Robust Demographic Inference from Genomic and SNP Data
Publication Date
October 24, 2013
Journal
PLOS Genetics
Authors
Laurent Excoffier, Isabelle Dupanloup, Emilia Huerta Sánchez, Vitor C. Sousa, et al
Volume
9
Issue
10
Pages
e1003905
DOI
https://dx.plos.org/10.1371/journal.pgen.1003905
Publisher URL
http://journals.plos.org/plosgenetics/article?id=10.1371%2Fjournal.pgen.1003905
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/24204310
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3812088
Europe PMC
http://europepmc.org/abstract/MED/24204310
Web of Science
000330367200070
Scopus
84887312794
Mendeley
http://www.mendeley.com/research/robust-demographic-inference-genomic-snp-data
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Mendeley | Further Information

{"title"=>"Robust Demographic Inference from Genomic and SNP Data", "type"=>"journal", "authors"=>[{"first_name"=>"Laurent", "last_name"=>"Excoffier", "scopus_author_id"=>"7004470075"}, {"first_name"=>"Isabelle", "last_name"=>"Dupanloup", "scopus_author_id"=>"6602711154"}, {"first_name"=>"Emilia", "last_name"=>"Huerta-Sánchez", "scopus_author_id"=>"6504236582"}, {"first_name"=>"Vitor C.", "last_name"=>"Sousa", "scopus_author_id"=>"23989723700"}, {"first_name"=>"Matthieu", "last_name"=>"Foll", "scopus_author_id"=>"9640149500"}], "year"=>2013, "source"=>"PLoS Genetics", "identifiers"=>{"issn"=>"15537390", "scopus"=>"2-s2.0-84887312794", "sgr"=>"84887312794", "pui"=>"370217953", "isbn"=>"1553-7390", "pmid"=>"24204310", "doi"=>"10.1371/journal.pgen.1003905"}, "id"=>"f0cc02b2-2df0-3ca0-b091-3ece7c951de5", "abstract"=>"Author Summary We present a new likelihood-based method to infer the past demography of a set of populations from large genomic datasets. Our method can be applied to arbitrarily complex models as the likelihood is estimated by coalescent simulations. Under simple scenarios, our method behaves similarly to a widely used diffusion-based method while showing better convergence properties. In addition, our approach can be applied to very complex models including as many as a dozen populations, and still retrieve parameters very accurately in a reasonable time. We apply our approach to estimate the past demography of four human populations for which non-coding whole genome diversity is available, estimating the degree of European admixture of a southwest African American population and that of a Kenyan population with an unsampled East African population. We also show the versatility of our framework by inferring the demographic history of African populations from SNP chip data with known ascertainment bias, and find a very old divergence time (>110 Ky) between Yorubas from Western Africa and Sans from Southern Africa.", "link"=>"http://www.mendeley.com/research/robust-demographic-inference-genomic-snp-data", "reader_count"=>604, "reader_count_by_academic_status"=>{"Unspecified"=>10, "Professor > Associate Professor"=>36, "Researcher"=>137, "Student > Doctoral Student"=>17, "Student > Ph. D. Student"=>218, "Student > Postgraduate"=>22, "Student > Master"=>75, "Other"=>10, "Student > Bachelor"=>45, "Lecturer"=>6, "Lecturer > Senior Lecturer"=>4, "Professor"=>24}, "reader_count_by_user_role"=>{"Unspecified"=>10, "Professor > Associate Professor"=>36, "Researcher"=>137, "Student > Doctoral Student"=>17, "Student > Ph. D. Student"=>218, "Student > Postgraduate"=>22, "Student > Master"=>75, "Other"=>10, "Student > Bachelor"=>45, "Lecturer"=>6, "Lecturer > Senior Lecturer"=>4, "Professor"=>24}, "reader_count_by_subject_area"=>{"Unspecified"=>20, "Agricultural and Biological Sciences"=>471, "Arts and Humanities"=>2, "Computer Science"=>5, "Earth and Planetary Sciences"=>2, "Environmental Science"=>14, "Biochemistry, Genetics and Molecular Biology"=>72, "Mathematics"=>5, "Medicine and Dentistry"=>5, "Neuroscience"=>2, "Physics and Astronomy"=>2, "Social Sciences"=>2, "Immunology and Microbiology"=>1, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>5}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Mathematics"=>{"Mathematics"=>5}, "Unspecified"=>{"Unspecified"=>20}, "Environmental Science"=>{"Environmental Science"=>14}, "Arts and Humanities"=>{"Arts and Humanities"=>2}, "Neuroscience"=>{"Neuroscience"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>471}, "Computer Science"=>{"Computer Science"=>5}, "Linguistics"=>{"Linguistics"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>72}}, "reader_count_by_country"=>{"United States"=>28, "United Kingdom"=>5, "Portugal"=>3, "Switzerland"=>4, "Spain"=>1, "Austria"=>1, "Netherlands"=>1, "Sweden"=>1, "Norway"=>1, "China"=>1, "Finland"=>1, "Brazil"=>8, "Italy"=>1, "Israel"=>1, "France"=>1, "Germany"=>3}, "group_count"=>10}

CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1257430"], "description"=>"<p>Parameters are defined in <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003905#pgen-1003905-g005\" target=\"_blank\">Figure 5</a>.</p>a<p>Population size estimates have been rounded to the nearest hundred.</p>b<p>Parametric bootstrap estimates obtained by parameter estimation from 100 data sets simulated according to CML estimates in point estimation columns.</p><p>Estimates were obtained from 100,000 simulations per likelihood and 20 ECM cycle.</p>", "links"=>[], "tags"=>["african"], "article_id"=>831963, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1003905.t002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inferred_parameters_of_African_demographic_history_for_model_A_and_B_/831963", "title"=>"Inferred parameters of African demographic history for model A and B.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-24 03:19:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1257429"], "description"=>"<p>A) Simple model of population divergence. The San and Yoruba populations are assumed to have split from an ancestral African population and to have gone through a recent populations size increase. They also had a single pulse of asymmetrical gene flow (admixture) T<sub>a</sub> generations ago. B) More complex scenario, where the San and Yoruba demes belong to two distinct continent-island structures, which have also admixed asymmetrically T<sub>a</sub> generations ago. The ancestral Yoruba and San populations would have gone through exponential growth at different times, and have exchanged genes just after their divergence until T<sub>EY</sub> generations ago. In both models, we assumed that the Denisova population diverged from the ancestral human population 16,000 generations ago, as estimated in <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003905#pgen.1003905-Reich1\" target=\"_blank\">[58]</a> based on an ancestral population size of 10,000 diploids (see Table S11.2 in Suppl. Mat. of ref. <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003905#pgen.1003905-Reich1\" target=\"_blank\">[58]</a>). This date would correspond to ≈400,000 years assuming a generation time of 25 y. The models and their parameters are further described in the Material and Methods section.</p>", "links"=>[], "tags"=>["african"], "article_id"=>831962, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1003905.g005", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Alternative_demographic_models_for_two_African_populations_/831962", "title"=>"Alternative demographic models for two African populations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-24 03:19:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1257443", "https://ndownloader.figshare.com/files/1257444", "https://ndownloader.figshare.com/files/1257445", "https://ndownloader.figshare.com/files/1257446", "https://ndownloader.figshare.com/files/1257447", "https://ndownloader.figshare.com/files/1257448", "https://ndownloader.figshare.com/files/1257449", "https://ndownloader.figshare.com/files/1257450", "https://ndownloader.figshare.com/files/1257451", "https://ndownloader.figshare.com/files/1257452", "https://ndownloader.figshare.com/files/1257453", "https://ndownloader.figshare.com/files/1257454", "https://ndownloader.figshare.com/files/1257455", "https://ndownloader.figshare.com/files/1257456", "https://ndownloader.figshare.com/files/1257457", "https://ndownloader.figshare.com/files/1257458", "https://ndownloader.figshare.com/files/1257459", "https://ndownloader.figshare.com/files/1257460", "https://ndownloader.figshare.com/files/1257461", "https://ndownloader.figshare.com/files/1257462"], "description"=>"<div><p>We introduce a flexible and robust simulation-based framework to infer demographic parameters from the site frequency spectrum (SFS) computed on large genomic datasets. We show that our composite-likelihood approach allows one to study evolutionary models of arbitrary complexity, which cannot be tackled by other current likelihood-based methods. For simple scenarios, our approach