ArticleAmerican journal of human genetics2012
Phasing of many thousands of genotyped samples.
Article in American journal of human genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
72 citing papers in PubMed, 2 syntheses or guidelines pooled it, 124 citations in OpenAlex.
- Cross-ethnic meta-analysis identifies association of the GPX3-TNIP1 locus with amyotrophic lateral sclerosis.Nature communications · 2017Pooled it
- Pooled it
- Advances in haplotype phasing and genotype imputation.Nature reviews. Genetics · 2026Review
- Phasing millions of samples achieves near perfect accuracy, enabling parent-of-origin analyses.HGG advances · 2025Article
- Induced and natural variation affect traits independently in hybrid Populus.G3 (Bethesda, Md.) · 2024Article
- Cancer risks among first-degree relatives of women with a genetic predisposition to breast cancer.Journal of the National Cancer Institute · 2024Article
- Prediction of breast cancer risk for sisters of women attending screening.Journal of the National Cancer Institute · 2023Article
- The genomic analysis of current-day North African populations reveals the existence of trans-Saharan migrations with different origins and dates.Human genetics · 2023Article
- Accurate genome-wide phasing from IBD data.BMC bioinformatics · 2022Article
- Genotype error biases trio-based estimates of haplotype phase accuracy.American journal of human genetics · 2022Article
- Reconstructing the history of founder events using genome-wide patterns of allele sharing across individuals.PLoS genetics · 2022Article
- Impact of polygenic risk for coronary artery disease and cardiovascular medication burden on cognitive impairment in psychotic disorders.Progress in neuro-psychopharmacology & biological psychiatry · 2022Article
- Article
- Fast two-stage phasing of large-scale sequence data.American journal of human genetics · 2021Article
- Mammographic features are associated with cardiometabolic disease risk and mortality.European heart journal · 2021Article
- Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2021Article
- A Continuous Statistical Phasing Framework for the Analysis of Forensic Mitochondrial DNA Mixtures.Genes · 2021Article
- Polygenic Scores for Height in Admixed Populations.G3 (Bethesda, Md.) · 2020Article
- Exploring effective approaches for haplotype block phasing.BMC bioinformatics · 2019Article
- Interval breast cancer is associated with other types of tumors.Nature communications · 2019Article
12 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Haplotypes are an important resource for a large number of applications in human genetics, but computationally inferred haplotypes are subject to switch errors that decrease their utility. The accuracy of computationally inferred haplotypes increases with sample size, and although ever larger genotypic data sets are being generated, the fact that existing methods require substantial computational resources limits their applicability to data sets containing tens or hundreds of thousands of samples. Here, we present HAPI-UR (haplotype inference for unrelated samples), an algorithm that is designed to handle unrelated and/or trio and duo family data, that has accuracy comparable to or greater than existing methods, and that is computationally efficient and can be applied to 100,000 samples or more. We use HAPI-UR to phase a data set with 58,207 samples and show that it achieves practical runtime and that switch errors decrease with sample size even with the use of samples from multiple ethnicities. Using a data set with 16,353 samples, we compare HAPI-UR to Beagle, MaCH, IMPUTE2, and SHAPEIT and show that HAPI-UR runs 18× faster than all methods and has a lower switch-error rate than do other methods except for Beagle; with the use of consensus phasing, running HAPI-UR three times gives a slightly lower switch-error rate than Beagle does and is more than six times faster. We demonstrate results similar to those from Beagle on another data set with a higher marker density. Lastly, we show that HAPI-UR has better runtime scaling properties than does Beagle so that for larger data sets, HAPI-UR will be practical and will have an even larger runtime advantage. HAPI-UR is available online (see Web Resources).
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What OpenQuestion holds
Registered trials
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.