ArticleBioinformatics (Oxford, England)2019
Very low-depth whole-genome sequencing in complex trait association studies.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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Who cites it
53 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gene-based whole genome sequencing meta-analysis of 250 circulating proteins in three isolated European populations.Molecular metabolism · 2022Pooled it
- Low-pass whole-genome sequencing reveals genomic diversity and ecotype-specific adaptation in indigenous Tigrayan chickens.Scientific reports · 2026Article
- Development of a low-coverage whole genome sequencing screen for apomixis using a diverse set of Malus germplasm.PLoS genetics · 2026Article
- A novel simulation tool for low-coverage whole-genome sequencing using multivariate Gaussian mixture models.BMC bioinformatics · 2026Article
- Imputation of ancient canid genomes reveals inbreeding history over the past 10,000 years.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Comparison between SNP array and imputed data to estimate population structure and ROH hotspots in horse breeds.BMC genomics · 2025Article
- High Imputation Accuracy Can Be Achieved Using a Small Reference Panel in a Natural Population With Low Genetic Diversity.Molecular ecology resources · 2025Article
- Fine mapping genetic variants affecting birth weight in sheep: a GWAS of 3007 individuals using low-coverage whole genome sequencing.Journal of animal science and biotechnology · 2025Article
- DPImpute: A Genotype Imputation Framework for Ultra-Low Coverage Whole-Genome Sequencing and its Application in Genomic Selection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Genomic Landscape and Prediction of Udder Traits in Saanen Dairy Goats.Animals : an open access journal from MDPI · 2025Article
- Accurate genotype imputation from low-coverage whole-genome sequencing data of rainbow trout.G3 (Bethesda, Md.) · 2024Article
- Robustness in population-structure and demographic-inference results derived from the Aedes aegypti genotyping chip and whole-genome sequencing data.G3 (Bethesda, Md.) · 2024Article
- A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.NPJ genomic medicine · 2024Article
- Diagnostic challenges in complicated case of glioblastoma.Pathology oncology research : POR · 2024Article
- Variant calling and genotyping accuracy of ddRAD-seq: Comparison with 20X WGS in layers.PloS one · 2024Article
- Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients.GigaByte (Hong Kong, China) · 2024Article
- Association between clonal hematopoiesis-related gene mutations and unfavorable functional outcome in patients with large-artery atherosclerotic stroke.European journal of medical research · 2023Article
- Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease.Nature protocols · 2023Review
- Evaluating the potential of (epi)genotype-by-low pass nanopore sequencing in dairy cattle: a study on direct genomic value and methylation analysis.Journal of animal science and biotechnology · 2023Article
- S-leaping: an efficient downsampling method for large high-throughput sequencing data.Bioinformatics (Oxford, England) · 2023Article
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17 authors.
Funding
Abstract
motivationVery low-depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterization of the genotype quality and association power for very low-depth sequencing designs is still lacking.
resultsWe perform cohort-wide whole-genome sequencing (WGS) at low depth in 1239 individuals (990 at 1× depth and 249 at 4× depth) from an isolated population, and establish a robust pipeline for calling and imputing very low-depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (75× depth) and high-depth (22×) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1× WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1× further allowed the discovery of 140 844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low-depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design. AVAILABILITY AND IMPLEMENTATION: The HELIC genotype and WGS datasets have been deposited to the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home): EGAD00010000518; EGAD00010000522; EGAD00010000610; EGAD00001001636, EGAD00001001637. The peakplotter software is available at https://github.com/wtsi-team144/peakplotter, the transformPhenotype app can be downloaded at https://github.com/wtsi-team144/transformPhenotype. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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