Inference of Population Structure from Ancient DNA View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Tyler A. Joseph , Itsik Pe’er

ABSTRACT

Methods for inferring population structure from genetic information traditionally assume samples are contemporary. Yet, the increasing availability of ancient DNA sequences begs revision of this paradigm. We present Dystruct (Dynamic Structure), a framework and toolbox for inference of shared ancestry from data that include ancient DNA. By explicitly modeling population history and genetic drift as a time-series, Dystruct more accurately and realistically discovers shared ancestry from ancient and contemporary samples. Formally, we use a normal approximation of drift, which allows a novel, efficient algorithm for optimizing model parameters using stochastic variational inference. We show that Dystruct outperforms the state of the art when individuals are sampled over time, as is common in ancient DNA datasets. We further demonstrate the utility of our method on a dataset of 92 ancient samples alongside 1941 modern ones genotyped at 222755 loci. Our model tends to present modern samples as the mixtures of ancestral populations they really are, rather than the artifactual converse of presenting ancestral samples as mixtures of contemporary groups. More... »

PAGES

90-104

Book

TITLE

Research in Computational Molecular Biology

ISBN

978-3-319-89928-2
978-3-319-89929-9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-89929-9_6

DOI

http://dx.doi.org/10.1007/978-3-319-89929-9_6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1103403000


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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Columbia University", 
          "id": "https://www.grid.ac/institutes/grid.21729.3f", 
          "name": [
            "Columbia University"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Joseph", 
        "givenName": "Tyler A.", 
        "id": "sg:person.012444370414.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012444370414.30"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Columbia University", 
          "id": "https://www.grid.ac/institutes/grid.21729.3f", 
          "name": [
            "Columbia University"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pe\u2019er", 
        "givenName": "Itsik", 
        "id": "sg:person.014337342227.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014337342227.51"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "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": "https://doi.org/10.1534/genetics.112.145037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006334147"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1534/genetics.112.145037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006334147"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.094052.109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010760027"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.aaa0114", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011366467"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/2133806.2133826", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012425283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature12736", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014659896", 
          "https://doi.org/10.1038/nature12736"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature12886", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016472358", 
          "https://doi.org/10.1038/nature12886"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1216304", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016746627"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ncomms1701", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018056965", 
          "https://doi.org/10.1038/ncomms1701"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1143844.1143859", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018244254"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/519795", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019061180"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.3710", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020695814", 
          "https://doi.org/10.1038/ng.3710"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13810", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020730897", 
          "https://doi.org/10.1038/nature13810"
        ], 
        "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": "sg:pub.10.1038/nature17993", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024096700", 
          "https://doi.org/10.1038/nature17993"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1007665907178", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025979677", 
          "https://doi.org/10.1023/a:1007665907178"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature14507", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027303071", 
          "https://doi.org/10.1038/nature14507"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1534/genetics.115.183913", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028394547"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1534/genetics.115.183913", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028394547"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature21347", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029627482", 
          "https://doi.org/10.1038/nature21347"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ncomms6257", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037347132", 
          "https://doi.org/10.1038/ncomms6257"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature14317", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046463951", 
          "https://doi.org/10.1038/nature14317"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13673", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047142949", 
          "https://doi.org/10.1038/nature13673"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature12960", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048008000", 
          "https://doi.org/10.1038/nature12960"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1534/genetics.114.164350", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048824135"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1534/genetics.114.164350", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048824135"
        ], 
        "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/molbev/mst099", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052811713"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1253448", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062469963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1561/2200000001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068001396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1074647594", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2017.1285773", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084157900"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1558-5646.1967.tb03411.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085728641"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.aao6266", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092036091"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018", 
    "datePublishedReg": "2018-01-01", 
    "description": "Methods for inferring population structure from genetic information traditionally assume samples are contemporary. Yet, the increasing availability of ancient DNA sequences begs revision of this paradigm. We present Dystruct (Dynamic Structure), a framework and toolbox for inference of shared ancestry from data that include ancient DNA. By explicitly modeling population history and genetic drift as a time-series, Dystruct more accurately and realistically discovers shared ancestry from ancient and contemporary samples. Formally, we use a normal approximation of drift, which allows a novel, efficient algorithm for optimizing model parameters using stochastic variational inference. We show that Dystruct outperforms the state of the art when individuals are sampled over time, as is common in ancient DNA datasets. We further demonstrate the utility of our method on a dataset of 92 ancient samples alongside 1941 modern ones genotyped at 222755 loci. Our model tends to present modern samples as the mixtures of ancestral populations they really are, rather than the artifactual converse of presenting ancestral samples as mixtures of contemporary groups.", 
    "editor": [
      {
        "familyName": "Raphael", 
        "givenName": "Benjamin J.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-89929-9_6", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.4179348", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.3131789", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.5301960", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": {
      "isbn": [
        "978-3-319-89928-2", 
        "978-3-319-89929-9"
      ], 
      "name": "Research in Computational Molecular Biology", 
      "type": "Book"
    }, 
    "name": "Inference of Population Structure from Ancient DNA", 
    "pagination": "90-104", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-89929-9_6"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "37d75b6cb59e16ef6483916c8bb201a231fcfe65cb7f41e9c18b366cbd216c49"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1103403000"
        ]
      }
    ], 
    "publisher": {
      "location": "Cham", 
      "name": "Springer International Publishing", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-89929-9_6", 
      "https://app.dimensions.ai/details/publication/pub.1103403000"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T11:45", 
    "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_8660_00000352.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-3-319-89929-9_6"
  }
]
 

