Analysis of High-Throughput Ancient DNA Sequencing Data View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2012

AUTHORS

Martin Kircher

ABSTRACT

Advances in sequencing technologies have dramatically changed the field of ancient DNA (aDNA). It is now possible to generate an enormous quantity of aDNA sequence data both rapidly and inexpensively. As aDNA sequences are generally short in length, damaged, and at low copy number relative to coextracted environmental DNA, high-throughput approaches offer a tremendous advantage over traditional sequencing approaches in that they enable a complete characterization of an aDNA extract. However, the particular qualities of aDNA also present specific limitations that require careful consideration in data analysis. For example, results of high-throughout analyses of aDNA libraries may include chimeric sequences, sequencing error and artifacts, damage, and alignment ambiguities due to the short read lengths. Here, I describe typical primary data analysis workflows for high-throughput aDNA sequencing experiments, including (1) separation of individual samples in multiplex experiments; (2) removal of protocol-specific library artifacts; (3) trimming adapter sequences and merging paired-end sequencing data; (4) base quality score filtering or quality score propagation during data analysis; (5) identification of endogenous molecules from an environmental background; (6) quantification of contamination from other DNA sources; and (7) removal of clonal amplification products or the compilation of a consensus from clonal amplification products, and their exploitation for estimation of library complexity. More... »

PAGES

197-228

References to SciGraph publications

  • 2009-03. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome in GENOME BIOLOGY
  • 2009-08. Improved base calling for the Illumina Genome Analyzer using machine learning strategies in GENOME BIOLOGY
  • 2008-02. Pyrobayes: an improved base caller for SNP discovery in pyrosequences in NATURE METHODS
  • 2008-11. Sequencing the nuclear genome of the extinct woolly mammoth in NATURE
  • 2010-02-11. Ancient human genome sequence of an extinct Palaeo-Eskimo in NATURE
  • 2010-12. Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction in BMC BIOINFORMATICS
  • 2009-05. How to map billions of short reads onto genomes in NATURE BIOTECHNOLOGY
  • 2008-11. Accurate whole human genome sequencing using reversible terminator chemistry in NATURE
  • 2008-08. Alta-Cyclic: a self-optimizing base caller for next-generation sequencing in NATURE METHODS
  • 2010-02. Target-enrichment strategies for next-generation sequencing in NATURE METHODS
  • 2005-09. Genome sequencing in microfabricated high-density picolitre reactors in NATURE
  • 2010-12. Genetic history of an archaic hominin group from Denisova Cave in Siberia in NATURE
  • 2008-12. Using quality scores and longer reads improves accuracy of Solexa read mapping in BMC BIOINFORMATICS
  • 2010-05. Computational challenges in the analysis of ancient DNA in GENOME BIOLOGY
  • 2010. Standardizing the Next Generation of Bioinformatics Software Development with BioHDF (HDF5) in ADVANCES IN COMPUTATIONAL BIOLOGY
  • 2008-10. Next-generation DNA sequencing in NATURE BIOTECHNOLOGY
  • 2010-04. The complete mitochondrial DNA genome of an unknown hominin from southern Siberia in NATURE
  • 2008-12. TileQC: A system for tile-based quality control of Solexa data in BMC BIOINFORMATICS
  • 2006-02. Multiplex amplification of the mammoth mitochondrial genome and the evolution of Elephantidae in NATURE
  • 2010-12. Artificial and natural duplicates in pyrosequencing reads of metagenomic data in BMC BIOINFORMATICS
  • 2008-02. Parallel tagged sequencing on the 454 platform in NATURE PROTOCOLS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-1-61779-516-9_23

