Meta-analysis is the quantitative synthesis of information from several studies. It is applicable to a variety of study designs in genetics, from family-based linkage studies and population-based association studies to genome-wide scans and genome-wide association studies. By combining relevant evidence from many studies, statistical power is increased and more precise estimates may be obtained. Most importantly, meta-analysis provides a framework for the appreciation and assessment of between-study heterogeneity, that is, the methodological, epidemiological, clinical, and biological dissimilarity across the various studies. Being a retrospective research design in most cases, meta-analysis is subject to a variety of selection biases that may undermine its validity. A major challenge is to differentiate genuine between-study heterogeneity from systematic errors and biases.