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- Publisher Website: 10.1002/gepi.21898
- Scopus: eid_2-s2.0-84934441755
- PMID: 25995121
- WOS: WOS:000356363800008
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Article: SPS: a simulation tool for calculating power of set-based genetic association tests
Title | SPS: a simulation tool for calculating power of set-based genetic association tests |
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Authors | |
Keywords | Complex disease Meta-analysis Power Set-based association test Simulation |
Issue Date | 2015 |
Publisher | John Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841 |
Citation | Genetic Epidemiology, 2015, v. 39 n. 5, p. 395-397 How to Cite? |
Abstract | Set-based association tests, combining a set of single-nucleotide polymorphisms into a unified test, have become important approaches to identify weak-effect or low-frequency risk loci of complex diseases. However, there is no comprehensive and user-friendly tool to estimate power of set-based tests for study design. We developed a simulation tool to estimate statistical power of multiple representative set-based tests (SPS). SPS has a graphic interface to facilitate parameter settings and result visualization. Advanced functions include loading real genotypes to define genetic architecture, set-based meta-analysis for risk loci with or without heterogeneity, and parallel simulations. In proof-of-principle examples, SPS took no more than 3 sec on average to estimate the power in a conventional setting. The SPS has been integrated into a user-friendly software tool (KGG) as an independent functional module and it is freely available at http://statgenpro.psychiatry.hku.hk/limx/kgg/. © 2015 WILEY PERIODICALS, INC. |
Description | Brief Report |
Persistent Identifier | http://hdl.handle.net/10722/210226 |
ISSN | 2023 Impact Factor: 1.7 2023 SCImago Journal Rankings: 0.977 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, J | - |
dc.contributor.author | Sham, PC | - |
dc.contributor.author | Song, Y | - |
dc.contributor.author | Li, M | - |
dc.date.accessioned | 2015-05-29T01:48:40Z | - |
dc.date.available | 2015-05-29T01:48:40Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Genetic Epidemiology, 2015, v. 39 n. 5, p. 395-397 | - |
dc.identifier.issn | 0741-0395 | - |
dc.identifier.uri | http://hdl.handle.net/10722/210226 | - |
dc.description | Brief Report | - |
dc.description.abstract | Set-based association tests, combining a set of single-nucleotide polymorphisms into a unified test, have become important approaches to identify weak-effect or low-frequency risk loci of complex diseases. However, there is no comprehensive and user-friendly tool to estimate power of set-based tests for study design. We developed a simulation tool to estimate statistical power of multiple representative set-based tests (SPS). SPS has a graphic interface to facilitate parameter settings and result visualization. Advanced functions include loading real genotypes to define genetic architecture, set-based meta-analysis for risk loci with or without heterogeneity, and parallel simulations. In proof-of-principle examples, SPS took no more than 3 sec on average to estimate the power in a conventional setting. The SPS has been integrated into a user-friendly software tool (KGG) as an independent functional module and it is freely available at http://statgenpro.psychiatry.hku.hk/limx/kgg/. © 2015 WILEY PERIODICALS, INC. | - |
dc.language | eng | - |
dc.publisher | John Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841 | - |
dc.relation.ispartof | Genetic Epidemiology | - |
dc.rights | Genetic Epidemiology. Copyright © John Wiley & Sons, Inc. | - |
dc.subject | Complex disease | - |
dc.subject | Meta-analysis | - |
dc.subject | Power | - |
dc.subject | Set-based association test | - |
dc.subject | Simulation | - |
dc.title | SPS: a simulation tool for calculating power of set-based genetic association tests | - |
dc.type | Article | - |
dc.identifier.email | Sham, PC: pcsham@hku.hk | - |
dc.identifier.email | Song, Y: songy@hku.hk | - |
dc.identifier.email | Li, M: mxli@hku.hk | - |
dc.identifier.authority | Sham, PC=rp00459 | - |
dc.identifier.authority | Song, Y=rp00488 | - |
dc.identifier.authority | Li, M=rp01722 | - |
dc.identifier.doi | 10.1002/gepi.21898 | - |
dc.identifier.pmid | 25995121 | - |
dc.identifier.scopus | eid_2-s2.0-84934441755 | - |
dc.identifier.hkuros | 246407 | - |
dc.identifier.isi | WOS:000356363800008 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0741-0395 | - |