Genomic screening in family-based association testing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2005-12

AUTHORS

Amy Murphy, Matthew B McQueen, Jessica Su, Peter Kraft, Ross Lazarus, Nan M Laird, Christoph Lange, Kristel Van Steen

ABSTRACT

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p = 0.004) and ttth1-ttth4 (p = 0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association. More... »

PAGES

s115

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2156-6-s1-s115

DOI

http://dx.doi.org/10.1186/1471-2156-6-s1-s115

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1037942527

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16451572


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": "Family", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genetic Testing", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genome, Human", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genome-Wide Association Study", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phenotype", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Biostatistics, Harvard School of Public Health, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Murphy", 
        "givenName": "Amy", 
        "id": "sg:person.01047505230.76", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01047505230.76"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Epidemiology, Harvard School of Public Health, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "McQueen", 
        "givenName": "Matthew B", 
        "id": "sg:person.013502425777.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013502425777.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Epidemiology, Harvard School of Public Health, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Su", 
        "givenName": "Jessica", 
        "id": "sg:person.01262023142.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262023142.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Biostatistics, Harvard School of Public Health, 02115, Boston, MA, USA", 
            "Department of Epidemiology, Harvard School of Public Health, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kraft", 
        "givenName": "Peter", 
        "id": "sg:person.01347664403.23", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01347664403.23"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Channing Laboratory, Harvard Medical School, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lazarus", 
        "givenName": "Ross", 
        "id": "sg:person.0766744011.63", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0766744011.63"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Biostatistics, Harvard School of Public Health, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Laird", 
        "givenName": "Nan M", 
        "id": "sg:person.01205773172.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205773172.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Biostatistics, Harvard School of Public Health, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lange", 
        "givenName": "Christoph", 
        "id": "sg:person.01342332616.87", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01342332616.87"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Department of Biostatistics, Harvard School of Public Health, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Van Steen", 
        "givenName": "Kristel", 
        "id": "sg:person.01320666741.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01320666741.12"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/(sici)1096-8628(19980508)81:3<207::aid-ajmg1>3.0.co;2-t", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007537499"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2202/1544-6115.1067", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010341877"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biostatistics/4.2.195", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013189896"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000073728", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014451174"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0301-0511(02)00060-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021129875"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000022920", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023900772"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1582", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025472883", 
          "https://doi.org/10.1038/ng1582"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1582", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025472883", 
          "https://doi.org/10.1038/ng1582"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1582", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025472883", 
          "https://doi.org/10.1038/ng1582"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/gepi.209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029825845"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.052716399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030019385"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/1098-2272(2000)19:1+<::aid-gepi6>3.0.co;2-m", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032977743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000022918", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040138305"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/378591", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058671624"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/378591", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058671624"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/381563", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058673343"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2005-12", 
    "datePublishedReg": "2005-12-01", 
    "description": "Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p = 0.004) and ttth1-ttth4 (p = 0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/1471-2156-6-s1-s115", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2685195", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2528020", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1024251", 
        "issn": [
          "1471-2156"
        ], 
        "name": "BMC Genetics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "Suppl 1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "6"
      }
    ], 
    "name": "Genomic screening in family-based association testing", 
    "pagination": "s115", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b4bee9c66287c8ee03cfa6b4d9771fb46fe836fd4a4d55f1960fb1d753703766"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "16451572"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100966978"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1471-2156-6-s1-s115"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1037942527"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1471-2156-6-s1-s115", 
      "https://app.dimensions.ai/details/publication/pub.1037942527"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T15:50", 
    "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_8664_00000506.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2F1471-2156-6-S1-S115"
  }
]
 

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.10.1186/1471-2156-6-s1-s115'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2156-6-s1-s115'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2156-6-s1-s115'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2156-6-s1-s115'


 

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

187 TRIPLES      21 PREDICATES      48 URIs      27 LITERALS      15 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1471-2156-6-s1-s115 schema:about N094c71a561ea4f62944f7fd975ee1544
2 N1af4cf7fdced4784bdaa124963285ed5
3 N22040d5db38f40eb863e1c9418048465
4 N5f0790b334a548c2885543c55ec5bf42
5 N6a14cd6e6d5b440d8ab544c544528610
6 Nbbea1995fb3e4ffe8089b29f749ce729
7 anzsrc-for:06
8 anzsrc-for:0604
9 schema:author N4905df1a319744b7ab9a9a0dc62dc1e0
10 schema:citation sg:pub.10.1038/ng1582
11 https://doi.org/10.1002/(sici)1096-8628(19980508)81:3<207::aid-ajmg1>3.0.co;2-t
12 https://doi.org/10.1002/1098-2272(2000)19:1+<::aid-gepi6>3.0.co;2-m
13 https://doi.org/10.1002/gepi.209
14 https://doi.org/10.1016/s0301-0511(02)00060-1
15 https://doi.org/10.1073/pnas.052716399
16 https://doi.org/10.1086/378591
17 https://doi.org/10.1086/381563
18 https://doi.org/10.1093/biostatistics/4.2.195
19 https://doi.org/10.1159/000022918
20 https://doi.org/10.1159/000022920
21 https://doi.org/10.1159/000073728
22 https://doi.org/10.2202/1544-6115.1067
23 schema:datePublished 2005-12
24 schema:datePublishedReg 2005-12-01
25 schema:description Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p = 0.004) and ttth1-ttth4 (p = 0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association.
26 schema:genre research_article
27 schema:inLanguage en
28 schema:isAccessibleForFree true
29 schema:isPartOf N3b705a455c784625bbc287fa6867fca5
30 Nc45e6977d1794c3cbeb5c02123757d98
31 sg:journal.1024251
32 schema:name Genomic screening in family-based association testing
33 schema:pagination s115
34 schema:productId N33584f88db9646149f1ae77c53cdf9dc
35 N3dc85fc2b893418789f13f1714457793
36 N902ec15a3a7f4d1c94da0027f3b6941c
37 Nd19fb826f79d484488e57b7be51a4ad1
38 Nf110e7017a8b43298f5bdf301aebd4ca
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037942527
40 https://doi.org/10.1186/1471-2156-6-s1-s115
41 schema:sdDatePublished 2019-04-10T15:50
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher N000921d6759e4ba59b023dd762d6bcd7
44 schema:url http://link.springer.com/10.1186%2F1471-2156-6-S1-S115
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N000921d6759e4ba59b023dd762d6bcd7 schema:name Springer Nature - SN SciGraph project
49 rdf:type schema:Organization
50 N094c71a561ea4f62944f7fd975ee1544 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
51 schema:name Genome-Wide Association Study
52 rdf:type schema:DefinedTerm
53 N0e1c2f50014842edace4878b239e01b6 rdf:first sg:person.01342332616.87
54 rdf:rest N8f604f3062304bfc87ffbf9c43f87d99
55 N1af4cf7fdced4784bdaa124963285ed5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
56 schema:name Family
57 rdf:type schema:DefinedTerm
58 N22040d5db38f40eb863e1c9418048465 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
59 schema:name Genome, Human
60 rdf:type schema:DefinedTerm
61 N33584f88db9646149f1ae77c53cdf9dc schema:name dimensions_id
62 schema:value pub.1037942527
63 rdf:type schema:PropertyValue
64 N3b705a455c784625bbc287fa6867fca5 schema:issueNumber Suppl 1
65 rdf:type schema:PublicationIssue
66 N3dc85fc2b893418789f13f1714457793 schema:name pubmed_id
67 schema:value 16451572
68 rdf:type schema:PropertyValue
69 N4905df1a319744b7ab9a9a0dc62dc1e0 rdf:first sg:person.01047505230.76
70 rdf:rest N6d0085725a264da09c3963ce7167e2d9
71 N4f65eb3bdcb74f6387043275e562d70f rdf:first sg:person.01347664403.23
72 rdf:rest N973fff64adfc4d9c8d2f57c2425d713a
73 N5f0790b334a548c2885543c55ec5bf42 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
74 schema:name Genetic Testing
75 rdf:type schema:DefinedTerm
76 N6a14cd6e6d5b440d8ab544c544528610 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
77 schema:name Humans
78 rdf:type schema:DefinedTerm
79 N6d0085725a264da09c3963ce7167e2d9 rdf:first sg:person.013502425777.58
80 rdf:rest N8486e4d67c0643beb2f2f7994239dd3a
81 N8486e4d67c0643beb2f2f7994239dd3a rdf:first sg:person.01262023142.55
82 rdf:rest N4f65eb3bdcb74f6387043275e562d70f
83 N8f604f3062304bfc87ffbf9c43f87d99 rdf:first sg:person.01320666741.12
84 rdf:rest rdf:nil
85 N902ec15a3a7f4d1c94da0027f3b6941c schema:name nlm_unique_id
86 schema:value 100966978
87 rdf:type schema:PropertyValue
88 N97140fff42504ffda49caca047d0d8eb rdf:first sg:person.01205773172.25
89 rdf:rest N0e1c2f50014842edace4878b239e01b6
90 N973fff64adfc4d9c8d2f57c2425d713a rdf:first sg:person.0766744011.63
91 rdf:rest N97140fff42504ffda49caca047d0d8eb
92 Nbbea1995fb3e4ffe8089b29f749ce729 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Phenotype
94 rdf:type schema:DefinedTerm
95 Nc45e6977d1794c3cbeb5c02123757d98 schema:volumeNumber 6
96 rdf:type schema:PublicationVolume
97 Nd19fb826f79d484488e57b7be51a4ad1 schema:name doi
98 schema:value 10.1186/1471-2156-6-s1-s115
99 rdf:type schema:PropertyValue
100 Nf110e7017a8b43298f5bdf301aebd4ca schema:name readcube_id