    DOI

    http://dx.doi.org/10.1007/978-1-61779-516-9_23

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1018322075

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/22237537


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Base Sequence", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "DNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Fossils", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Library", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "High-Throughput Nucleotide Sequencing", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Molecular Sequence Data", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Analysis, DNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Software", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Max Planck Institute for Evolutionary Anthropology", 
              "id": "https://www.grid.ac/institutes/grid.419518.0", 
              "name": [
                "Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103\u00a0Leipzig, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kircher", 
            "givenName": "Martin", 
            "id": "sg:person.01172741207.54", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01172741207.54"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1186/gb-2010-11-5-r47", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000160930", 
              "https://doi.org/10.1186/gb-2010-11-5-r47"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1188021", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002597304"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1188021", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002597304"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature07446", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003406391", 
              "https://doi.org/10.1038/nature07446"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/18.7.1687", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004205431"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1365815.1365816", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005702119"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.079053.108", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005708074"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1486", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005954516", 
              "https://doi.org/10.1038/nbt1486"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.229202", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006260064"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bib/bbp019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009995255"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bib/bbp019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009995255"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-11-33", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010080883", 
              "https://doi.org/10.1186/1471-2105-11-33"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/emboj.2009.222", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010219128"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bies.200900181", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010604039"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bies.200900181", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010604039"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1117389", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010697532"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp163", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011232850"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btn025", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012266713"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nprot.2007.520", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012965453", 
              "https://doi.org/10.1038/nprot.2007.520"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0022-2836(05)80360-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013618994"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btl158", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014668137"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04432", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014777217", 
              "https://doi.org/10.1038/nature04432"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04432", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014777217", 
              "https://doi.org/10.1038/nature04432"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04432", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014777217", 
              "https://doi.org/10.1038/nature04432"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1181498", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014947319"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1181498", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014947319"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0710982105", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015261616"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp367", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015468380"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp336", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016441007"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp383", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020011631"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-11-187", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020540926", 
              "https://doi.org/10.1186/1471-2105-11-187"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1172", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020593059", 
              "https://doi.org/10.1038/nmeth.1172"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/29.23.4793", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020812153"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1188046", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020995997"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1188046", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020995997"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature03959", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021574562", 
              "https://doi.org/10.1038/nature03959"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature03959", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021574562", 
              "https://doi.org/10.1038/nature03959"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.095299.109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021759418"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08835", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021776500", 
              "https://doi.org/10.1038/nature08835"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08835", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021776500", 
              "https://doi.org/10.1038/nature08835"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/jmbi.2000.4042", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022575813"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp352", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023014918"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0802315105", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024667673"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08976", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025023915", 
              "https://doi.org/10.1038/nature08976"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08976", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025023915", 
              "https://doi.org/10.1038/nature08976"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkh340", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025846396"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btq461", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025904619"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2008.06.021", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027138557"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2008.06.021", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027138557"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.361602", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028020859"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cub.2009.11.068", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028054623"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cub.2009.11.068", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028054623"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1230", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029364743", 
