I am looking at identified candidate genes for isolated orofacial clefts identified in various populations to see if the associations are replicated in a UK population. (Along with environmental exposures).
I will be using a secondary data source only, and I am aware of papers that explain what analysis is needed for primary data but I haven't seen if this differs for the use of secondary data?
Georgia Awcock Case-control Secondary data genetic association studies often employ a variety of statistical approaches to examine the data and assess the strength of the relationship between genetic variations and the illness of interest. Among the most frequent approaches are:
1. Logistic regression: This approach is used to calculate the odds ratio (OR) and 95% confidence interval (CI) for a genetic variant's connection with illness. This may be used to analyze both the main impact of the genetic variation and the interactions between the genetic variant and environmental exposures.
2. The Cochran-Mantel-Haenszel (CMH) test is a statistical test used to examine the relationship between a genetic variation and illness while controlling for other factors such as population stratification.
3. Haplotype analysis: This approach is used to examine the inheritance patterns of numerous genetic variations in linkage disequilibrium. It can be used to identify particular haplotypes linked to the condition.
4. Multivariate analysis can be used to investigate the combined influence of several genetic variations and environmental exposures on the illness of interest.
It should be noted that when utilizing secondary data, it is critical to ensure that the data is of high quality and that the genetic variations and environmental exposures were quantified in the same way as in the main study. Furthermore, before beginning the study, it is critical to have a well-defined research topic, a sample size calculation, and a pre-specified plan of analysis.
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