Meta-analysis of genetic association studies under different inheritance models using data reported as merged genotypes
| dc.contributor.author | Salanti, G. | en |
| dc.contributor.author | Higgins, J. P. | en |
| dc.date.accessioned | 2015-11-24T19:04:44Z | |
| dc.date.available | 2015-11-24T19:04:44Z | |
| dc.identifier.issn | 0277-6715 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/20094 | |
| dc.rights | Default Licence | - |
| dc.subject | Genetic Predisposition to Disease | en |
| dc.subject | *Genetic Research | en |
| dc.subject | *Genotype | en |
| dc.subject | Humans | en |
| dc.subject | *Meta-Analysis as Topic | en |
| dc.subject | *Models, Statistical | en |
| dc.title | Meta-analysis of genetic association studies under different inheritance models using data reported as merged genotypes | en |
| heal.abstract | Meta-analysis of population-based genetic association studies is often challenged by obstacles associated with the underlying inheritance model. For a simple genetic variant with two alleles, a recessive, dominant or co-dominant model is typically assumed. In the absence of a strong biological rationale for a particular inheritance model, a recently suggested inheritance-model-free approach can be implemented. To enable a flexible choice among these models, summary results from each of the three genotypes are required. Incompatibility of the data across studies because of different inheritance models is a common problem. For instance, if the underlying model is dominant, studies that have assumed the recessive model and presented the results accordingly, have so far been excluded from the meta-analysis. We show how to combine data and make inferences under any inheritance model, irrespective of the models assumed within each study and the way that data are presented. Within a Bayesian framework we describe prospective models for binary and continuous outcomes, and retrospective models for binary outcomes. The methods exploit an assumption of Hardy-Weinberg equilibrium, prior information about genotype prevalence or assumption of a specific inheritance model. On application to meta-analyses of the associations between a polymorphism in the lipoprotein lipase gene and coronary heart disease or high-density lipoprotein cholesterol, we observe substantial gains in precision when there is a large proportion of studies in which different inheritance models have been assumed. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | 10.1002/sim.2919 | - |
| heal.identifier.secondary | http://www.ncbi.nlm.nih.gov/pubmed/17576642 | - |
| heal.identifier.secondary | http://onlinelibrary.wiley.com/store/10.1002/sim.2919/asset/2919_ftp.pdf?v=1&t=h0dojecl&s=3dfbab719160bec5e01b860a38d8becb9c245702 | - |
| heal.journalName | Stat Med | en |
| heal.journalType | peer-reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2008 | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικής | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
Files
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 1.74 KB
- Format:
- Item-specific license agreed upon to submission
- Description: