The term "meta-analysis" was coined in 1976 by the statistician Gene V. Glass. Meta-analysis is a set of techniques used “to combine the results of a number of different reports into one report to create a single, more precise estimate of an effect” (Ferrer, 1998). Simply, a meta-analysis is a statistical analysis that combines the results of multiple scientific studies. The aims of meta-analysis are “to increase statistical power; to deal with controversy when individual studies disagree; to improve estimates of size of effect, and to answer new questions not previously posed in component studies” (Hunter and Schmidt, 1990). There are several advantages to meta-analysis. It allows investigators to pool data from many trials that are too small by themselves to allow for secure conclusions. For example, in medical sciences, the strength of meta-analysis lies in the ability to summarize a large volume of literature in a single publication and to produce clinically relevant conclusions. Meta-analysis can generate sufficient power from a series of smaller trials to answer important clinical questions. In the absence of meta-analysis, the combination of a series of small trials with low individual power can lead to confusion about appropriate therapeutic decisions (Bennett et al, 2008). This presentation was about potential and limitations of meta-analysis of (animal) genetic data based on several research articles/projects.
