Ontology type: schema:ScholarlyArticle Open Access: True
2018-12
AUTHORSNicholas Mancuso, Simon Gayther, Alexander Gusev, Wei Zheng, Kathryn L. Penney, Zsofia Kote-Jarai, Rosalind Eeles, Matthew Freedman, Christopher Haiman, Bogdan Pasaniuc,
ABSTRACTAlthough genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N = 142,392) with gene expression measured in 45 tissues (N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level; this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci. More... »
PAGES4079
http://scigraph.springernature.com/pub.10.1038/s41467-018-06302-1
DOIhttp://dx.doi.org/10.1038/s41467-018-06302-1
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1107306502
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30287866
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": "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": "Male",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Prostatic Neoplasms",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Transcriptome",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of California Los Angeles",
"id": "https://www.grid.ac/institutes/grid.19006.3e",
"name": [
"Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, 90095 CA USA"
],
"type": "Organization"
},
"familyName": "Mancuso",
"givenName": "Nicholas",
"id": "sg:person.01062062720.41",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01062062720.41"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Cedars-Sinai Medical Center",
"id": "https://www.grid.ac/institutes/grid.50956.3f",
"name": [
"The Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, 90048 CA USA"
],
"type": "Organization"
},
"familyName": "Gayther",
"givenName": "Simon",
"id": "sg:person.0634761502.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0634761502.26"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Dana\u2013Farber Cancer Institute",
"id": "https://www.grid.ac/institutes/grid.65499.37",
"name": [
"Dana Farber Cancer Institute, Boston, 02215 MA USA"
],
"type": "Organization"
},
"familyName": "Gusev",
"givenName": "Alexander",
"id": "sg:person.01047400610.27",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01047400610.27"
],
"type": "Person"
},
{
"affiliation": {
"name": [
"Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, 37232 TN USA"
],
"type": "Organization"
},
"familyName": "Zheng",
"givenName": "Wei",
"id": "sg:person.016425765167.70",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016425765167.70"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Brigham and Women's Hospital",
"id": "https://www.grid.ac/institutes/grid.62560.37",
"name": [
"Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115 MA USA",
"Channing Division of Network Medicine, Department of Medicine, Brigham and Women\u2019s Hospital/Harvard Medical School, Boston, 02115 MA USA"
],
"type": "Organization"
},
"familyName": "Penney",
"givenName": "Kathryn L.",
"id": "sg:person.01344544062.36",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01344544062.36"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal Marsden NHS Foundation Trust",
"id": "https://www.grid.ac/institutes/grid.5072.0",
"name": [
"Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP UK",
"Royal Marsden NHS Foundation Trust, London, SW3 6JJ UK"
],
"type": "Organization"
},
"familyName": "Kote-Jarai",
"givenName": "Zsofia",
"id": "sg:person.01157661566.11",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01157661566.11"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal Marsden NHS Foundation Trust",
"id": "https://www.grid.ac/institutes/grid.5072.0",
"name": [
"Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP UK",
"Royal Marsden NHS Foundation Trust, London, SW3 6JJ UK"
],
"type": "Organization"
},
"familyName": "Eeles",
"givenName": "Rosalind",
"id": "sg:person.010370267737.55",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010370267737.55"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Dana\u2013Farber Cancer Institute",
"id": "https://www.grid.ac/institutes/grid.65499.37",
"name": [
"Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, 02215 MA USA"
],
"type": "Organization"
},
"familyName": "Freedman",
"givenName": "Matthew",
"id": "sg:person.0756242177.53",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0756242177.53"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Southern California",
"id": "https://www.grid.ac/institutes/grid.42505.36",
"name": [
"Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, 90015 CA USA"
],
"type": "Organization"
},
"familyName": "Haiman",
"givenName": "Christopher",
"id": "sg:person.012607214677.06",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012607214677.06"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of California Los Angeles",
"id": "https://www.grid.ac/institutes/grid.19006.3e",
"name": [
"Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, 90095 CA USA",
"Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, 90095 CA USA",
"Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, 90095 CA USA"
],
"type": "Organization"
},
"familyName": "Pasaniuc",
"givenName": "Bogdan",
"id": "sg:person.0737513674.23",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0737513674.23"
],
"type": "Person"
},
{}
],
"citation": [
{
"id": "https://doi.org/10.1371/journal.pgen.1001204",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000305391"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/pros.22778",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000468311"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.115.176107",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000783574"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.115.176107",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000783574"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.452",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003124418",
"https://doi.org/10.1038/ng.452"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.452",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003124418",
"https://doi.org/10.1038/ng.452"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1006/geno.1998.5639",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003878945"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3367",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005364973",
"https://doi.org/10.1038/ng.3367"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1158/1055-9965.epi-13-0568",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006317704"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pgen.1003608",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008209705"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2337/db11-1378",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008589452"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pgen.1004958",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009545802"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1158/0008-5472.can-04-0603",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012847388"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3538",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013588188",
"https://doi.org/10.1038/ng.3538"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nm.3975",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014188936",
"https://doi.org/10.1038/nm.3975"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.1200853109",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015700985"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.2862",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016123190",
"https://doi.org/10.1038/ng.2862"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.2435",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016174016",
"https://doi.org/10.1038/ng.2435"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/humu.22909",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016683788"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1126/science.1222794",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017092582"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ncomms9653",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018273477",
"https://doi.org/10.1038/ncomms9653"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/hmg/ddu228",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018357890"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3523",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019808950",
"https://doi.org/10.1038/ng.3523"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btv240",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020585900"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature15393",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021812064",
"https://doi.org/10.1038/nature15393"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0069317",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022132081"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nn.4399",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022499785",
"https://doi.org/10.1038/nn.4399"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pgen.1000888",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022521320"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3506",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022766702",
"https://doi.org/10.1038/ng.3506"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3094",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027844356",