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.10.1007/978-3-319-89929-9_6'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-89929-9_6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-89929-9_6'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-89929-9_6'


 

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

188 TRIPLES      23 PREDICATES      59 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-89929-9_6 schema:about anzsrc-for:06
2 anzsrc-for:0604
3 schema:author N2e95c8d44b5c46d8b0fe29050266e9e4
4 schema:citation sg:pub.10.1023/a:1007665907178
5 sg:pub.10.1038/nature08835
6 sg:pub.10.1038/nature09710
7 sg:pub.10.1038/nature12736
8 sg:pub.10.1038/nature12886
9 sg:pub.10.1038/nature12960
10 sg:pub.10.1038/nature13673
11 sg:pub.10.1038/nature13810
12 sg:pub.10.1038/nature14317
13 sg:pub.10.1038/nature14507
14 sg:pub.10.1038/nature17993
15 sg:pub.10.1038/nature21347
16 sg:pub.10.1038/ncomms1701
17 sg:pub.10.1038/ncomms6257
18 sg:pub.10.1038/ng.3710
19 https://app.dimensions.ai/details/publication/pub.1074647594
20 https://doi.org/10.1080/01621459.2017.1285773
21 https://doi.org/10.1086/519795
22 https://doi.org/10.1093/molbev/mst099
23 https://doi.org/10.1101/gr.094052.109
24 https://doi.org/10.1111/j.1558-5646.1967.tb03411.x
25 https://doi.org/10.1126/science.1188021
26 https://doi.org/10.1126/science.1216304
27 https://doi.org/10.1126/science.1253448
28 https://doi.org/10.1126/science.aaa0114
29 https://doi.org/10.1126/science.aao6266
30 https://doi.org/10.1145/1143844.1143859
31 https://doi.org/10.1145/2133806.2133826
32 https://doi.org/10.1534/genetics.112.145037
33 https://doi.org/10.1534/genetics.114.164350
34 https://doi.org/10.1534/genetics.115.183913
35 https://doi.org/10.1561/2200000001
36 schema:datePublished 2018
37 schema:datePublishedReg 2018-01-01
38 schema:description Methods for inferring population structure from genetic information traditionally assume samples are contemporary. Yet, the increasing availability of ancient DNA sequences begs revision of this paradigm. We present Dystruct (Dynamic Structure), a framework and toolbox for inference of shared ancestry from data that include ancient DNA. By explicitly modeling population history and genetic drift as a time-series, Dystruct more accurately and realistically discovers shared ancestry from ancient and contemporary samples. Formally, we use a normal approximation of drift, which allows a novel, efficient algorithm for optimizing model parameters using stochastic variational inference. We show that Dystruct outperforms the state of the art when individuals are sampled over time, as is common in ancient DNA datasets. We further demonstrate the utility of our method on a dataset of 92 ancient samples alongside 1941 modern ones genotyped at 222755 loci. Our model tends to present modern samples as the mixtures of ancestral populations they really are, rather than the artifactual converse of presenting ancestral samples as mixtures of contemporary groups.
39 schema:editor N05eb563a136443f9a11100cb7b6940ec
40 schema:genre chapter
41 schema:inLanguage en
42 schema:isAccessibleForFree false
43 schema:isPartOf N51ca0efe5f84457c82b5f366b786a232
44 schema:name Inference of Population Structure from Ancient DNA
45 schema:pagination 90-104
46 schema:productId N5a884a0a9ff84d08b2e74133bdaeae36
47 Na4c5f465fd5341358cc27865fb5052a9
48 Nb59e70dc43d749baa2a94940b696c156
49 schema:publisher N62b5b777a19741a78d0e597a7de16735
50 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103403000
51 https://doi.org/10.1007/978-3-319-89929-9_6
52 schema:sdDatePublished 2019-04-15T11:45
53 schema:sdLicense https://scigraph.springernature.com/explorer/license/
54 schema:sdPublisher N78db1a8bd43f4a32a3edc36c703bce27
