Linear mixed models for association analysis of quantitative traits with next-generation sequencing data.
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| Title: | Linear mixed models for association analysis of quantitative traits with next-generation sequencing data. |
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| Authors: | Chiu CY; Division of Biostatistics, Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee.; Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, Maryland., Yuan F; Department of Biochemistry and Molecular Biology, School of Basic Medicine, Kunming Medical University, Kunming, Yunnan, China., Zhang BS; Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, District of Columbia., Yuan A; Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, District of Columbia., Li X; Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, District of Columbia., Fang HB; Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, District of Columbia., Lange K; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California., Weeks DE; Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.; Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania., Wilson AF; Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, Maryland., Bailey-Wilson JE; Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, Maryland., Musolf AM; Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, Maryland., Stambolian D; Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania., Lakhal-Chaieb ML; Department de Mathematiques et de Statistique, Universite Laval, Quebec, Canada., Cook RJ; Department of Statistics and Actuarial Science, Waterloo, Ontario, Quebec, Canada., McMahon FJ; Human Genetics Branch and Genetic Basis of Mood and Anxiety Disorders Section, University of Waterloo, National Institute of Mental Health, NIH, Bethesda, Maryland., Amos CI; Department of Medicine, Baylor College of Medicine, Houston, Texas., Xiong M; Human Genetics Center, University of Texas-Houston, Houston, Texas., Fan R; Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, Maryland.; Department of Biochemistry and Molecular Biology, School of Basic Medicine, Kunming Medical University, Kunming, Yunnan, China. |
| Source: | Genetic epidemiology [Genet Epidemiol] 2019 Mar; Vol. 43 (2), pp. 189-206. Date of Electronic Publication: 2018 Dec 09. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, N.I.H., Intramural; Research Support, Non-U.S. Gov't |
| 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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| ISSN: | 1098-2272 |
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| DOI: | 10.1002/gepi.22177 |
