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ComPaSS-GWAS: A method to reduce type I error in genome-wide association studies when replication data are not available.

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Title: ComPaSS-GWAS: A method to reduce type I error in genome-wide association studies when replication data are not available.
Authors: Sabourin JA; Genometrics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland., Cropp CD; Statistical Genetics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland.; Integrated Cancer Genomics Division, Translational Genomics Research Institute (TGen), Phoenix, Arizona.; McWhorter School of Pharmacy, Samford University, Birmingham, Alabama., Sung H; Genometrics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland., Brody LC; Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Bethesda, Maryland., Bailey-Wilson JE; Statistical Genetics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland., Wilson AF; Genometrics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland.
Source: Genetic epidemiology [Genet Epidemiol] 2019 Feb; Vol. 43 (1), pp. 102-111. Date of Electronic Publication: 2018 Oct 18.
Publication Type: Journal Article; Research Support, N.I.H., Intramural
Journal Info: Publisher: Wiley-Liss Country of Publication: United States NLM ID: 8411723 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1098-2272 (Electronic) Linking ISSN: 07410395 NLM ISO Abbreviation: Genet Epidemiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Sabourin+JA%22">Sabourin JA</searchLink>; Genometrics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland.<br /><searchLink fieldCode="AU" term="%22Cropp+CD%22">Cropp CD</searchLink>; Statistical Genetics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland.; Integrated Cancer Genomics Division, Translational Genomics Research Institute (TGen), Phoenix, Arizona.; McWhorter School of Pharmacy, Samford University, Birmingham, Alabama.<br /><searchLink fieldCode="AU" term="%22Sung+H%22">Sung H</searchLink>; Genometrics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland.<br /><searchLink fieldCode="AU" term="%22Brody+LC%22">Brody LC</searchLink>; Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Bethesda, Maryland.<br /><searchLink fieldCode="AU" term="%22Bailey-Wilson+JE%22">Bailey-Wilson JE</searchLink>; Statistical Genetics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland.<br /><searchLink fieldCode="AU" term="%22Wilson+AF%22">Wilson AF</searchLink>; Genometrics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute/National Institutes of Health (NHGRI/NIH), Baltimore, Maryland.
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  Data: <searchLink fieldCode="JN" term="%228411723%22">Genetic epidemiology</searchLink> [Genet Epidemiol] 2019 Feb; Vol. 43 (1), pp. 102-111. <i>Date of Electronic Publication: </i>2018 Oct 18.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley-Liss%22">Wiley-Liss </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>8411723 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1098-2272 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2207410395%22">07410395 </searchLink><i>NLM ISO Abbreviation: </i>Genet Epidemiol <i>Subsets: </i>MEDLINE
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        Value: 10.1002/gepi.22168
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      – TitleFull: ComPaSS-GWAS: A method to reduce type I error in genome-wide association studies when replication data are not available.
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              Text: 2019 Feb
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