              "https://doi.org/10.1038/nmeth.1230"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-9-128", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029892891", 
              "https://doi.org/10.1186/1471-2105-9-128"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1150427", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030422156"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.107524.110", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032096953"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-9-250", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034760598", 
              "https://doi.org/10.1186/1471-2105-9-250"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-9-250", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034760598", 
              "https://doi.org/10.1186/1471-2105-9-250"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkp1163", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036956881"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btn322", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038142398"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp324", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038266369"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/23.11.2049", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038595948"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.8.3.186", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038920266"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4419-5913-3_77", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038927211", 
              "https://doi.org/10.1007/978-1-4419-5913-3_77"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2009-10-8-r83", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041308110", 
              "https://doi.org/10.1186/gb-2009-10-8-r83"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.095760.109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041449671"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1419", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042265948", 
              "https://doi.org/10.1038/nmeth.1419"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1419", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042265948", 
              "https://doi.org/10.1038/nmeth.1419"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/22.22.4673", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042438223"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt0509-455", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043194556", 
              "https://doi.org/10.1038/nbt0509-455"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt0509-455", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043194556", 
              "https://doi.org/10.1038/nbt0509-455"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp527", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044842298"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkn425", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044990606"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0704665104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045401726"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkq572", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049568274"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2009-10-3-r25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049583368", 
              "https://doi.org/10.1186/gb-2009-10-3-r25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09710", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050205294", 
              "https://doi.org/10.1038/nature09710"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09710", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050205294", 
              "https://doi.org/10.1038/nature09710"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btm451", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051622036"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.074492.107", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051720574"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature07517", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052925719", 
              "https://doi.org/10.1038/nature07517"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1089/10665270050081478", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059204834"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/pdb.prot5448", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060411299"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1123360", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062453436"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1174462", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062460190"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2144/000113219", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077975130"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1078635978", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2012", 
        "datePublishedReg": "2012-01-01", 
        "description": "Advances in sequencing technologies have dramatically changed the field of ancient DNA (aDNA). It is now possible to generate an enormous quantity of aDNA sequence data both rapidly and inexpensively. As aDNA sequences are generally short in length, damaged, and at low copy number relative to coextracted environmental DNA, high-throughput approaches offer a tremendous advantage over traditional sequencing approaches in that they enable a complete characterization of an aDNA extract. However, the particular qualities of aDNA also present specific limitations that require careful consideration in data analysis. For example, results of high-throughout analyses of aDNA libraries may include chimeric sequences, sequencing error and artifacts, damage, and alignment ambiguities due to the short read lengths. Here, I describe typical primary data analysis workflows for high-throughput aDNA sequencing experiments, including (1) separation of individual samples in multiplex experiments; (2) removal of protocol-specific library artifacts; (3) trimming adapter sequences and merging paired-end sequencing data; (4) base quality score filtering or quality score propagation during data analysis; (5) identification of endogenous molecules from an environmental background; (6) quantification of contamination from other DNA sources; and (7) removal of clonal amplification products or the compilation of a consensus from clonal amplification products, and their exploitation for estimation of library complexity.", 
        "editor": [
          {
            "familyName": "Shapiro", 
            "givenName": "Beth", 
            "type": "Person"
          }, 
          {
            "familyName": "Hofreiter", 
            "givenName": "Michael", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-1-61779-516-9_23", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-1-61779-515-2", 
            "978-1-61779-516-9"
          ], 
          "name": "Ancient DNA", 
          "type": "Book"
        }, 
        "name": "Analysis of High-Throughput Ancient DNA Sequencing Data", 
        "pagination": "197-228", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-1-61779-516-9_23"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "574c08432baf3c43c0bcda61eedee2de3b22cc6b4ab6c2219e7d4807814295a2"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1018322075"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "22237537"
            ]
          }
        ], 
        "publisher": {
          "location": "Totowa, NJ", 
          "name": "Humana Press", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-1-61779-516-9_23", 
          "https://app.dimensions.ai/details/publication/pub.1018322075"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T18:10", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8681_00000254.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-1-61779-516-9_23"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-516-9_23'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-516-9_23'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-516-9_23'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-516-9_23'


