OSCA: a tool for omic-data-based complex trait analysis
The rapid increase of omic data has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we propose a mixed-linear-model-based method called MOMENT that tests for association between a DNAm probe and tra...
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| Published in: | Genome Biology Vol. 20; no. 1; p. 107 |
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| Main Authors: | , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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28-05-2019
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| Abstract | The rapid increase of omic data has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we propose a mixed-linear-model-based method called MOMENT that tests for association between a DNAm probe and trait with all other distal probes fitted in multiple random-effect components to account for unobserved confounders. We demonstrate by simulations that MOMENT shows a lower false positive rate and more robustness than existing methods. MOMENT has been implemented in a versatile software package called OSCA together with a number of other implementations for omic-data-based analyses. |
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| AbstractList | The rapid increase of omic data has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we propose a mixed-linear-model-based method called MOMENT that tests for association between a DNAm probe and trait with all other distal probes fitted in multiple random-effect components to account for unobserved confounders. We demonstrate by simulations that MOMENT shows a lower false positive rate and more robustness than existing methods. MOMENT has been implemented in a versatile software package called OSCA together with a number of other implementations for omic-data-based analyses. Abstract The rapid increase of omic data has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we propose a mixed-linear-model-based method called MOMENT that tests for association between a DNAm probe and trait with all other distal probes fitted in multiple random-effect components to account for unobserved confounders. We demonstrate by simulations that MOMENT shows a lower false positive rate and more robustness than existing methods. MOMENT has been implemented in a versatile software package called OSCA together with a number of other implementations for omic-data-based analyses. |
| ArticleNumber | 107 |
| Author | Deary, Ian J McRae, Allan F Nabais, Marta F Visscher, Peter M Yang, Jian Wray, Naomi R Zhu, Zhihong Qi, Ting Zhang, Qian Zhang, Futao Chen, Wenhan |
| Author_xml | – sequence: 1 givenname: Futao surname: Zhang fullname: Zhang, Futao organization: Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 2 givenname: Wenhan surname: Chen fullname: Chen, Wenhan organization: Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 3 givenname: Zhihong surname: Zhu fullname: Zhu, Zhihong organization: Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 4 givenname: Qian surname: Zhang fullname: Zhang, Qian organization: Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 5 givenname: Marta F surname: Nabais fullname: Nabais, Marta F organization: University of Exeter Medical School, Devon, EX2 5DW, UK – sequence: 6 givenname: Ting surname: Qi fullname: Qi, Ting organization: Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 7 givenname: Ian J surname: Deary fullname: Deary, Ian J organization: Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK – sequence: 8 givenname: Naomi R surname: Wray fullname: Wray, Naomi R organization: Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 9 givenname: Peter M surname: Visscher fullname: Visscher, Peter M organization: Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 10 givenname: Allan F surname: McRae fullname: McRae, Allan F organization: Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia – sequence: 11 givenname: Jian orcidid: 0000-0003-2001-2474 surname: Yang fullname: Yang, Jian email: jian.yang.qt@gmail.com, jian.yang.qt@gmail.com, jian.yang.qt@gmail.com organization: Institute for Advanced Research, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China. jian.yang.qt@gmail.com |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31138268$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Age Aged Computer Simulation Data analysis Deoxyribonucleic acid DNA DNA Methylation DNA probes Gene expression Genetic Techniques Genotype & phenotype Humans Linear Models Metabolomics - methods Method Phenotype Software Studies |
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| Title | OSCA: a tool for omic-data-based complex trait analysis |
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