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dc.contributor.authorChang, Christine Q.
dc.contributor.authorYesupriya, Ajay
dc.contributor.authorRowell, Jessica L.
dc.contributor.authorPimentel, Camilla B.
dc.contributor.authorClyne, Melinda
dc.contributor.authorGwinn, Marta
dc.contributor.authorKhoury, Muin J.
dc.contributor.authorWulf, Anja
dc.contributor.authorSchully, Sheri D.
dc.date2022-08-11T08:08:30.000
dc.date.accessioned2022-08-23T15:57:28Z
dc.date.available2022-08-23T15:57:28Z
dc.date.issued2014-03-01
dc.date.submitted2014-10-24
dc.identifier.citationEur J Hum Genet. 2014 Mar;22(3):402-8. doi: 10.1038/ejhg.2013.161. <a href="http://dx.doi.org/10.1038/ejhg.2013.161">Link to article on publisher's site</a>
dc.identifier.issn1018-4813 (Linking)
dc.identifier.doi10.1038/ejhg.2013.161
dc.identifier.pmid23881057
dc.identifier.urihttp://hdl.handle.net/20.500.14038/30204
dc.description.abstractCandidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=23881057&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://dx.doi.org/10.1038/ejhg.2013.161
dc.subjectCase-Control Studies
dc.subject*Genome-Wide Association Study
dc.subjectHumans
dc.subjectNeoplasms
dc.subjectCancer Biology
dc.subjectGenomics
dc.subjectMolecular Genetics
dc.subjectNeoplasms
dc.titleA systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes
dc.typeJournal Article
dc.source.journaltitleEuropean journal of human genetics : EJHG
dc.source.volume22
dc.source.issue3
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/450
dc.identifier.contextkey6282104
html.description.abstract<p>Candidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities</p>
dc.identifier.submissionpathfaculty_pubs/450
dc.contributor.departmentGraduate School of Biomedical Sciences, Clinical and Population Health Research Program
dc.source.pages402-8


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