The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

doi:10.1038/nature18964

. 2016 Oct 13;538(7624):201-206.

doi: 10.1038/nature18964. Epub 2016 Sep 21.

The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

Swapan Mallick^{1

2

3}, Heng Li², Mark Lipson¹, Iain Mathieson¹, Melissa Gymrek^{2

4

5

6}, Fernando Racimo⁷, Mengyao Zhao^{1

2

3}, Niru Chennagiri^{1

2

3}, Susanne Nordenfelt^{1

2

3}, Arti Tandon^{1

2}, Pontus Skoglund^{1

2}, Iosif Lazaridis^{1

2}, Sriram Sankararaman^{1

2}, Qiaomei Fu^{1

2

8}, Nadin Rohland^{1

2}, Gabriel Renaud⁹, Yaniv Erlich^{6

10

11}, Thomas Willems^{6

12}, Carla Gallo¹³, Jeffrey P Spence¹⁴, Yun S Song^{15

16

17}, Giovanni Poletti¹³, Francois Balloux¹⁸, George van Driem¹⁹, Peter de Knijff²⁰, Irene Gallego Romero^{21

22}, Aashish R Jha²³, Doron M Behar²⁴, Claudio M Bravi²⁵, Cristian Capelli²⁶, Tor Hervig²⁷, Andres Moreno-Estrada²⁸, Olga L Posukh^{29

30}, Elena Balanovska³¹, Oleg Balanovsky^{31

32

33}, Sena Karachanak-Yankova³⁴, Hovhannes Sahakyan^{24

35}, Draga Toncheva³⁴, Levon Yepiskoposyan³⁵, Chris Tyler-Smith³⁶, Yali Xue³⁶, M Syafiq Abdullah³⁷, Andres Ruiz-Linares³⁸, Cynthia M Beall³⁹, Anna Di Rienzo²³, Choongwon Jeong²³, Elena B Starikovskaya⁴⁰, Ene Metspalu^{24

41}, Jüri Parik²⁴, Richard Villems^{24

41

42}, Brenna M Henn⁴³, Ugur Hodoglugil⁴⁴, Robert Mahley⁴⁵, Antti Sajantila⁴⁶, George Stamatoyannopoulos⁴⁷, Joseph T S Wee⁴⁸, Rita Khusainova^{49

50}, Elza Khusnutdinova^{49

50}, Sergey Litvinov^{24

49

50}, George Ayodo⁵¹, David Comas⁵², Michael F Hammer⁵³, Toomas Kivisild^{24

54}, William Klitz⁶, Cheryl A Winkler⁵⁵, Damian Labuda⁵⁶, Michael Bamshad⁵⁷, Lynn B Jorde⁵⁸, Sarah A Tishkoff⁵⁹, W Scott Watkins⁶⁰, Mait Metspalu²⁴, Stanislav Dryomov^{40

61}, Rem Sukernik^{40

62}, Lalji Singh⁶³, Kumarasamy Thangaraj⁶³, Svante Pääbo⁹, Janet Kelso⁹, Nick Patterson², David Reich^{1

