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The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Joint Estimation of Contamination, Error and Demography for Nuclear DNA from Ancient Humans

Racimo, Fernando, Renaud, Gabriel, Slatkin, Montgomery·2016·PLOS Genetics

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Crossref · 10.1371/journal.pgen.1005972

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  • Genome editing technologies such as CRISPR-Cas9, pluripotent iPS stem cells and miniaturized organoid systems mimicking simplified organs now offer possibility to investigate functional consequences of virtually any change in sequence of a given genome.

    “Genome editing technologies such as CRISPR-Cas9 344 , pluripotent iPS stem cells 345 and miniaturized organoid systems mimicking simplified organs 346 now offer the possibility to investigate the functional consequences of virtually any change in the sequence of a given genome.”

    From Ancient DNA analysis (2021) · cites this paper as [346]

    The Discussion (page not provided) describes DICE, a method for estimating contamination, sequencing error and demographic parameters in ancient DNA. Searches for CRISPR-Cas9, iPS cells, organoids and functional consequences of genome edits found no passage addressing the attributed claim. (LLM, conf=0.75)

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Research works printed but not linked: 25

  1. R. E. Green, 2010, A draft sequence of the Neandertal genome, Science, 328, 710, 10.1126/science.1188021 · DOI · Paper page
  2. R. E. Green, 2008, A complete Neandertal mitochondrial genome sequence determined by high-throughput sequencing, Cell, 134, 416, 10.1016/j.cell.2008.06.021 · DOI
  3. R. E. Green, 2009, The Neandertal genome and ancient DNA authenticity, The EMBO journal, 28, 2494, 10.1038/emboj.2009.222 · DOI · Paper page
  4. S. Sawyer, 2015, Nuclear and mitochondrial dna sequences from two denisovan individuals, Proceedings of the National Academy of Sciences, 112, 15696, 10.1073/pnas.1519905112 · DOI
  5. P. Skoglund, 2013, Accurate sex identification of ancient human remains using DNA shotgun sequencing, Journal of Archaeological Science, 40, 4477, 10.1016/j.jas.2013.07.004 · DOI · Paper page
  6. R. H. Byrd, 1995, A limited memory algorithm for bound constrained optimization, SIAM Journal on Scientific Computing, 16, 1190, 10.1137/0916069 · DOI
  7. 2015, A global reference for human genetic variation, Nature, 526, 68, 10.1038/nature15393 · DOI · Paper page
  8. H. Chen, 2007, The joint allele-frequency spectrum in closely related species, Genetics, 177, 387, 10.1534/genetics.107.070730 · DOI
  9. G. Ewing, 2010, MSMS: a coalescent simulation program including recombination, demographic structure and selection at a single locus, Bioinformatics, 26, 2064, 10.1093/bioinformatics/btq322 · DOI
  10. G. O. Roberts, 1997, Weak convergence and optimal scaling of random walk Metropolis algorithms, The Annals of Applied Probability, 7, 110, 10.1214/aoap/1034625254 · DOI · Paper page
  11. A. W. Briggs, 2010, Removal of deaminated cytosines and detection of in vivo methylation in ancient dna, Nucleic acids research, 38, e87, 10.1093/nar/gkp1163 · DOI · Paper page
  12. R. D. Hernandez, 2007, Context dependence, ancestral misidentification, and spurious signatures of natural selection, Molecular Biology and Evolution, 24, 1792, 10.1093/molbev/msm108 · DOI · Paper page
  13. R. R. Hudson, 2002, Generating samples under a wright–fisher neutral model of genetic variation, Bioinformatics, 18, 337, 10.1093/bioinformatics/18.2.337 · DOI
  14. H. Li, 2009, Fast and accurate short read alignment with burrows–wheeler transform, Bioinformatics, 25, 1754, 10.1093/bioinformatics/btp324 · DOI · Paper page
  15. A. Rambaut, 1997, Seq-gen: an application for the monte carlo simulation of dna sequence evolution along phylogenetic trees, Computer applications in the biosciences: CABIOS, 13, 235
  16. M. Hasegawa, 1985, Dating of the human-ape splitting by a molecular clock of mitochondrial dna, Journal of molecular evolution, 22, 160, 10.1007/BF02101694 · DOI · Paper page
  17. G. Renaud, 2013, freeibis: an efficient basecaller with calibrated quality scores for illumina sequencers, Bioinformatics, 29, 1208, 10.1093/bioinformatics/btt117 · DOI
  18. K. R. Rosenbloom, 2015, The ucsc genome browser database: 2015 update, Nucleic acids research, 43, D670, 10.1093/nar/gku1177 · DOI
  19. M. Lipson, 2013, Efficient moment-based inference of admixture parameters and sources of gene flow, Molecular biology and evolution, 30, 1788, 10.1093/molbev/mst099 · DOI
  20. T. Higham, 2014, The timing and spatiotemporal patterning of Neanderthal disappearance, Nature, 512, 306, 10.1038/nature13621 · DOI
  21. H. Li, 2011, Inference of human population history from individual whole-genome sequences, Nature, 475, 493, 10.1038/nature10231 · DOI · Paper page
  22. S. Castellano, 2014, Patterns of coding variation in the complete exomes of three Neandertals, Proceedings of the National Academy of Sciences, 111, 6666, 10.1073/pnas.1405138111 · DOI · Paper page
  23. H. Chen, 2012, The joint allele frequency spectrum of multiple populations: a coalescent theory approach, Theoretical Population Biology, 81, 179, 10.1016/j.tpb.2011.11.004 · DOI
  24. E. M. Jewett, 2014, Theory and applications of a deterministic approximation to the coalescent model, Theoretical Population Biology, 93, 14, 10.1016/j.tpb.2013.12.007 · DOI
  25. J. A. Kamm, J. Terhorst, Y. S. Song, Efficient computation of the joint sample frequency spectra for multiple populations, arXiv preprint arXiv:1503.01133 (2015). · arXiv

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Metadata

Authors
Racimo, F., Renaud, G., & Slatkin, M.
Venue
PLOS Genetics
Published
2016-04-06
Volume
12
Issue
4
Pages
e1005972
ISSN
1553-7404
Cited by
56
References
17
Language
en

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