55 schema:url http://link.springer.com/10.1007/978-3-319-89929-9_6
56 sgo:license sg:explorer/license/
57 sgo:sdDataset chapters
58 rdf:type schema:Chapter
59 N05eb563a136443f9a11100cb7b6940ec rdf:first N2ce9ba95c15c4d30998ae56f78114125
60 rdf:rest rdf:nil
61 N2ce9ba95c15c4d30998ae56f78114125 schema:familyName Raphael
62 schema:givenName Benjamin J.
63 rdf:type schema:Person
64 N2e95c8d44b5c46d8b0fe29050266e9e4 rdf:first sg:person.012444370414.30
65 rdf:rest Nb77b34da46c046a19bd2a2d2f95f4ab4
66 N51ca0efe5f84457c82b5f366b786a232 schema:isbn 978-3-319-89928-2
67 978-3-319-89929-9
68 schema:name Research in Computational Molecular Biology
69 rdf:type schema:Book
70 N5a884a0a9ff84d08b2e74133bdaeae36 schema:name dimensions_id
71 schema:value pub.1103403000
72 rdf:type schema:PropertyValue
73 N62b5b777a19741a78d0e597a7de16735 schema:location Cham
74 schema:name Springer International Publishing
75 rdf:type schema:Organisation
76 N78db1a8bd43f4a32a3edc36c703bce27 schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 Na4c5f465fd5341358cc27865fb5052a9 schema:name readcube_id
79 schema:value 37d75b6cb59e16ef6483916c8bb201a231fcfe65cb7f41e9c18b366cbd216c49
80 rdf:type schema:PropertyValue
81 Nb59e70dc43d749baa2a94940b696c156 schema:name doi
82 schema:value 10.1007/978-3-319-89929-9_6
83 rdf:type schema:PropertyValue
84 Nb77b34da46c046a19bd2a2d2f95f4ab4 rdf:first sg:person.014337342227.51
85 rdf:rest rdf:nil
86 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
87 schema:name Biological Sciences
88 rdf:type schema:DefinedTerm
89 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
90 schema:name Genetics
91 rdf:type schema:DefinedTerm
92 sg:grant.3131789 http://pending.schema.org/fundedItem sg:pub.10.1007/978-3-319-89929-9_6
93 rdf:type schema:MonetaryGrant
94 sg:grant.4179348 http://pending.schema.org/fundedItem sg:pub.10.1007/978-3-319-89929-9_6
95 rdf:type schema:MonetaryGrant
96 sg:grant.5301960 http://pending.schema.org/fundedItem sg:pub.10.1007/978-3-319-89929-9_6
97 rdf:type schema:MonetaryGrant
98 sg:person.012444370414.30 schema:affiliation https://www.grid.ac/institutes/grid.21729.3f
99 schema:familyName Joseph
100 schema:givenName Tyler A.
101 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012444370414.30
102 rdf:type schema:Person
103 sg:person.014337342227.51 schema:affiliation https://www.grid.ac/institutes/grid.21729.3f
104 schema:familyName Pe’er
105 schema:givenName Itsik
106 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014337342227.51
107 rdf:type schema:Person
108 sg:pub.10.1023/a:1007665907178 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025979677
109 https://doi.org/10.1023/a:1007665907178
110 rdf:type schema:CreativeWork
111 sg:pub.10.1038/nature08835 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021776500
112 https://doi.org/10.1038/nature08835
113 rdf:type schema:CreativeWork
114 sg:pub.10.1038/nature09710 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050205294
115 https://doi.org/10.1038/nature09710
116 rdf:type schema:CreativeWork
117 sg:pub.10.1038/nature12736 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014659896
118 https://doi.org/10.1038/nature12736
119 rdf:type schema:CreativeWork
120 sg:pub.10.1038/nature12886 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016472358
121 https://doi.org/10.1038/nature12886
122 rdf:type schema:CreativeWork
123 sg:pub.10.1038/nature12960 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048008000
124 https://doi.org/10.1038/nature12960
125 rdf:type schema:CreativeWork
126 sg:pub.10.1038/nature13673 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047142949
127 https://doi.org/10.1038/nature13673
128 rdf:type schema:CreativeWork
129 sg:pub.10.1038/nature13810 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020730897