2

3}

Affiliations

¹ Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA.
² Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.
³ Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA.
⁴ Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142, USA.
⁵ Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts 02139, USA.
⁶ New York Genome Center, New York, New York 10013, USA.
⁷ Department of Integrative Biology, University of California, Berkeley, California 94720-3140, USA.
⁸ Key Laboratory of Vertebrate Evolution and Human Origins of Chinese Academy of Sciences, IVPP, CAS, Beijing 100044, China.
⁹ Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.
¹⁰ Department of Computer Science, Columbia University, New York, New York 10027, USA.
¹¹ Center for Computational Biology and Bioinformatics, Columbia University, New York, New York 10032, USA.
¹² Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
¹³ Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Perú.
¹⁴ Computational Biology Graduate Group, University of California, Berkeley, California 94720, USA.
¹⁵ Computer Science Division, University of California, Berkeley, California 94720, USA.
¹⁶ Department of Statistics, University of California, Berkeley, California 94720, USA.
¹⁷ Department of Mathematics and Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
¹⁸ Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK.
¹⁹ Institute of Linguistics, University of Bern, Bern CH-3012, Switzerland.
²⁰ Department of Human and Clinical Genetics, Postzone S5-P, Leiden University Medical Center, 2333 ZA Leiden, Netherlands.
²¹ School of Biological Sciences, Nanyang Technological University, 637551 Singapore.
²² Lee Kong Chian School of Medicine, Nanyang Technological University, 636921 Singapore.
²³ Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA.
²⁴ Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia.
²⁵ Laboratorio de Genética Molecular Poblacional, Instituto Multidisciplinario de Biología Celular (IMBICE), CCT-CONICET La Plata/CIC Buenos Aires/Universidad Nacional de La Plata, La Plata B1906APO, Argentina.
²⁶ Department of Zoology, University of Oxford, Oxford OX1 3PS, UK.
²⁷ Department of Clinical Science, University of Bergen, Bergen 5021, Norway.
²⁸ National Laboratory of Genomics for Biodiversity (LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, Mexico.
²⁹ Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
³⁰ Novosibirsk State University, Novosibirsk 630090, Russia.
³¹ Research Centre for Medical Genetics, Moscow 115478, Russia.
³² Vavilov Institute for General Genetics, Moscow 119991, Russia.
³³ Moscow Institute for Physics and Technology, Dolgoprudniy 141700, Russia.
³⁴ Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria.
³⁵ Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia.
³⁶ The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK.
³⁷ RIPAS Hospital, Bandar Seri Begawan, Brunei.
³⁸ Department of Genetics, Evolution and Environment, University College London WC1E 6BT, UK.
³⁹ Department of Anthropology, Case Western Reserve University, Cleveland, Ohio 44106-7125, USA.
⁴⁰ Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
⁴¹ Department of Evolutionary Biology, University of Tartu, Tartu 51010, Estonia.
⁴² Estonian Academy of Sciences, Tallinn 10130, Estonia.
⁴³ Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York 11794, USA.
⁴⁴ NextBio, Illumina, Santa Clara, California 95050, USA.
⁴⁵ Gladstone Institutes, San Francisco, California 94158, USA.
⁴⁶ Department of Forensic Medicine, University of Helsinki, Helsinki 00014, Finland.
⁴⁷ Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, Washington 98195, USA.
⁴⁸ National Cancer Centre Singapore, 169610 Singapore.
⁴⁹ Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia.
⁵⁰ Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia.
⁵¹ Jaramogi Oginga Odinga University of Science and Technology, Bondo 40601, Kenya.
⁵² Institut de Biologia Evolutiva (CSIC-UPF), Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona 08003, Spain.
⁵³ ARL Division of Biotechnology, University of Arizona, Tucson, Arizona 85721, USA.
⁵⁴ Division of Biological Anthropology, University of Cambridge, Fitzwilliam Street, Cambridge CB2 1QH, UK.
⁵⁵ Basic Research Laboratory, Center for Cancer Research, NCI, Leidos Biomedical Research, Inc., Frederick National Laboratory, Frederick, Maryland 21702, USA.
⁵⁶ CHU Sainte-Justine, Pediatrics Departement, Université de Montréal, Québec H3T 1C5, Canada.
⁵⁷ Department of Pediatrics, University of Washington, Seattle, Washington 98119, USA.
⁵⁸ Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah 84112, USA.
⁵⁹ Departments of Genetics and Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
⁶⁰ Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA.
⁶¹ Department of Paleolithic Archaeology, Institute of Archaeology and Ethnography, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
⁶² Altai State University, Barnaul 656000, Russia.
⁶³ CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500 007, India.

PMID: 27654912
PMCID: PMC5161557
DOI: 10.1038/nature18964

Free PMC article

The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

Swapan Mallick et al. Nature. 2016.

Free PMC article

. 2016 Oct 13;538(7624):201-206.

doi: 10.1038/nature18964. Epub 2016 Sep 21.