"https://doi.org/10.1038/ng.3094"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.2951",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028118113",
"https://doi.org/10.1038/ng.2951"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1126/science.aad9417",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028120507"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.cell.2015.10.025",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028836563"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ncomms10979",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029725277",
"https://doi.org/10.1038/ncomms10979"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pgen.1004102",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030759709"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature14248",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031836937",
"https://doi.org/10.1038/nature14248"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.2653",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032444369",
"https://doi.org/10.1038/ng.2653"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3322/caac.21332",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032745321"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pgen.1003264",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033700835"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.2764",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033967678",
"https://doi.org/10.1038/ng.2764"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2337/db08-1607",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035839534"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.181336698",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036176277"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ejhg.2013.195",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041787485",
"https://doi.org/10.1038/ejhg.2013.195"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13073-016-0338-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044314445",
"https://doi.org/10.1186/s13073-016-0338-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13073-016-0338-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044314445",
"https://doi.org/10.1186/s13073-016-0338-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13073-015-0257-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045600814",
"https://doi.org/10.1186/s13073-015-0257-9"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1001/jama.2015.17703",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045717668"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/hmg/ddv203",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046680127"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/ije/dym225",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046830839"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.90",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048595961",
"https://doi.org/10.1038/ng.90"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.2560",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049745027",
"https://doi.org/10.1038/ng.2560"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/gb-2010-11-2-r14",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050171830",
"https://doi.org/10.1186/gb-2010-11-2-r14"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3643",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050700099",
"https://doi.org/10.1038/ng.3643"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3643",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050700099",
"https://doi.org/10.1038/ng.3643"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature09298",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052674054",
"https://doi.org/10.1038/nature09298"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature09298",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052674054",
"https://doi.org/10.1038/nature09298"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1158/1055-9965.epi-14-0694-t",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052800002"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ccr.2011.10.014",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053130567"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1403494814541597",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064002373"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1403494814541597",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064002373"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3795",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083850743",
"https://doi.org/10.1038/ng.3795"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ajhg.2017.01.031",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083907151"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41588-018-0092-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1103194548",
"https://doi.org/10.1038/s41588-018-0092-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41588-018-0142-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1104478461",
"https://doi.org/10.1038/s41588-018-0142-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41588-018-0142-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1104478461",
"https://doi.org/10.1038/s41588-018-0142-8"
],
"type": "CreativeWork"
}
],
"datePublished": "2018-12",
"datePublishedReg": "2018-12-01",
"description": "Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N\u2009=\u2009142,392) with gene expression measured in 45 tissues (N\u2009=\u20094458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1\u2009Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2\u2009Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a\u00a0pre-defined level; this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.",
"genre": "research_article",
"id": "sg:pub.10.1038/s41467-018-06302-1",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isFundedItemOf": [
{
"id": "sg:grant.6618066",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2689002",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6714900",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2689005",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5140177",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6735310",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2695970",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2774057",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6715299",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2695968",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2689004",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2529444",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5135789",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2755349",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6726682",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5140627",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6735717",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5141946",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2695966",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2479403",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5141130",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6713633",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.3772173",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.4241918",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5151057",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6717255",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.3805536",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6732156",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5140591",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6712765",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6714480",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.6723910",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.2689003",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1043282",
"issn": [
"2041-1723"
],
"name": "Nature Communications",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "9"
}
],
"name": "Large-scale transcriptome-wide association study identifies new prostate cancer risk regions",
"pagination": "4079",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"682c101b977b9af820fe3e42ab758d9cbffe471389be98870d91db0e90ea2ad2"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"30287866"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"101528555"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1038/s41467-018-06302-1"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1107306502"
]
}
],
"sameAs": [
"https://doi.org/10.1038/s41467-018-06302-1",
"https://app.dimensions.ai/details/publication/pub.1107306502"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T13:17",
"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/v90/0000000368_0000000368/records_78935_00000001.jsonl",
"type": "ScholarlyArticle",
"url": "https://www.nature.com/articles/s41467-018-06302-1"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1038/s41467-018-06302-1'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41467-018-06302-1'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41467-018-06302-1'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41467-018-06302-1'
This table displays all metadata directly associated to this object as RDF triples.
443 TRIPLES
21 PREDICATES
92 URIs
26 LITERALS
14 BLANK NODES