ArticleBioinformatics (Oxford, England)2022
XSI-a genotype compression tool for compressive genomics in large biobanks.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Selphi, a tool for improving genotype imputation accuracy.Scientific reports · 2026Article
- Highly efficient genotype compression leveraging genealogical relatedness.bioRxiv : the preprint server for biology · 2026Article
- General, orders-of-magnitude faster whole-genome analysis with genotype representation graphs.bioRxiv : the preprint server for biology · 2026Article
- Fast phenotype simulation for genotype representation graphs.Bioinformatics advances · 2026Article
- Enhancing Data Compression: Recent Innovations in LZ77 Algorithms.Journal of computational biology : a journal of computational molecular cell biology · 2025Review
- Analysis-ready VCF at Biobank scale using Zarr.bioRxiv : the preprint server for biology · 2025Article
- Enabling efficient analysis of biobank-scale data with genotype representation graphs.Nature computational science · 2025Article
- Analysis-ready VCF at Biobank scale using Zarr.GigaScience · 2025Article
- IGD: a simple, efficient genotype data format.Bioinformatics advances · 2025Article
- Genotype Representation Graphs: Enabling Efficient Analysis of Biobank-Scale Data.bioRxiv : the preprint server for biology · 2024Article
- Improving population scale statistical phasing with whole-genome sequencing data.PLoS genetics · 2024Article
- GSC: efficient lossless compression of VCF files with fast query.GigaScience · 2024Article
- Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank.Nature genetics · 2023Article
- Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression.Bioinformatics advances · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
motivationGeneration of genotype data has been growing exponentially over the last decade. With the large size of recent datasets comes a storage and computational burden with ever increasing costs. To reduce this burden, we propose XSI, a file format with reduced storage footprint that also allows computation on the compressed data and we show how this can improve future analyses.
resultsWe show that xSqueezeIt (XSI) allows for a file size reduction of 4-20× compared with compressed BCF and demonstrate its potential for 'compressive genomics' on the UK Biobank whole-genome sequencing genotypes with 8× faster loading times, 5× faster run of homozygozity computation, 30× faster dot products computation and 280× faster allele counts. AVAILABILITY AND IMPLEMENTATION: The XSI file format specifications, API and command line tool are released under open-source (MIT) license and are available at https://github.com/rwk-unil/xSqueezeIt. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.