Authors

Affiliations

¹ Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA.
² Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.
³ Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA.
⁴ Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142, USA.
⁵ Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts 02139, USA.
⁶ New York Genome Center, New York, New York 10013, USA.
⁷ Department of Integrative Biology, University of California, Berkeley, California 94720-3140, USA.
⁸ Key Laboratory of Vertebrate Evolution and Human Origins of Chinese Academy of Sciences, IVPP, CAS, Beijing 100044, China.
⁹ Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.
¹⁰ Department of Computer Science, Columbia University, New York, New York 10027, USA.
¹¹ Center for Computational Biology and Bioinformatics, Columbia University, New York, New York 10032, USA.
¹² Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
¹³ Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Perú.
¹⁴ Computational Biology Graduate Group, University of California, Berkeley, California 94720, USA.
¹⁵ Computer Science Division, University of California, Berkeley, California 94720, USA.
¹⁶ Department of Statistics, University of California, Berkeley, California 94720, USA.
¹⁷ Department of Mathematics and Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
¹⁸ Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK.
¹⁹ Institute of Linguistics, University of Bern, Bern CH-3012, Switzerland.
²⁰ Department of Human and Clinical Genetics, Postzone S5-P, Leiden University Medical Center, 2333 ZA Leiden, Netherlands.
²¹ School of Biological Sciences, Nanyang Technological University, 637551 Singapore.
²² Lee Kong Chian School of Medicine, Nanyang Technological University, 636921 Singapore.
²³ Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA.
²⁴ Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia.
²⁵ Laboratorio de Genética Molecular Poblacional, Instituto Multidisciplinario de Biología Celular (IMBICE), CCT-CONICET La Plata/CIC Buenos Aires/Universidad Nacional de La Plata, La Plata B1906APO, Argentina.
²⁶ Department of Zoology, University of Oxford, Oxford OX1 3PS, UK.
²⁷ Department of Clinical Science, University of Bergen, Bergen 5021, Norway.
²⁸ National Laboratory of Genomics for Biodiversity (LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, Mexico.
²⁹ Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
³⁰ Novosibirsk State University, Novosibirsk 630090, Russia.
³¹ Research Centre for Medical Genetics, Moscow 115478, Russia.
³² Vavilov Institute for General Genetics, Moscow 119991, Russia.
³³ Moscow Institute for Physics and Technology, Dolgoprudniy 141700, Russia.
³⁴ Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria.
³⁵ Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia.
³⁶ The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK.
³⁷ RIPAS Hospital, Bandar Seri Begawan, Brunei.
³⁸ Department of Genetics, Evolution and Environment, University College London WC1E 6BT, UK.
³⁹ Department of Anthropology, Case Western Reserve University, Cleveland, Ohio 44106-7125, USA.
⁴⁰ Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
⁴¹ Department of Evolutionary Biology, University of Tartu, Tartu 51010, Estonia.
⁴² Estonian Academy of Sciences, Tallinn 10130, Estonia.
⁴³ Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York 11794, USA.
⁴⁴ NextBio, Illumina, Santa Clara, California 95050, USA.
⁴⁵ Gladstone Institutes, San Francisco, California 94158, USA.
⁴⁶ Department of Forensic Medicine, University of Helsinki, Helsinki 00014, Finland.
⁴⁷ Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, Washington 98195, USA.
⁴⁸ National Cancer Centre Singapore, 169610 Singapore.
⁴⁹ Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia.
⁵⁰ Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia.
⁵¹ Jaramogi Oginga Odinga University of Science and Technology, Bondo 40601, Kenya.
⁵² Institut de Biologia Evolutiva (CSIC-UPF), Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona 08003, Spain.
⁵³ ARL Division of Biotechnology, University of Arizona, Tucson, Arizona 85721, USA.
⁵⁴ Division of Biological Anthropology, University of Cambridge, Fitzwilliam Street, Cambridge CB2 1QH, UK.
⁵⁵ Basic Research Laboratory, Center for Cancer Research, NCI, Leidos Biomedical Research, Inc., Frederick National Laboratory, Frederick, Maryland 21702, USA.
⁵⁶ CHU Sainte-Justine, Pediatrics Departement, Université de Montréal, Québec H3T 1C5, Canada.
⁵⁷ Department of Pediatrics, University of Washington, Seattle, Washington 98119, USA.
⁵⁸ Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah 84112, USA.
⁵⁹ Departments of Genetics and Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
⁶⁰ Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA.
⁶¹ Department of Paleolithic Archaeology, Institute of Archaeology and Ethnography, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
⁶² Altai State University, Barnaul 656000, Russia.
⁶³ CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500 007, India.

