The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Robust and scalable inference of population history from hundreds of unphased whole genomes
Open accessAbstract
It has recently been demonstrated that inference methods based on genealogical processes with recombination can uncover past population history in unprecedented detail. However, these methods scale poorly with sample size, limiting resolution in the recent past, and they require phased genomes, which contain switch errors that can catastrophically distort the inferred history. Here we present SMC++, a new statistical tool capable of analyzing orders of magnitude more samples than existing methods while requiring only unphased genomes (its results are independent of phasing). SMC++ can jointly infer population size histories and split times in diverged populations, and it employs a novel spline regularization scheme that greatly reduces estimation error. We apply SMC++ to analyze sequence data from over a thousand human genomes in Africa and Eurasia, hundreds of genomes from a Drosophila melanogaster population in Africa, and tens of genomes from zebra finch and long-tailed finch populations in Australia.
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Cites
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
A draft sequence of the Neandertal genome
Green, R. E., Krause, J., Briggs, A. W., Maricic, T., Stenzel, U., Kircher, M., Patterson, N., Li, H., Zhai, W., Fritz, M. H.-Y., et al. (2010) · Science · doi:10.1126/science.1188021 · Cited by 4,318
Inference of human population history from individual whole-genome sequences
Li, H., & Durbin, R. (2011) · Nature · doi:10.1038/nature10231 · Cited by 2,590
The complete genome sequence of a Neanderthal from the Altai Mountains
Prüfer, K., Racimo, F., Patterson, N., Jay, F., Sankararaman, S., Sawyer, S., Heinze, A., Renaud, G., Sudmant, P. H., de Filippo, C., et al. (2014) · Nature · doi:10.1038/nature12886 · Cited by 2,254
Gutenkunst, R. N., Hernandez, R. D., Williamson, S. H., & Bustamante, C. D. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000695 · Cited by 1,906 · cited 2×
“Next, we compared SMC++ with MSMC and the SFS-based inference method ∂ a ∂ i 18 .”
BackgroundResultEvolution and functional impact of rare coding variation from deep sequencing of human exomes
Tennessen, J. A., Bigham, A. W., O’Connor, T. D., Fu, W., Kenny, E. E., Gravel, S., McGee, S., Do, R., Liu, X., Jun, G., et al. (2012) · Science · doi:10.1126/science.1219240 · Cited by 1,613
Robust Demographic Inference from Genomic and SNP Data
Excoffier, L., Dupanloup, I., Huerta-Sánchez, E., Sousa, V. C., & Foll, M. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003905 · Cited by 1,466
Improved whole-chromosome phasing for disease and population genetic studies
Delaneau, O., Zagury, J.-F., & Marchini, J. (2013) · Nature Methods · doi:10.1038/nmeth.2307 · Cited by 1,315
Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays
Drmanac, R., Sparks, A. B., Callow, M. J., Halpern, A. L., Burns, N. L., Kermani, B. G., Carnevali, P., Nazarenko, I., Nilsen, G. B., Yeung, G., et al. (2010) · Science · doi:10.1126/science.1181498 · Cited by 1,212
Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA
Huerta-Sánchez, E., Jin, X., Asan, Bianba, Z., Peter, B. M., Vinckenbosch, N., Liang, Y., Yi, X., He, M., Somel, M., et al. (2014) · Nature · doi:10.1038/nature13408 · Cited by 1,208
Cited by
Insights into human genetic variation and population history from 929 diverse genomes
Bergström, A., McCarthy, S. A., Hui, R., Almarri, M. A., Ayub, Q., Danecek, P., Chen, Y., Felkel, S., Hallast, P., Kamm, J., et al. (2020) · Science · doi:10.1126/science.aay5012 · Cited by 1,020
Self-citationA high-coverage Neandertal genome from Vindija Cave in Croatia
Prüfer, K., de Filippo, C., Grote, S., Mafessoni, F., Korlević, P., Hajdinjak, M., Vernot, B., Skov, L., Hsieh, P., Peyrégne, S., et al. (2017) · Science · doi:10.1126/science.aao1887 · Cited by 719
Population genomics for wildlife conservation and management
Hohenlohe, P. A., Funk, W. C., & Rajora, O. P. (2021) · Molecular Ecology · doi:10.1111/mec.15720 · Cited by 702
A method for genome-wide genealogy estimation for thousands of samples
Speidel, L., Forest, M., Shi, S., & Myers, S. R. (2019) · Nature Genetics · doi:10.1038/s41588-019-0484-x · Cited by 480
fastsimcoal2: demographic inference under complex evolutionary scenarios
Excoffier, L., Marchi, N., Marques, D. A., Matthey-Doret, R., Gouy, A., & Sousa, V. C. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab468 · Cited by 426
Metadata
- Authors
- Terhorst, J., Kamm, J. A., & Song, Y. S.
- Venue
- Nature Genetics
- Published
- 2016-12-26
- Volume
- 49
- Issue
- 2
- Pages
- 303-309
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W2564456678
- Cited by
- 937
- References
- 44
- FWCI
- 27.64
- Type
- journal article
- Language
- en
- Open access
- green
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