     

    This table displays all metadata directly associated to this object as RDF triples.

    339 TRIPLES      23 PREDICATES      107 URIs      29 LITERALS      17 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-1-61779-516-9_23 schema:about N12f94f3c872b4606a23b6d3df34b2675
    2 N1e54351197d846269e78e8d671d356ae
    3 N328864a2d2fa4ba59b17f3dcf8ba1a8d
    4 N3f5ba9851acb4a0da5defcc0493e6f53
    5 N50dc8a37a63042798b39285afd56f017
    6 N9b809b1a06fa43f5b8a5c8a9281ef9cc
    7 Nb7523c72faa14e6282010b65d82f35f5
    8 Nb92319d32de04133a6b37078c7cc68b5
    9 anzsrc-for:06
    10 anzsrc-for:0604
    11 schema:author N735388f89f9f40f2864be40652c52538
    12 schema:citation sg:pub.10.1007/978-1-4419-5913-3_77
    13 sg:pub.10.1038/nature03959
    14 sg:pub.10.1038/nature04432
    15 sg:pub.10.1038/nature07446
    16 sg:pub.10.1038/nature07517
    17 sg:pub.10.1038/nature08835
    18 sg:pub.10.1038/nature08976
    19 sg:pub.10.1038/nature09710
    20 sg:pub.10.1038/nbt0509-455
    21 sg:pub.10.1038/nbt1486
    22 sg:pub.10.1038/nmeth.1172
    23 sg:pub.10.1038/nmeth.1230
    24 sg:pub.10.1038/nmeth.1419
    25 sg:pub.10.1038/nprot.2007.520
    26 sg:pub.10.1186/1471-2105-11-187
    27 sg:pub.10.1186/1471-2105-11-33
    28 sg:pub.10.1186/1471-2105-9-128
    29 sg:pub.10.1186/1471-2105-9-250
    30 sg:pub.10.1186/gb-2009-10-3-r25
    31 sg:pub.10.1186/gb-2009-10-8-r83
    32 sg:pub.10.1186/gb-2010-11-5-r47
    33 https://app.dimensions.ai/details/publication/pub.1078635978
    34 https://doi.org/10.1002/bies.200900181
    35 https://doi.org/10.1006/jmbi.2000.4042
    36 https://doi.org/10.1016/j.cell.2008.06.021
    37 https://doi.org/10.1016/j.cub.2009.11.068
    38 https://doi.org/10.1016/s0022-2836(05)80360-2
    39 https://doi.org/10.1038/emboj.2009.222
    40 https://doi.org/10.1073/pnas.0704665104
    41 https://doi.org/10.1073/pnas.0710982105
    42 https://doi.org/10.1073/pnas.0802315105
    43 https://doi.org/10.1089/10665270050081478
    44 https://doi.org/10.1093/bib/bbp019
    45 https://doi.org/10.1093/bioinformatics/btl158
    46 https://doi.org/10.1093/bioinformatics/btm451
    47 https://doi.org/10.1093/bioinformatics/btn025
    48 https://doi.org/10.1093/bioinformatics/btn322
    49 https://doi.org/10.1093/bioinformatics/btp163
    50 https://doi.org/10.1093/bioinformatics/btp324
    51 https://doi.org/10.1093/bioinformatics/btp336
    52 https://doi.org/10.1093/bioinformatics/btp352
    53 https://doi.org/10.1093/bioinformatics/btp367
    54 https://doi.org/10.1093/bioinformatics/btp383
    55 https://doi.org/10.1093/bioinformatics/btp527
    56 https://doi.org/10.1093/bioinformatics/btq461
    57 https://doi.org/10.1093/nar/18.7.1687
    58 https://doi.org/10.1093/nar/22.22.4673
    59 https://doi.org/10.1093/nar/23.11.2049
    60 https://doi.org/10.1093/nar/29.23.4793
    61 https://doi.org/10.1093/nar/gkh340
    62 https://doi.org/10.1093/nar/gkn425
    63 https://doi.org/10.1093/nar/gkp1163
    64 https://doi.org/10.1093/nar/gkq572
    65 https://doi.org/10.1101/gr.074492.107
    66 https://doi.org/10.1101/gr.079053.108
    67 https://doi.org/10.1101/gr.095299.109
    68 https://doi.org/10.1101/gr.095760.109
    69 https://doi.org/10.1101/gr.107524.110
    70 https://doi.org/10.1101/gr.229202
    71 https://doi.org/10.1101/gr.361602
    72 https://doi.org/10.1101/gr.8.3.186
    73 https://doi.org/10.1101/pdb.prot5448
    74 https://doi.org/10.1126/science.1117389
    75 https://doi.org/10.1126/science.1123360
    76 https://doi.org/10.1126/science.1150427
    77 https://doi.org/10.1126/science.1174462
    78 https://doi.org/10.1126/science.1181498
    79 https://doi.org/10.1126/science.1188021
    80 https://doi.org/10.1126/science.1188046
    81 https://doi.org/10.1145/1365815.1365816
    82 https://doi.org/10.2144/000113219
    83 schema:datePublished 2012
    84 schema:datePublishedReg 2012-01-01
