(SNP's) are compared with single binary exposure factors to determine any effects. Candidate studies such as these require strong biological hypotheses which are currently difficult to select given the little understanding of biological mechanisms that lead to higher risk. These studies are also often difficult to replicate commonly due to small sample sizes which typically results in disputed results. The polygenic nature of complex phenotypes suggests single candidate studies could be ineffective in determining the various smaller scale effects from the large number of influencing gene variants. Interaction with multiple genes Since the same environmental factor could interact with multiple genes, a polygenic approach can be taken to analyze GxE interactions. A polygenic score is generated using the alleles associated with a trait and their respective weights based on effect and examined in combination with environmental exposure. Though this method of research is still early, it is consistent with psychiatric disorders. As a result of the overlap of endophenotypes amongst disorders this suggests that the outcomes of gene–environment interactions are applicable across various diagnoses. Genome-wide association studies and genome wide interaction studies A genome wide interaction scan (GEWIS) approach examines the interaction between the environment and a large number of independent SNP's. An effective approach to this all-encompassing study occurs in two-steps where the genome is first filtered using gene-level tests and pathway based gene set analyses. The second step uses the SNP's with G–E association and tests for interaction. The differential susceptibility hypothesis has been reaffirmed through genome wide approaches. Controversies Lack of replication A particular concern with gene–environment interaction studies is the lack of reproducibility. Specifically complex traits studies have come under scrutiny for producing results that cannot be replicated. For example, studies of the 5-HTTLPR gene and stress resulting in modified risk of depression have had conflicting results. A possible explanation behind the inconsistent results is the heavy use of multiple testing. Studies are suggested to produce inaccurate results due to the investigation of multiple phenotypes and environmental factors in individual experiments. Additive vs multiplicative model There are two different models for the scale of measurement that helps determine if gene–environment interaction exists in a statistical context. There is disagreement on which scale should be used. Under these analyses, if the combined variables fit either model then there is no interaction. The combined effects must either be greater for synergistic or less than for an antagonistic outcome.