A multiple analytic approach may be useful for analyzing complex traits since different methods extract both similar and distinct, but complementary pieces of information from genome screen data on extended pedigrees. We examined the usefulness of combining p-values both across methods and across adjacent markers, taking into account the observed correlation structure among these p-values. To this end, we employed the recently proposed truncated product method [Zaykin et al., Genet Epidemiol, in press]. It appears that this approach is helpful for visualizing priority regions for follow-up analysis and reducing the number of false-positive linkage signals.