ArticleProceedings of the National Academy of Sciences of the United States of America2009
Estimating the number of unseen variants in the human genome.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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37 citing papers in PubMed.
- The impact of DNA input amount and DNA source on the performance of whole-exome sequencing in cancer epidemiology.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2015Trial
- Divergent Clonal Evolution and Early Dissemination Promote Genetic Heterogeneity of Metastases in Castration-Resistant Prostate Cancer.Cancer research · 2025Article
- The hypothetical molecular mechanism of the ethnic variations in the manifestation of age-related macular degeneration; focuses on the functions of the most significant susceptibility genes.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Review
- Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation.Journal of the American Statistical Association · 2024Article
- Bayesian Modeling of Sequential Discoveries.Journal of the American Statistical Association · 2023Article
- Pan-human consensus genome significantly improves the accuracy of RNA-seq analyses.Genome research · 2022Article
- Coexpression network architecture reveals the brain-wide and multiregional basis of disease susceptibility.Nature neuroscience · 2021Article
- Upscaling Statistical Patterns from Reduced Storage in Social and Life Science Big Datasets.Entropy (Basel, Switzerland) · 2020Article
- Using somatic variant richness to mine signals from rare variants in the cancer genome.Nature communications · 2019Article
- Opportunities for improving cancer treatment using systems biology.Current opinion in systems biology · 2019Article
- Optimal prediction of the number of unseen species.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Quantifying unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects.Nature communications · 2016Article
- Applications of species accumulation curves in large-scale biological data analysis.Quantitative biology (Beijing, China) · 2015Article
- Estimating T-cell repertoire diversity: limitations of classical estimators and a new approach.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015Review
- Century-scale methylome stability in a recently diverged Arabidopsis thaliana lineage.PLoS genetics · 2015Article
- Predicting discovery rates of genomic features.Genetics · 2014Article
- BETASEQ: a powerful novel method to control type-I error inflation in partially sequenced data for rare variant association testing.Bioinformatics (Oxford, England) · 2014Article
- Windfalls and pitfalls: Applications of population genetics to the search for disease genes.Evolution, medicine, and public health · 2013Article
- Highly diverse TCRα chain repertoire of pre-immune CD8⁺ T cells reveals new insights in gene recombination.The EMBO journal · 2012Article
- Genetic testing for dilated cardiomyopathy in clinical practice.Journal of cardiac failure · 2012Article
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Abstract
The different genetic variation discovery projects (The SNP Consortium, the International HapMap Project, the 1000 Genomes Project, etc.) aim to identify as much as possible of the underlying genetic variation in various human populations. The question we address in this article is how many new variants are yet to be found. This is an instance of the species problem in ecology, where the goal is to estimate the number of species in a closed population. We use a parametric beta-binomial model that allows us to calculate the expected number of new variants with a desired minimum frequency to be discovered in a new dataset of individuals of a specified size. The method can also be used to predict the number of individuals necessary to sequence in order to capture all (or a fraction of) the variation with a specified minimum frequency. We apply the method to three datasets: the ENCODE dataset, the SeattleSNPs dataset, and the National Institute of Environmental Health Sciences SNPs dataset. Consistent with previous descriptions, our results show that the African population is the most diverse in terms of the number of variants expected to exist, the Asian populations the least diverse, with the European population in-between. In addition, our results show a clear distinction between the Chinese and the Japanese populations, with the Japanese population being the less diverse. To find all common variants (frequency at least 1%) the number of individuals that need to be sequenced is small ( approximately 350) and does not differ much among the different populations; our data show that, subject to sequence accuracy, the 1000 Genomes Project is likely to find most of these common variants and a high proportion of the rarer ones (frequency between 0.1 and 1%). The data reveal a rule of diminishing returns: a small number of individuals ( approximately 150) is sufficient to identify 80% of variants with a frequency of at least 0.1%, while a much larger number (> 3,000 individuals) is necessary to find all of those variants. Finally, our results also show a much higher diversity in environmental response genes compared with the average genome, especially in African populations.
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