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Article: Multiple testing and power calculations in genetic association studies

TitleMultiple testing and power calculations in genetic association studies
Authors
Issue Date2011
PublisherCold Spring Harbor Laboratory Press. The Journal's web site is located at http://cshprotocols.cshlp.org/
Citation
Cold Spring Harbor Protocols, 2011, v. 6 n. 1 How to Cite?
AbstractModern genetic association studies typically involve multiple single-nucleotide polymorphisms (SNPs) and/or multiple genes. With the development of high-throughput genotyping technologies and the reduction in genotyping cost, investigators can now assay up to a million SNPs for direct or indirect association with disease phenotypes. In addition, some studies involve multiple disease or related phenotypes and use multiple methods of statistical analysis. The combination of multiple genetic loci, multiple phenotypes, and multiple methods of evaluating associations between genotype and phenotype means that modern genetic studies often involve the testing of an enormous number of hypotheses. When multiple hypothesis tests are performed in a study, there is a risk of inflation of the type I error rate (i.e., the chance of falsely claiming an association when there is none). Several methods for multiple-testing correction are in popular use, and they all have strengths and weaknesses. Because no single method is universally adopted or always appropriate, it is important to understand the principles, strengths, and weaknesses of the methods so that they can be applied appropriately in practice. In this article, we review the three principle methods for multiple-testing correction and provide guidance for calculating statistical power.
Persistent Identifierhttp://hdl.handle.net/10722/137519
ISSN
2015 SCImago Journal Rankings: 0.673
References

 

DC FieldValueLanguage
dc.contributor.authorSo, HCen_HK
dc.contributor.authorSham, PCen_HK
dc.date.accessioned2011-08-26T14:26:55Z-
dc.date.available2011-08-26T14:26:55Z-
dc.date.issued2011en_HK
dc.identifier.citationCold Spring Harbor Protocols, 2011, v. 6 n. 1en_HK
dc.identifier.issn1559-6095en_HK
dc.identifier.urihttp://hdl.handle.net/10722/137519-
dc.description.abstractModern genetic association studies typically involve multiple single-nucleotide polymorphisms (SNPs) and/or multiple genes. With the development of high-throughput genotyping technologies and the reduction in genotyping cost, investigators can now assay up to a million SNPs for direct or indirect association with disease phenotypes. In addition, some studies involve multiple disease or related phenotypes and use multiple methods of statistical analysis. The combination of multiple genetic loci, multiple phenotypes, and multiple methods of evaluating associations between genotype and phenotype means that modern genetic studies often involve the testing of an enormous number of hypotheses. When multiple hypothesis tests are performed in a study, there is a risk of inflation of the type I error rate (i.e., the chance of falsely claiming an association when there is none). Several methods for multiple-testing correction are in popular use, and they all have strengths and weaknesses. Because no single method is universally adopted or always appropriate, it is important to understand the principles, strengths, and weaknesses of the methods so that they can be applied appropriately in practice. In this article, we review the three principle methods for multiple-testing correction and provide guidance for calculating statistical power.en_US
dc.languageengen_US
dc.publisherCold Spring Harbor Laboratory Press. The Journal's web site is located at http://cshprotocols.cshlp.org/-
dc.relation.ispartofCold Spring Harbor Protocolsen_HK
dc.subject.meshBiostatistics - methodsen_US
dc.subject.meshGenetic Association Studies - methodsen_US
dc.subject.meshHigh-Throughput Screening Assays - methodsen_US
dc.subject.meshPolymorphism, Single Nucleotideen_US
dc.titleMultiple testing and power calculations in genetic association studiesen_HK
dc.typeArticleen_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1101/pdb.top95en_HK
dc.identifier.pmid21205861en_US
dc.identifier.scopuseid_2-s2.0-78651442508en_HK
dc.identifier.hkuros189865en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78651442508&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6en_HK
dc.identifier.issue1en_HK
dc.identifier.spage7en_US
dc.identifier.epage16en_US
dc.publisher.placeUnited States-
dc.identifier.scopusauthoridSo, HC=37031934700en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK

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