ArticleMammalian genome : official journal of the International Mammalian Genome Society2022
Best practices for analyzing imputed genotypes from low-pass sequencing in dogs.
Article in Mammalian genome : official journal of the International Mammalian Genome Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 39 citations in OpenAlex.
- Imputation in the Wild: Genome-Wide Robustness and Fine-Scale Limitations of Low-Coverage Genomes in Endangered Species.Molecular ecology resources · 2026Article
- Opportunities and computational challenges in large-scale whole-genome sequencing data analysis.Journal of animal science · 2026Review
- 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
- Assessing Genotype Imputation Methods for Low-Coverage Sequencing Data in Populations With Differing Relatedness and Inbreeding Levels.Molecular ecology resources · 2025Article
- Large-scale genomic analysis of the domestic dog informs biological discovery.Genome research · 2024Review
- Low-pass sequencing plus imputation using avidity sequencing displays comparable imputation accuracy to sequencing by synthesis while reducing duplicates.G3 (Bethesda, Md.) · 2024Article
- A cautionary tale of low-pass sequencing and imputation with respect to haplotype accuracy.Genetics, selection, evolution : GSE · 2024Article
- GWAS using low-pass whole genome sequence reveals a novel locus in canine congenital idiopathic megaesophagus.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Article
- Genome sequencing of 2000 canids by the Dog10K consortium advances the understanding of demography, genome function and architecture.Genome biology · 2023Article
- Skim resequencing finely maps the downy mildew resistance lociHorticulture research · 2023Article
- Ancestry-inclusive dog genomics challenges popular breed stereotypes.Science (New York, N.Y.) · 2022Article
- An autoencoder-based deep learning method for genotype imputation.Frontiers in artificial intelligence · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although DNA array-based approaches for genome-wide association studies (GWAS) permit the collection of thousands of low-cost genotypes, it is often at the expense of resolution and completeness, as SNP chip technologies are ultimately limited by SNPs chosen during array development. An alternative low-cost approach is low-pass whole genome sequencing (WGS) followed by imputation. Rather than relying on high levels of genotype confidence at a set of select loci, low-pass WGS and imputation rely on the combined information from millions of randomly sampled low-confidence genotypes. To investigate low-pass WGS and imputation in the dog, we assessed accuracy and performance by downsampling 97 high-coverage (> 15×) WGS datasets from 51 different breeds to approximately 1× coverage, simulating low-pass WGS. Using a reference panel of 676 dogs from 91 breeds, genotypes were imputed from the downsampled data and compared to a truth set of genotypes generated from high-coverage WGS. Using our truth set, we optimized a variant quality filtering strategy that retained approximately 80% of 14 M imputed sites and lowered the imputation error rate from 3.0% to 1.5%. Seven million sites remained with a MAF > 5% and an average imputation quality score of 0.95. Finally, we simulated the impact of imputation errors on outcomes for case-control GWAS, where small effect sizes were most impacted and medium-to-large effect sizes were minorly impacted. These analyses provide best practice guidelines for study design and data post-processing of low-pass WGS-imputed genotypes in dogs.
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