Inferring genome-wide patterns of admixture in Qataris using fifty-five ancestral populations.
Larsson Omberg,Jacqueline Salit,Neil R. Hackett,Jennifer Fuller,Rebecca Matthew,Lotfi Chouchane,Juan L. Rodriguez-Flores,Carlos Bustamante,Ronald G. Crystal,Jason G. Mezey +9 more
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Simulations show that SupportMix is not only more accurate than other popular admixture discovery tools but is the first admixture inference method that can efficiently scale for simultaneous analysis of 50-100 putative ancestral populations while being independent of prior demographic information.Abstract:
Populations of the Arabian Peninsula have a complex genetic structure that reflects waves of migrations including the earliest human migrations from Africa and eastern Asia, migrations along ancient civilization trading routes and colonization history of recent centuries. Here, we present a study of genome-wide admixture in this region, using 156 genotyped individuals from Qatar, a country located at the crossroads of these migration patterns. Since haplotypes of these individuals could have originated from many different populations across the world, we have developed a machine learning method "SupportMix" to infer loci-specific genomic ancestry when simultaneously analyzing many possible ancestral populations. Simulations show that SupportMix is not only more accurate than other popular admixture discovery tools but is the first admixture inference method that can efficiently scale for simultaneous analysis of 50-100 putative ancestral populations while being independent of prior demographic information. By simultaneously using the 55 world populations from the Human Genome Diversity Panel, SupportMix was able to extract the fine-scale ancestry of the Qatar population, providing many new observations concerning the ancestry of the region. For example, as well as recapitulating the three major sub-populations in Qatar, composed of mainly Arabic, Persian, and African ancestry, SupportMix additionally identifies the specific ancestry of the Persian group to populations sampled in Greater Persia rather than from China and the ancestry of the African group to sub-Saharan origin and not Southern African Bantu origin as previously thought.read more
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RFMix: a discriminative modeling approach for rapid and robust local-ancestry inference.
TL;DR: RFMix, a powerful discriminative modeling approach that is faster and more accurate than existing methods and capable of learning from the admixed samples themselves to boost performance and autocorrect phasing errors, is presented.
Journal ArticleDOI
Evaluating the Use of ABBA–BABA Statistics to Locate Introgressed Loci
TL;DR: It is found that D is unreliable in this situation as it gives inflated values when effective population size is low, causing D outliers to cluster in genomic regions of reduced diversity, and a related statistic f^d is proposed, a modified version of a statistic originally developed to estimate the genome-wide fraction of admixture.
Journal ArticleDOI
Barley landraces are characterized by geographically heterogeneous genomic origins
TL;DR: The findings indicate that cultivated barley is comprised of multiple source populations with unequal contributions traceable across the genome, which increases the understanding of the evolutionary process associated with the transition from wild to domesticated barley.
Posted Content
Recommended MBE section: Methods Evaluating the use of ABBA-BABA statistics to locate introgressed loci
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Ancestry Composition: A Novel, Efficient Pipeline for Ancestry Deconvolution
TL;DR: Ancestry Composition is described, a modular three-stage pipeline that efficiently and accurately identifies the ancestral origin of chromosomal segments in admixed individuals and achieves high precision and recall for labeling chromosomesomal segments across over 25 different populations worldwide.
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Hsu Chih-Wei,Chih-Jen Lin +1 more
TL;DR: Decomposition implementations for two "all-together" multiclass SVM methods are given and it is shown that for large problems methods by considering all data at once in general need fewer support vectors.