    85 schema:description Advances in sequencing technologies have dramatically changed the field of ancient DNA (aDNA). It is now possible to generate an enormous quantity of aDNA sequence data both rapidly and inexpensively. As aDNA sequences are generally short in length, damaged, and at low copy number relative to coextracted environmental DNA, high-throughput approaches offer a tremendous advantage over traditional sequencing approaches in that they enable a complete characterization of an aDNA extract. However, the particular qualities of aDNA also present specific limitations that require careful consideration in data analysis. For example, results of high-throughout analyses of aDNA libraries may include chimeric sequences, sequencing error and artifacts, damage, and alignment ambiguities due to the short read lengths. Here, I describe typical primary data analysis workflows for high-throughput aDNA sequencing experiments, including (1) separation of individual samples in multiplex experiments; (2) removal of protocol-specific library artifacts; (3) trimming adapter sequences and merging paired-end sequencing data; (4) base quality score filtering or quality score propagation during data analysis; (5) identification of endogenous molecules from an environmental background; (6) quantification of contamination from other DNA sources; and (7) removal of clonal amplification products or the compilation of a consensus from clonal amplification products, and their exploitation for estimation of library complexity.
    86 schema:editor N7eb6d191335d4846b666194c9baf82b3
    87 schema:genre chapter
    88 schema:inLanguage en
    89 schema:isAccessibleForFree false
    90 schema:isPartOf N1292c1c2e2184f9088e8192f307c1bda
    91 schema:name Analysis of High-Throughput Ancient DNA Sequencing Data
    92 schema:pagination 197-228
    93 schema:productId N1264a63e016142ccbedb11a7f4e2610c
    94 N2ccc936acc414b9e8d3de0475d2fab4d
    95 Na7cab67badf04eb4b5be7a45e9dd1570
    96 Nb3a6f28adae2498e906da5f3a14e6a12
    97 schema:publisher Nc10295b3274f47f8ada8cc38da68c917
    98 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018322075
    99 https://doi.org/10.1007/978-1-61779-516-9_23
    100 schema:sdDatePublished 2019-04-15T18:10
    101 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    102 schema:sdPublisher Nad38a149e0c74101870008dd42245361
    103 schema:url http://link.springer.com/10.1007/978-1-61779-516-9_23
    104 sgo:license sg:explorer/license/
    105 sgo:sdDataset chapters
    106 rdf:type schema:Chapter
    107 N1264a63e016142ccbedb11a7f4e2610c schema:name dimensions_id
    108 schema:value pub.1018322075
    109 rdf:type schema:PropertyValue
    110 N1292c1c2e2184f9088e8192f307c1bda schema:isbn 978-1-61779-515-2
    111 978-1-61779-516-9
    112 schema:name Ancient DNA
    113 rdf:type schema:Book
    114 N12f94f3c872b4606a23b6d3df34b2675 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    115 schema:name Base Sequence
    116 rdf:type schema:DefinedTerm
    117 N1e54351197d846269e78e8d671d356ae schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    118 schema:name Sequence Analysis, DNA
    119 rdf:type schema:DefinedTerm
    120 N2ccc936acc414b9e8d3de0475d2fab4d schema:name doi
    121 schema:value 10.1007/978-1-61779-516-9_23
    122 rdf:type schema:PropertyValue
    123 N328864a2d2fa4ba59b17f3dcf8ba1a8d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    124 schema:name Fossils
    125 rdf:type schema:DefinedTerm
    126 N3f5ba9851acb4a0da5defcc0493e6f53 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    127 schema:name DNA
    128 rdf:type schema:DefinedTerm
    129 N50dc8a37a63042798b39285afd56f017 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    130 schema:name Gene Library
    131 rdf:type schema:DefinedTerm
    132 N52603d4bd08845ccb242df0b446c966c schema:familyName Shapiro
    133 schema:givenName Beth
    134 rdf:type schema:Person
    135 N735388f89f9f40f2864be40652c52538 rdf:first sg:person.01172741207.54
    136 rdf:rest rdf:nil
    137 N756d5b653d9045309fce09b33e36cc67 schema:familyName Hofreiter
    138 schema:givenName Michael
    139 rdf:type schema:Person
    140 N7eb6d191335d4846b666194c9baf82b3 rdf:first N52603d4bd08845ccb242df0b446c966c
    141 rdf:rest Nfea2a53136654207b3e8796171818e43
    142 N9b809b1a06fa43f5b8a5c8a9281ef9cc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    143 schema:name Molecular Sequence Data
    144 rdf:type schema:DefinedTerm
    145 Na7cab67badf04eb4b5be7a45e9dd1570 schema:name pubmed_id
    146 schema:value 22237537
    147 rdf:type schema:PropertyValue