compares favorably in terms of accuracy and speed with , the current reference in the field, while showing better convergence properties for complex models. We first apply our methodology to non-coding genomic SNP data from four human populations. To infer their demographic history, we compare neutral evolutionary models of increasing complexity, including unsampled populations. We further show the versatility of our framework by extending it to the inference of demographic parameters from SNP chips with known ascertainment, such as that recently released by Affymetrix to study human origins. Whereas previous ways of handling ascertained SNPs were either restricted to a single population or only allowed the inference of divergence time between a pair of populations, our framework can correctly infer parameters of more complex models including the divergence of several populations, bottlenecks and migration. We apply this approach to the reconstruction of African demography using two distinct ascertained human SNP panels studied under two evolutionary models. The two SNP panels lead to globally very similar estimates and confidence intervals, and suggest an ancient divergence (>110 Ky) between Yoruba and San populations. Our methodology appears well suited to the study of complex scenarios from large genomic data sets.</p></div>", "links"=>[], "tags"=>["inference", "genomic", "snp"], "article_id"=>831971, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1003905.s001", "https://dx.doi.org/10.1371/journal.pgen.1003905.s002", "https://dx.doi.org/10.1371/journal.pgen.1003905.s003", "https://dx.doi.org/10.1371/journal.pgen.1003905.s004", "https://dx.doi.org/10.1371/journal.pgen.1003905.s005", "https://dx.doi.org/10.1371/journal.pgen.1003905.s006", "https://dx.doi.org/10.1371/journal.pgen.1003905.s007", "https://dx.doi.org/10.1371/journal.pgen.1003905.s008", "https://dx.doi.org/10.1371/journal.pgen.1003905.s009", "https://dx.doi.org/10.1371/journal.pgen.1003905.s010", "https://dx.doi.org/10.1371/journal.pgen.1003905.s011", "https://dx.doi.org/10.1371/journal.pgen.1003905.s012", "https://dx.doi.org/10.1371/journal.pgen.1003905.s013", "https://dx.doi.org/10.1371/journal.pgen.1003905.s014", "https://dx.doi.org/10.1371/journal.pgen.1003905.s015", "https://dx.doi.org/10.1371/journal.pgen.1003905.s016", "https://dx.doi.org/10.1371/journal.pgen.1003905.s017", "https://dx.doi.org/10.1371/journal.pgen.1003905.s018", "https://dx.doi.org/10.1371/journal.pgen.1003905.s019", "https://dx.doi.org/10.1371/journal.pgen.1003905.s020"], "stats"=>{"downloads"=>99, "page_views"=>28, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Robust_Demographic_Inference_from_Genomic_and_SNP_Data_/831971", "title"=>"Robust Demographic Inference from Genomic and SNP Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-10-24 03:19:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1257431"], "description"=>"a<p>Parametric bootstrap estimates obtained by parameter estimation from data sets simulated according to CML estimates shown in the point estimation column.</p>b<p>Bottleneck intensity is equal to bottleneck duration (100 generations) divided by the bottleneck population size (N<sub>BEUR</sub> or N<sub>BNC</sub>).</p><p>Conditions for <i>fastsimcoal2</i> point estimations were: 50–250,000 simulations per likelihood estimation (-n50000, -N250000), 30 ECM cycles (-L30), 50 runs per data set. Conditions for <i>fastsimcoal2</i> CI estimations were: 100,000 simulations per likelihood estimation (-N100000), 30 ECM cycles (-L30), 10 runs per data set.</p>", "links"=>[], "tags"=>["demography", "b1", "b2", "defined"], "article_id"=>831964, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1003905.t001", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inferred_parameters_of_human_demography_under_model_B1_and_B2_defined_in_Figure_4B_/831964", "title"=>"Inferred parameters of human demography under model B1 and B2 defined in Figure 4B.