Journal ArticleDOI
A second generation human haplotype map of over 3.1 million SNPs
Kelly A. Frazer,Dennis G. Ballinger,David R. Cox,David A. Hinds,Laura L. Stuve,Richard A. Gibbs,John W. Belmont,Andrew Boudreau,Paul Hardenbol,Suzanne M. Leal,Shiran Pasternak,David A. Wheeler,Thomas D. Willis,Fuli Yu,Huanming Yang,Changqing Zeng,Gao Yang,H. B. Hu,Weitao Hu,Chaohua Li,Wei Lin,Siqi Liu,Hao Pan,Xiaoli Tang,Jian Wang,Wei Wang,Jun Yu,Bo Zhang,Qingrun Zhang,Hongbin Zhao,Hui Zhao,Jun Zhou,Stacey Gabriel,Rachel Barry,Brendan Blumenstiel,Amy L. Camargo,Matthew Defelice,Maura Faggart,Mary Goyette,Supriya Gupta,Jamie Moore,Huy Nguyen,Robert C. Onofrio,Melissa Parkin,Jessica Roy,Erich Stahl,Ellen Winchester,Liuda Ziaugra,David Altshuler,Yan Shen,Zhijian Yao,Wei Huang,Xun Chu,Yungang He,Li Jin,Yangfan Liu,Yayun Shen,Weiwei Sun,Haifeng Wang,Yi Wang,Ying Wang,Xiaoyan Xiong,Liang Xu,Mary M.Y. Waye,Stephen Kwok-Wing Tsui,Hong Xue,J. Tze Fei Wong,Luana Galver,Jian-Bing Fan,Kevin L. Gunderson,Sarah S. Murray,Arnold Oliphant,Mark S. Chee,Alexandre Montpetit,Fanny Chagnon,Vincent Ferretti,Martin Leboeuf,Jean François Olivier,Michael S. Phillips,Stéphanie Roumy,Clémentine Sallée,Andrei Verner,Thomas J. Hudson,Pui-Yan Kwok,Dongmei Cai,Daniel C. Koboldt,Raymond D. Miller,Ludmila Pawlikowska,Patricia Taillon-Miller,Ming Xiao,Lap-Chee Tsui,William Mak,Qiang Song You,Paul K.H. Tam,Yusuke Nakamura,Takahisa Kawaguchi,Takuya Kitamoto,Takashi Morizono,Atsushi Nagashima,Yozo Ohnishi,Akihiro Sekine,Toshihiro Tanaka,Tatsuhiko Tsunoda,Panos Deloukas,Christine P. Bird,Marcos Delgado,Emmanouil T. Dermitzakis,Rhian Gwilliam,Sarah E. Hunt,Jonathan J. Morrison,Don Powell,Barbara E. Stranger,Pamela Whittaker,David R. Bentley,Mark J. Daly,Paul I.W. de Bakker,Jeffrey C. Barrett,Yves Chretien,Julian Maller,Steve McCarroll,Nick Patterson,Itsik Pe'er,Alkes L. Price,Shaun Purcell,Daniel J. Richter,Pardis C. Sabeti,Richa Saxena,Stephen F. Schaffner,Pak C. Sham,Patrick Varilly,Lincoln Stein,Lalitha Krishnan,Albert V. Smith,Marcela K. Tello-Ruiz,Gudmundur A. Thorisson,Aravinda Chakravarti,Peter E. Chen,David J. Cutler,Carl S. Kashuk,Shin Lin,Gonçalo R. Abecasis,Weihua Guan,Yun Li,Heather M. Munro,Zhaohui S. Qin,Daryl J. Thomas,Gilean McVean,Adam Auton,Leonardo Bottolo,Niall Cardin,Susana Eyheramendy,Colin Freeman,Jonathan Marchini,Simon Myers,Chris C. A. Spencer,Matthew Stephens,Peter Donnelly,Lon R. Cardon,Geraldine M. Clarke,David M. Evans,Andrew P. Morris,Bruce S. Weir,Todd A. Johnson,James C. Mullikin,Stephen T. Sherry,Michael Feolo,Andrew D. Skol,Houcan Zhang,Ichiro Matsuda,Yoshimitsu Fukushima,Darryl Macer,Eiko Suda,Charles N. Rotimi,Clement Adebamowo,Ike Ajayi,Toyin Aniagwu,Patricia A. Marshall,Chibuzor Nkwodimmah,Charmaine D.M. Royal,Mark Leppert,Missy Dixon,Andy Peiffer,Renzong Qiu,Alastair Kent,Kazuto Kato,Norio Niikawa,Isaac F. Adewole,Bartha Maria Knoppers,Morris W. Foster,Ellen Wright Clayton,Jessica Watkin,Donna M. Muzny,Lynne V. Nazareth,Erica Sodergren,George M. Weinstock,Imtaz Yakub,Bruce W. Birren,Richard K. Wilson,Lucinda Fulton,Jane Rogers,John Burton,Nigel P. Carter,C M Clee,Mark Griffiths,Matthew C. Jones,Kirsten McLay,Robert W. Plumb,Mark T. Ross,Sarah Sims,David Willey,Zhu Chen,Hua Han,Le Kang,Martin Godbout,John C. Wallenburg,Paul L'Archevêque,Guy Bellemare,Koji Saeki,Hongguang Wang,Daochang An,Hongbo Fu,Qing Li,Zhen Wang,Renwu Wang,Arthur L. Holden,Lisa D. Brooks,Jean E. McEwen,Mark S. Guyer,Vivian Ota Wang,Jane Peterson,Michael Shi,Jack Spiegel,Lawrence M. Sung,Lynn F. Zacharia,Francis S. Collins,Karen Kennedy,Ruth Jamieson,John Stewart +237 more
TL;DR: The Phase II HapMap is described, which characterizes over 3.1 million human single nucleotide polymorphisms genotyped in 270 individuals from four geographically diverse populations and includes 25–35% of common SNP variation in the populations surveyed, and increased differentiation at non-synonymous, compared to synonymous, SNPs is demonstrated.