PMID: 27654912
PMCID: PMC5161557
DOI: 10.1038/nature18964

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Abstract

Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.

Figures

Extended Data Figure 1. Heatmap of fraction of heterozygous sites missed in the 1000 Genomes Project

For each sample, we examine all heterozygous sites passing filter level 1, and compute the fraction included as known polymorphisms in the 1000 Genomes Project.

Extended Data Figure 2. Worldwide variation in human short tandem repeats

A: Mean STR length is reported as the average of the length difference (in base pairs) from the GRCh37 reference for each genotype. Bubble area scales with the number of calls compared at each point. B: and C: show the first two principal components after performing principal component analysis on tetranucleotide and homopolymer genotypes, respectively. Colors represent the region of origin of each sample. D: Pairwise F_ST values between populations computed using only SNPs vs. using combined SNP+STR loci. E: Block jackknife standard errors for the SNP vs. SNP+STR F_ST analysis. The red dashed lines give the best-fit line, described by the formula in red. The black dashed line denotes the diagonal.

Extended Data Figure 3. ADMIXTURE analysis

We carried out unsupervised ADMIXTURE 1.23^, analysis over the 300 SGDP individuals in 20 replicates with randomly chosen initial seeds, varying the number of ancestral populations between K=2 and K=12 and using default 5-fold cross-validation (--cv flag). We used genotypes of at least filter level 1, and restricted analysis to sites where at least two individuals carried the variant allele (as singleton variants are non-informative for population clustering). After further filtering sites with at least 99% completeness and performing linkage-disequilibrium based pruning in PLINK 1.9^, with parameters (--indep-pairwise 1000 100 0.2), a total of 482,515 single nucleotide polymorphisms remained. This figure shows the highest likelihood replicate for each value of K. We found that log likelihood monotonically increases with K, while the value K=5 minimizes cross-validation error (not shown). The solution at K=5 corresponds to major continental groups (Sub-Saharan Africans, Oceanians, East Asians, Native Americans, and West Eurasians), but we show the full range of K here as they illustrate finer-scale population structure that may be useful to users of the data.

Extended Data Figure 4. Principal component analysis and neighbor joining tree

A: Principal component analysis. B: Neighbor-joining tree based on F_ST values for all populations with at least two samples.

Extended Data Figure 5. Fewer accumulated mutations in Africans than in non-Africans confirmed by mapping to chimpanzee

We compute a statistic D(Population A, Population B, Chimp), measuring the difference in the rate of matching to chimpanzee in Population A compared to Population B. The evidence of mismatching to chimpanzee is seen when we restrict to the male X chromosome to eliminate possible effects due to differences in heterozygosity across populations, and map to the chimpanzee genome which is phylogenetically symmetrically related to all present-day humans. We find that in 78 randomly chosen Population A = African and Population B = non-African pairs of males, transversion substitutions show no consistent skew from zero, but transition substitutions do.

Extended Data Figure 6. 3P-CLR scan for positive selection

The red line denotes the 99.9% quantile cutoff. The genes in the top 5 regions are labeled. A: Scan for selection on the San terminal branch. B: Scan for selection on the non-San terminal branch. C: Scan for selection on the ancestral modern human branch.