    148 Nad38a149e0c74101870008dd42245361 schema:name Springer Nature - SN SciGraph project
    149 rdf:type schema:Organization
    150 Nb3a6f28adae2498e906da5f3a14e6a12 schema:name readcube_id
    151 schema:value 574c08432baf3c43c0bcda61eedee2de3b22cc6b4ab6c2219e7d4807814295a2
    152 rdf:type schema:PropertyValue
    153 Nb7523c72faa14e6282010b65d82f35f5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    154 schema:name Software
    155 rdf:type schema:DefinedTerm
    156 Nb92319d32de04133a6b37078c7cc68b5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    157 schema:name High-Throughput Nucleotide Sequencing
    158 rdf:type schema:DefinedTerm
    159 Nc10295b3274f47f8ada8cc38da68c917 schema:location Totowa, NJ
    160 schema:name Humana Press
    161 rdf:type schema:Organisation
    162 Nfea2a53136654207b3e8796171818e43 rdf:first N756d5b653d9045309fce09b33e36cc67
    163 rdf:rest rdf:nil
    164 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    165 schema:name Biological Sciences
    166 rdf:type schema:DefinedTerm
    167 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    168 schema:name Genetics
    169 rdf:type schema:DefinedTerm
    170 sg:person.01172741207.54 schema:affiliation https://www.grid.ac/institutes/grid.419518.0
    171 schema:familyName Kircher
    172 schema:givenName Martin
    173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01172741207.54
    174 rdf:type schema:Person
    175 sg:pub.10.1007/978-1-4419-5913-3_77 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038927211
    176 https://doi.org/10.1007/978-1-4419-5913-3_77
    177 rdf:type schema:CreativeWork
    178 sg:pub.10.1038/nature03959 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021574562
    179 https://doi.org/10.1038/nature03959
    180 rdf:type schema:CreativeWork
    181 sg:pub.10.1038/nature04432 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014777217
    182 https://doi.org/10.1038/nature04432
    183 rdf:type schema:CreativeWork
    184 sg:pub.10.1038/nature07446 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003406391
    185 https://doi.org/10.1038/nature07446
    186 rdf:type schema:CreativeWork
    187 sg:pub.10.1038/nature07517 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052925719
    188 https://doi.org/10.1038/nature07517
    189 rdf:type schema:CreativeWork
    190 sg:pub.10.1038/nature08835 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021776500
    191 https://doi.org/10.1038/nature08835
    192 rdf:type schema:CreativeWork
    193 sg:pub.10.1038/nature08976 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025023915
    194 https://doi.org/10.1038/nature08976
    195 rdf:type schema:CreativeWork
    196 sg:pub.10.1038/nature09710 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050205294
    197 https://doi.org/10.1038/nature09710
    198 rdf:type schema:CreativeWork
    199 sg:pub.10.1038/nbt0509-455 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043194556
    200 https://doi.org/10.1038/nbt0509-455
    201 rdf:type schema:CreativeWork
    202 sg:pub.10.1038/nbt1486 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005954516
    203 https://doi.org/10.1038/nbt1486
    204 rdf:type schema:CreativeWork
    205 sg:pub.10.1038/nmeth.1172 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020593059
    206 https://doi.org/10.1038/nmeth.1172
    207 rdf:type schema:CreativeWork
    208 sg:pub.10.1038/nmeth.1230 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029364743
    209 https://doi.org/10.1038/nmeth.1230
    210 rdf:type schema:CreativeWork
    211 sg:pub.10.1038/nmeth.1419 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042265948
    212 https://doi.org/10.1038/nmeth.1419
    213 rdf:type schema:CreativeWork
    214 sg:pub.10.1038/nprot.2007.520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012965453
    215 https://doi.org/10.1038/nprot.2007.520
    216 rdf:type schema:CreativeWork
    217 sg:pub.10.1186/1471-2105-11-187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020540926
    218 https://doi.org/10.1186/1471-2105-11-187
    219 rdf:type schema:CreativeWork
    220 sg:pub.10.1186/1471-2105-11-33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010080883
    221 https://doi.org/10.1186/1471-2105-11-33
