Bioinformatics for the Interpretation of Genetic Association Study Results
Genetic association studies can provide statistically significant results but further studies are required to establish biological significance. Functional replication studies on genetically replicated results aim to confirm or refute whether the statistical correlation between the variant and disease risk points toward a potentially causal relationship. Recent advances in computational bioinformatics, as well as the availability of massive amounts of genomics and proteomics data, enable researchers to carry out computational analyses in a dry laboratory to pinpoint the functional variants. The ultimate aim is to treat the statistical result as an association signal to find out the actual causal variant. This chapter will present the bioinformatics tools and approaches available to take association studies a step further. Bioinformatics is a very broad and ever-expanding discipline. Here, only what is emerging as translational bioinformatics is covered, with a focus on the functional assessment of genetic variants.