Extended Data Figure 7. Scan for genomic locations where the great majority of present-day humans share a recent common ancestor

We carried out PSMC analysis on 40 pairs of haploid genomes chosen to sample some of the most deeply divergent present-day human lineages. We recorded the time since the most recent common ancestor (TMRCA) at each position, and rescaled to obtain an estimate of absolute time (Supplementary Information section 12). A: Distribution across the genome of the fraction of TMRCAs below specified date cutoffs. For the 100 kya cutoff, the maximum fraction observed anywhere in the genome is 68%. B: Distribution across the genome of the date T at which specified fractions of sample pairs are inferred to have a TMRCA less than T. C: Percentile points of the cumulative distribution function of B.

Figure 1. Genetic variation in the SGDP

A: Neighbor-joining tree of relationships based on pairwise divergence. B: Plot of autosomal heterozygosity against the X-to-autosome heterozygosity ratio, showing the reduction in this ratio in non-Africans and Pygmies. C: Estimate of Neanderthal ancestry with a heatmap scale of 0–3%. D: Estimate of Denisovan ancestry with a heatmap scale of 0–0.5% to bring out subtle differences in mainland Eurasia (Oceanian groups with as much as 5% Denisovan ancestry are saturated in bright red).

Figure 2. Cross-coalescence rates and effective population sizes for selected population pairs

A–C: Cross-coalescence rates as a function of time in thousands of years ago (kya) estimated using MSMC, with four haplotypes per pair. In each subfigure legend, we give the point estimate of the date at which 25%, 50% and 75% of lineages in the pair of populations have coalesced into a common ancestral population. We generated these plots using data phased with the 1000 Genomes reference panel (method PS1 described in supplementary information section 9), but only show pairs of populations for which the cross-coalescence rates are relatively insensitive to the phasing approach. A: Selected African cross-coalescence rates. B: Central African rainforest hunter-gatherer cross-coalescence rates. C: Ancient non-African cross coalescence rates. D–F: Effective population sizes inferred using PSMC, using one diploid genome per population, for the same populations that we used in A–C.

Figure 3. Present-day populations have negligible ancestry from an early dispersal of modern humans out of Africa

Best-fitting admixture graph model of relationships among Australians, New Guineans, Andamanese and other diverse populations. Present-day populations are shown in blue, ancient samples in red, and select inferred ancestral nodes in green. Dotted lines indicate admixture events, all of which involve archaic humans. All f-statistic relationships are accurately fit to within 2.1 standard errors. (Inset) Results of adding putative early dispersal admixture to the graph model for different assumptions about when the early lineage split off. We specify the split time in terms of the genetic drift above the "Non-African" node, with 0.01 units of drift representing on the order of ten thousand years. The (approximate) model likelihood is maximized with zero early dispersal ancestry, and no more than a few percent is consistent with the data.

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Comment in

Population genetics: A map of human wanderlust.
Tucci S, Akey JM. Tucci S, et al. Nature. 2016 Oct 13;538(7624):179-180. doi: 10.1038/nature19472. Epub 2016 Sep 21. Nature. 2016. PMID: 27654916 No abstract available.

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References

1. Genomes Project C, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65. - PMC - PubMed
1. https://support.illumina.com/content/dam/illumina-marketing/documents/services/FastTrackServices_Methods_Tech_Note.pdf.
1. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26:589–595. - PMC - PubMed
1. McKenna A, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research. 2010;20:1297–1303. - PMC - PubMed
1. http://arxiv.org/abs/1504.06574.

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[1] Genomes Project C, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65. - PMC - PubMed

[2] Genomes Project C, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65. - PMC - PubMed

[3] https://support.illumina.com/content/dam/illumina-marketing/documents/services/FastTrackServices_Methods_Tech_Note.pdf.

[4] https://support.illumina.com/content/dam/illumina-marketing/documents/services/FastTrackServices_Methods_Tech_Note.pdf.

[5] Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26:589–595. - PMC - PubMed

[6] Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26:589–595. - PMC - PubMed

[7] McKenna A, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research. 2010;20:1297–1303. - PMC - PubMed

[8] McKenna A, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research. 2010;20:1297–1303. - PMC - PubMed

[9] http://arxiv.org/abs/1504.06574.

[10] http://arxiv.org/abs/1504.06574.

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The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

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The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

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