Meta-analysis has become a common approach to summarize genetic association with the tremendous amount of published epidemiological evidence. Assessing the credibility of meta-analysis evidence on genetic association is a rapidly growing challenge. This paper illuminates how to assess the credibility of meta-analysis evidence by using Venice criteria. A semi-quantitative index assigns three levels for the amount of evidence, replication and protection from bias. At the end, three considerations are merged into a grading scheme, which generates three composite assessments: weak, moderate or strong. Credibility assessment is necessary to estimate whether a true genetic association exists. Such method provides indication for further study and is of clinical importance.
The association between single nucleotide polymorphism and disease is a typical representation of genetic association studies. Compared with the traditional dichotomous data, single nucleotide polymorphism data has its own characteristics, and 5 genetic models are commonly performed in meta-analysis. In this paper, we show how to use the " meta” package in R software to conduct meta-analysis of single nucleotide polymorphism research through examples.