101 schema:value b4bee9c66287c8ee03cfa6b4d9771fb46fe836fd4a4d55f1960fb1d753703766
102 rdf:type schema:PropertyValue
103 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
104 schema:name Biological Sciences
105 rdf:type schema:DefinedTerm
106 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
107 schema:name Genetics
108 rdf:type schema:DefinedTerm
109 sg:grant.2528020 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2156-6-s1-s115
110 rdf:type schema:MonetaryGrant
111 sg:grant.2685195 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2156-6-s1-s115
112 rdf:type schema:MonetaryGrant
113 sg:journal.1024251 schema:issn 1471-2156
114 schema:name BMC Genetics
115 rdf:type schema:Periodical
116 sg:person.01047505230.76 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
117 schema:familyName Murphy
118 schema:givenName Amy
119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01047505230.76
120 rdf:type schema:Person
121 sg:person.01205773172.25 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
122 schema:familyName Laird
123 schema:givenName Nan M
124 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205773172.25
125 rdf:type schema:Person
126 sg:person.01262023142.55 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
127 schema:familyName Su
128 schema:givenName Jessica
129 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262023142.55
130 rdf:type schema:Person
131 sg:person.01320666741.12 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
132 schema:familyName Van Steen
133 schema:givenName Kristel
134 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01320666741.12
135 rdf:type schema:Person
136 sg:person.01342332616.87 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
137 schema:familyName Lange
138 schema:givenName Christoph
139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01342332616.87
140 rdf:type schema:Person
141 sg:person.01347664403.23 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
142 schema:familyName Kraft
143 schema:givenName Peter
144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01347664403.23
145 rdf:type schema:Person
146 sg:person.013502425777.58 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
147 schema:familyName McQueen
148 schema:givenName Matthew B
149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013502425777.58
150 rdf:type schema:Person
151 sg:person.0766744011.63 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
152 schema:familyName Lazarus
153 schema:givenName Ross
154 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0766744011.63
155 rdf:type schema:Person
156 sg:pub.10.1038/ng1582 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025472883
157 https://doi.org/10.1038/ng1582
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1002/(sici)1096-8628(19980508)81:3<207::aid-ajmg1>3.0.co;2-t schema:sameAs https://app.dimensions.ai/details/publication/pub.1007537499
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1002/1098-2272(2000)19:1+<::aid-gepi6>3.0.co;2-m schema:sameAs https://app.dimensions.ai/details/publication/pub.1032977743
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1002/gepi.209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029825845
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/s0301-0511(02)00060-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021129875
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1073/pnas.052716399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030019385
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1086/378591 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058671624
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1086/381563 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058673343
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1093/biostatistics/4.2.195 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013189896
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1159/000022918 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040138305
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1159/000022920 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023900772
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1159/000073728 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014451174
180 rdf:type schema:CreativeWork
181 https://doi.org/10.2202/1544-6115.1067 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010341877
182 rdf:type schema:CreativeWork
183 https://www.grid.ac/institutes/grid.38142.3c schema:alternateName Harvard University
184 schema:name Channing Laboratory, Harvard Medical School, 02115, Boston, MA, USA
185 Department of Biostatistics, Harvard School of Public Health, 02115, Boston, MA, USA
186 Department of Epidemiology, Harvard School of Public Health, 02115, Boston, MA, USA
187 rdf:type schema:Organization
 




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


...