Autosomal genes contributing to variation in many complex traits are influenced by male or female physiological "environments." Accounting for such genotype-by-sex (G x S) interactions has been shown to be important in quantitative genetic, segregation, and linkage analyses of a number of sexually dimorphic traits. In analyses of data simulated for GAW10, we showed that incorporating sex-specific variance components into a variance components-based linkage method increased the power to detect linkage in a trait that exhibited G x S interaction. The goals of this study of data from the Collaborative Study on the Genetics of Alcoholism (COGA) were to screen the event-related brain potential (ERP) data from COGA participants for G x S interaction, and then to conduct variance components linkage analysis of ERP phenotypes showing evidence of G x S interaction using models incorporating sex-specific variance components. Significant G x S interaction was found in four ERP phenotypes: N100 measured at occipital leads 1 and 2, and P300 measured at occipital leads 1 and 2. In linkage analyses of these traits, the most significant lod score found was that between N100 occipital lead 1 amplitude and marker D7S490. The peak lod score at the D7S490 locus was 2.45 without sex-specific variance components, and 3.25 with sex-specific marker and residual polygenic components.