as recombination rates (e.g., Hinch et al, 2011) and intensity of selection within and across hosts in viral sequence data (e.g., Palmer et al, 2019). See McVean and Kelleher (2019) for further review and discussion of the LS model.…”

Section: The LI and Stephens Modelmentioning

confidence: 99%

Towards Pandemic-Scale Ancestral Recombination Graphs of SARS-CoV-2

Zhan¹,

Ignatieva

Wong³

et al. 2023

Preprint

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Recombination is an ongoing and increasingly important feature of circulating lineages of SARS-CoV-2, challenging how we represent the evolutionary history of this virus and giving rise to new variants of potential public health concern by combining transmission and immune evasion properties of different lineages. Detection of new recombinant strains is challenging, with most methods looking for breaks between sets of mutations that characterise distinct lineages. In addition, many basic approaches fundamental to the study of viral evolution assume that recombination is negligible, in that a single phylogenetic tree can represent the genetic ancestry of the circulating strains. Here we present an initial version of sc2ts, a method to automatically detect recombinants in real time and to cohesively integrate them into a genealogy in the form of an ancestral recombination graph (ARG), which jointly records mutation, recombination and genetic inheritance. We infer two ARGs under different sampling strategies, and study their properties. One contains 1.27 million sequences sampled up to June 30, 2021, and the second is more sparsely sampled, consisting of 657K sequences sampled up to June 30, 2022. We find that both ARGs are highly consistent with known features of SARS-CoV-2 evolution, recovering the basic backbone phylogeny, mutational spectra, and recapitulating details on the majority of known recombinant lineages. Using the well-established and feature-rich tskit library, the ARGs can also be stored concisely and processed efficiently using standard Python tools. For example, the ARG for 1.27 million sequences---encoding the inferred reticulate ancestry, genetic variation, and extensive metadata---requires 58MB of storage, and loads in less than a second. The ability to fully integrate the effects of recombination into downstream analyses, to quickly and automatically detect new recombinants, and to utilise an efficient and convenient platform for computation based on well-engineered technologies makes sc2ts a promising approach.

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Linkage Disequilibrium, Recombination and Haplotype Structure

Cited by 2 publications

References 174 publications

Analysis-ready VCF at Biobank scale using Zarr

Analysis-ready VCF at Biobank scale using Zarr

Towards Pandemic-Scale Ancestral Recombination Graphs of SARS-CoV-2

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