    222 rdf:type schema:CreativeWork
    223 sg:pub.10.1186/1471-2105-9-128 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029892891
    224 https://doi.org/10.1186/1471-2105-9-128
    225 rdf:type schema:CreativeWork
    226 sg:pub.10.1186/1471-2105-9-250 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034760598
    227 https://doi.org/10.1186/1471-2105-9-250
    228 rdf:type schema:CreativeWork
    229 sg:pub.10.1186/gb-2009-10-3-r25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049583368
    230 https://doi.org/10.1186/gb-2009-10-3-r25
    231 rdf:type schema:CreativeWork
    232 sg:pub.10.1186/gb-2009-10-8-r83 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041308110
    233 https://doi.org/10.1186/gb-2009-10-8-r83
    234 rdf:type schema:CreativeWork
    235 sg:pub.10.1186/gb-2010-11-5-r47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000160930
    236 https://doi.org/10.1186/gb-2010-11-5-r47
    237 rdf:type schema:CreativeWork
    238 https://app.dimensions.ai/details/publication/pub.1078635978 schema:CreativeWork
    239 https://doi.org/10.1002/bies.200900181 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010604039
    240 rdf:type schema:CreativeWork
    241 https://doi.org/10.1006/jmbi.2000.4042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022575813
    242 rdf:type schema:CreativeWork
    243 https://doi.org/10.1016/j.cell.2008.06.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027138557
    244 rdf:type schema:CreativeWork
    245 https://doi.org/10.1016/j.cub.2009.11.068 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028054623
    246 rdf:type schema:CreativeWork
    247 https://doi.org/10.1016/s0022-2836(05)80360-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013618994
    248 rdf:type schema:CreativeWork
    249 https://doi.org/10.1038/emboj.2009.222 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010219128
    250 rdf:type schema:CreativeWork
    251 https://doi.org/10.1073/pnas.0704665104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045401726
    252 rdf:type schema:CreativeWork
    253 https://doi.org/10.1073/pnas.0710982105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015261616
    254 rdf:type schema:CreativeWork
    255 https://doi.org/10.1073/pnas.0802315105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024667673
    256 rdf:type schema:CreativeWork
    257 https://doi.org/10.1089/10665270050081478 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059204834
    258 rdf:type schema:CreativeWork
    259 https://doi.org/10.1093/bib/bbp019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009995255
    260 rdf:type schema:CreativeWork
    261 https://doi.org/10.1093/bioinformatics/btl158 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014668137
    262 rdf:type schema:CreativeWork
    263 https://doi.org/10.1093/bioinformatics/btm451 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051622036
    264 rdf:type schema:CreativeWork
    265 https://doi.org/10.1093/bioinformatics/btn025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012266713
    266 rdf:type schema:CreativeWork
    267 https://doi.org/10.1093/bioinformatics/btn322 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038142398
    268 rdf:type schema:CreativeWork
    269 https://doi.org/10.1093/bioinformatics/btp163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011232850
    270 rdf:type schema:CreativeWork
    271 https://doi.org/10.1093/bioinformatics/btp324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038266369
    272 rdf:type schema:CreativeWork
    273 https://doi.org/10.1093/bioinformatics/btp336 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016441007
    274 rdf:type schema:CreativeWork
    275 https://doi.org/10.1093/bioinformatics/btp352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023014918
    276 rdf:type schema:CreativeWork
    277 https://doi.org/10.1093/bioinformatics/btp367 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015468380
    278 rdf:type schema:CreativeWork
    279 https://doi.org/10.1093/bioinformatics/btp383 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020011631
    280 rdf:type schema:CreativeWork
