Distinguishing between selective sweeps from standing variation and from a de novo mutation.

An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminat...
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Autor*in:	Benjamin M Peter [verfasserIn] Emilia Huerta-Sanchez [verfasserIn] Rasmus Nielsen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2012

Übergeordnetes Werk:	In: PLoS Genetics - Public Library of Science (PLoS), 2005, 8(2012), 10, p e1003011
Übergeordnetes Werk:	volume:8 ; year:2012 ; number:10, p e1003011

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1371/journal.pgen.1003011

Katalog-ID:	DOAJ015975339

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allfields	10.1371/journal.pgen.1003011 doi (DE-627)DOAJ015975339 (DE-599)DOAJ40024da6128b4aaf8a77a605246f1bb8 DE-627 ger DE-627 rakwb eng QH426-470 Benjamin M Peter verfasserin aut Distinguishing between selective sweeps from standing variation and from a de novo mutation. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection. Genetics Emilia Huerta-Sanchez verfasserin aut Rasmus Nielsen verfasserin aut In PLoS Genetics Public Library of Science (PLoS), 2005 8(2012), 10, p e1003011 (DE-627)485248026 (DE-600)2186725-2 15537404 nnns volume:8 year:2012 number:10, p e1003011 https://doi.org/10.1371/journal.pgen.1003011 kostenfrei https://doaj.org/article/40024da6128b4aaf8a77a605246f1bb8 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23071458/pdf/?tool=EBI kostenfrei https://doaj.org/toc/1553-7390 Journal toc kostenfrei https://doaj.org/toc/1553-7404 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2012 10, p e1003011
spelling	10.1371/journal.pgen.1003011 doi (DE-627)DOAJ015975339 (DE-599)DOAJ40024da6128b4aaf8a77a605246f1bb8 DE-627 ger DE-627 rakwb eng QH426-470 Benjamin M Peter verfasserin aut Distinguishing between selective sweeps from standing variation and from a de novo mutation. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection. Genetics Emilia Huerta-Sanchez verfasserin aut Rasmus Nielsen verfasserin aut In PLoS Genetics Public Library of Science (PLoS), 2005 8(2012), 10, p e1003011 (DE-627)485248026 (DE-600)2186725-2 15537404 nnns volume:8 year:2012 number:10, p e1003011 https://doi.org/10.1371/journal.pgen.1003011 kostenfrei https://doaj.org/article/40024da6128b4aaf8a77a605246f1bb8 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23071458/pdf/?tool=EBI kostenfrei https://doaj.org/toc/1553-7390 Journal toc kostenfrei https://doaj.org/toc/1553-7404 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2012 10, p e1003011
allfields_unstemmed	10.1371/journal.pgen.1003011 doi (DE-627)DOAJ015975339 (DE-599)DOAJ40024da6128b4aaf8a77a605246f1bb8 DE-627 ger DE-627 rakwb eng QH426-470 Benjamin M Peter verfasserin aut Distinguishing between selective sweeps from standing variation and from a de novo mutation. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection. Genetics Emilia Huerta-Sanchez verfasserin aut Rasmus Nielsen verfasserin aut In PLoS Genetics Public Library of Science (PLoS), 2005 8(2012), 10, p e1003011 (DE-627)485248026 (DE-600)2186725-2 15537404 nnns volume:8 year:2012 number:10, p e1003011 https://doi.org/10.1371/journal.pgen.1003011 kostenfrei https://doaj.org/article/40024da6128b4aaf8a77a605246f1bb8 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23071458/pdf/?tool=EBI kostenfrei https://doaj.org/toc/1553-7390 Journal toc kostenfrei https://doaj.org/toc/1553-7404 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2012 10, p e1003011
allfieldsGer	10.1371/journal.pgen.1003011 doi (DE-627)DOAJ015975339 (DE-599)DOAJ40024da6128b4aaf8a77a605246f1bb8 DE-627 ger DE-627 rakwb eng QH426-470 Benjamin M Peter verfasserin aut Distinguishing between selective sweeps from standing variation and from a de novo mutation. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection. Genetics Emilia Huerta-Sanchez verfasserin aut Rasmus Nielsen verfasserin aut In PLoS Genetics Public Library of Science (PLoS), 2005 8(2012), 10, p e1003011 (DE-627)485248026 (DE-600)2186725-2 15537404 nnns volume:8 year:2012 number:10, p e1003011 https://doi.org/10.1371/journal.pgen.1003011 kostenfrei https://doaj.org/article/40024da6128b4aaf8a77a605246f1bb8 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23071458/pdf/?tool=EBI kostenfrei https://doaj.org/toc/1553-7390 Journal toc kostenfrei https://doaj.org/toc/1553-7404 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2012 10, p e1003011
allfieldsSound	10.1371/journal.pgen.1003011 doi (DE-627)DOAJ015975339 (DE-599)DOAJ40024da6128b4aaf8a77a605246f1bb8 DE-627 ger DE-627 rakwb eng QH426-470 Benjamin M Peter verfasserin aut Distinguishing between selective sweeps from standing variation and from a de novo mutation. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection. Genetics Emilia Huerta-Sanchez verfasserin aut Rasmus Nielsen verfasserin aut In PLoS Genetics Public Library of Science (PLoS), 2005 8(2012), 10, p e1003011 (DE-627)485248026 (DE-600)2186725-2 15537404 nnns volume:8 year:2012 number:10, p e1003011 https://doi.org/10.1371/journal.pgen.1003011 kostenfrei https://doaj.org/article/40024da6128b4aaf8a77a605246f1bb8 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23071458/pdf/?tool=EBI kostenfrei https://doaj.org/toc/1553-7390 Journal toc kostenfrei https://doaj.org/toc/1553-7404 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2012 10, p e1003011
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author	Benjamin M Peter
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topic_title	QH426-470 Distinguishing between selective sweeps from standing variation and from a de novo mutation
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title	Distinguishing between selective sweeps from standing variation and from a de novo mutation.
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title_full	Distinguishing between selective sweeps from standing variation and from a de novo mutation
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title_sort	distinguishing between selective sweeps from standing variation and from a de novo mutation
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title_auth	Distinguishing between selective sweeps from standing variation and from a de novo mutation.
abstract	An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection.
abstractGer	An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection.
abstract_unstemmed	An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection.
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title_short	Distinguishing between selective sweeps from standing variation and from a de novo mutation.
url	https://doi.org/10.1371/journal.pgen.1003011 https://doaj.org/article/40024da6128b4aaf8a77a605246f1bb8 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23071458/pdf/?tool=EBI https://doaj.org/toc/1553-7390 https://doaj.org/toc/1553-7404
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Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. 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Distinguishing between selective sweeps from standing variation and from a de novo mutation.

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