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-24 03:19:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1257428"], "description"=>"<p>A: Simple model of African American (ASW) admixture supposed to have occurred 16 generations ago, with contributions from 3 potential sources (Europeans : CEU; Yoruba: YRI; Luhya: LWK. The European population is assumed to have diverged 2000 generations ago (50 Kya, <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003905#pgen.1003905-Gravel1\" target=\"_blank\">[28]</a>) from Africa. B1: More realistic demographic scenario (dark grey) of African American admixture and population differentiation, based on continent-island models used to depict spatially arranged populations after range expansions <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003905#pgen.1003905-Excoffier2\" target=\"_blank\">[see e.g. 47]</a>. B2: same as B1 but with an additional possible admixture of Luhya from an unsampled (possibly East African) population. The extra parameters and population of model B2 are shown with a lighter shade of gray and with dashed arrows, respectively. The models and their parameters are further described in the Material and Methods section.</p>", "links"=>[], "tags"=>[], "article_id"=>831961, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1003905.g004", "stats"=>{"downloads"=>1, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_models_of_four_human_populations_/831961", "title"=>"Demographic models of four human populations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-24 03:19:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1257426"], "description"=>"<p><i>fastsimcoal2</i> results are in black and 's results (8/10) are in blue. True parameters values are shown as red dots. <i>fastsimcoal2</i> required 4–5 h for a single estimation based on 40 ECM cycles over parameters, whereas a run of requires on average 34 hours on a similar CPU.</p>", "links"=>[], "tags"=>["divergence"], "article_id"=>831959, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1003905.g002", "stats"=>{"downloads"=>2, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Three_population_divergence_and_growth_model_/831959", "title"=>"Three population divergence and growth model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-24 03:19:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1257427"], "description"=>"<p>Boxplots showing the distribution parameters estimated from 10 data sets simulated under the same scenario. True parameter values are shown as red dots. <i>fastsimcoal2</i> required 35–40 hours for a single estimation based on 30 ECM cycles over parameters, using 50 thousand simulations to estimate the expected SFS under a given set of parameters.</p>", "links"=>[], "tags"=>["islands"], "article_id"=>831960, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1003905.g003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hierarchical_islands_model_/831960", "title"=>"Hierarchical islands model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-24 03:19:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1257425"], "description"=>"<p>A) One population with bottleneck B) Isolation of two populations with asymmetric migration C) Three population divergence with migration and bottleneck. This model corresponds roughly to a model of human differentiation, where N<sub>1</sub> would be the size of an African population, and T<sub>DIV</sub> would correspond to the exit of a population diverging into Asian and European populations growing exponentially and still exchanging migrants at rate m. We assume that the current size of the expanding population is known and equal to 1 million diploids. D) Divergence of two continent-islands. We assume that two Continent-Island systems were created <i>T</i><sub>CI1</sub> and <i>T</i><sub>CI2</sub> generations ago, with the youngest continent stemming from one of the island of Continent 2. The parameters of interest are the per generation number of migrant genes (<i>M</i> = 2<i>Nm</i>) from each continent to each island, the age of the continents and the ancestral population size <i>N</i><sub>A</sub>. The island population sizes were set to 500 diploids and <i>M</i> changed due to immigration rates <i>m</i> that could differ for each island.</p>", "links"=>[], "tags"=>[], "article_id"=>831958, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Laurent Excoffier", "Isabelle Dupanloup", "Emilia Huerta-Sanchez", "Vitor C. Sousa", "Matthieu Foll"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1003905.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Tested_demographic_models_/831958", "title"=>"Tested demographic models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-24 03:19:01"}

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Relative Metric

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