    281 https://doi.org/10.1093/bioinformatics/btp527 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044842298
    282 rdf:type schema:CreativeWork
    283 https://doi.org/10.1093/bioinformatics/btq461 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025904619
    284 rdf:type schema:CreativeWork
    285 https://doi.org/10.1093/nar/18.7.1687 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004205431
    286 rdf:type schema:CreativeWork
    287 https://doi.org/10.1093/nar/22.22.4673 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042438223
    288 rdf:type schema:CreativeWork
    289 https://doi.org/10.1093/nar/23.11.2049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038595948
    290 rdf:type schema:CreativeWork
    291 https://doi.org/10.1093/nar/29.23.4793 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020812153
    292 rdf:type schema:CreativeWork
    293 https://doi.org/10.1093/nar/gkh340 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025846396
    294 rdf:type schema:CreativeWork
    295 https://doi.org/10.1093/nar/gkn425 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044990606
    296 rdf:type schema:CreativeWork
    297 https://doi.org/10.1093/nar/gkp1163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036956881
    298 rdf:type schema:CreativeWork
    299 https://doi.org/10.1093/nar/gkq572 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049568274
    300 rdf:type schema:CreativeWork
    301 https://doi.org/10.1101/gr.074492.107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051720574
    302 rdf:type schema:CreativeWork
    303 https://doi.org/10.1101/gr.079053.108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005708074
    304 rdf:type schema:CreativeWork
    305 https://doi.org/10.1101/gr.095299.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021759418
    306 rdf:type schema:CreativeWork
    307 https://doi.org/10.1101/gr.095760.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041449671
    308 rdf:type schema:CreativeWork
    309 https://doi.org/10.1101/gr.107524.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032096953
    310 rdf:type schema:CreativeWork
    311 https://doi.org/10.1101/gr.229202 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006260064
    312 rdf:type schema:CreativeWork
    313 https://doi.org/10.1101/gr.361602 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028020859
    314 rdf:type schema:CreativeWork
    315 https://doi.org/10.1101/gr.8.3.186 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038920266
    316 rdf:type schema:CreativeWork
    317 https://doi.org/10.1101/pdb.prot5448 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060411299
    318 rdf:type schema:CreativeWork
    319 https://doi.org/10.1126/science.1117389 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010697532
    320 rdf:type schema:CreativeWork
    321 https://doi.org/10.1126/science.1123360 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062453436
    322 rdf:type schema:CreativeWork
    323 https://doi.org/10.1126/science.1150427 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030422156
    324 rdf:type schema:CreativeWork
    325 https://doi.org/10.1126/science.1174462 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062460190
    326 rdf:type schema:CreativeWork
    327 https://doi.org/10.1126/science.1181498 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014947319
    328 rdf:type schema:CreativeWork
    329 https://doi.org/10.1126/science.1188021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002597304
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1126/science.1188046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020995997
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1145/1365815.1365816 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005702119
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.2144/000113219 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077975130
    336 rdf:type schema:CreativeWork
    337 https://www.grid.ac/institutes/grid.419518.0 schema:alternateName Max Planck Institute for Evolutionary Anthropology
    338 schema:name Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
    339 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...