130 https://doi.org/10.1038/nature13810
131 rdf:type schema:CreativeWork
132 sg:pub.10.1038/nature14317 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046463951
133 https://doi.org/10.1038/nature14317
134 rdf:type schema:CreativeWork
135 sg:pub.10.1038/nature14507 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027303071
136 https://doi.org/10.1038/nature14507
137 rdf:type schema:CreativeWork
138 sg:pub.10.1038/nature17993 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024096700
139 https://doi.org/10.1038/nature17993
140 rdf:type schema:CreativeWork
141 sg:pub.10.1038/nature21347 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029627482
142 https://doi.org/10.1038/nature21347
143 rdf:type schema:CreativeWork
144 sg:pub.10.1038/ncomms1701 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018056965
145 https://doi.org/10.1038/ncomms1701
146 rdf:type schema:CreativeWork
147 sg:pub.10.1038/ncomms6257 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037347132
148 https://doi.org/10.1038/ncomms6257
149 rdf:type schema:CreativeWork
150 sg:pub.10.1038/ng.3710 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020695814
151 https://doi.org/10.1038/ng.3710
152 rdf:type schema:CreativeWork
153 https://app.dimensions.ai/details/publication/pub.1074647594 schema:CreativeWork
154 https://doi.org/10.1080/01621459.2017.1285773 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084157900
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1086/519795 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019061180
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1093/molbev/mst099 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052811713
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1101/gr.094052.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010760027
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1111/j.1558-5646.1967.tb03411.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1085728641
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1126/science.1188021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002597304
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1126/science.1216304 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016746627
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1126/science.1253448 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062469963
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1126/science.aaa0114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011366467
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1126/science.aao6266 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092036091
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1145/1143844.1143859 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018244254
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1145/2133806.2133826 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012425283
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1534/genetics.112.145037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006334147
179 rdf:type schema:CreativeWork
180 https://doi.org/10.1534/genetics.114.164350 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048824135
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1534/genetics.115.183913 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028394547
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1561/2200000001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068001396
185 rdf:type schema:CreativeWork
186 https://www.grid.ac/institutes/grid.21729.3f schema:alternateName Columbia University
187 schema:name Columbia University
188 rdf:type schema:Organization
 




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


...