GAIN is based on interaction information between three attributes which in this case, between two single nucleotide polymorphisms (SNPs) and a class or phenotype attribute. Interaction information is the gain in phenotype information obtained by considering SNP A and SNP B jointly beyond the phenotype information that would be gained by considering SNPs A and B independently.
Thus, each edge in a GAIN represents the increase in information about the phenotype achieved by considering the two SNPs jointly compared to the expected increase in information with the assumption of independence between the SNPs. We emphasize that a connection between SNPs in a GAIN is specific to the given phenotype because it measures the correlation between two SNPs that influences association with the phenotype. The network can be exported to Cytoscape or visualized interactively within the GAIN tool.
GAIN can be combined with SNPrank for a powerful analysis engine. We have a tutorial describing the steps of the analysis as well as the dependencies required.
There are two currently two implementations of GAIN available.
- a command-line tool written in Python, hosted on Github
- an older Java-based GUI version of GAIN, hosted on Google Code