The trend in the main effect of components in any mixture was affected by the trends in the physico-chemical properties of the components, i.e., partition coefficient, molecular size and polarity.
A two-way ANOVA for repeated measures with Task (time-based vs. event-based vs. activity-based) and Component PMM component vs. RM component) performed on the z-scores of the aMCI participants revealed a significant main effect of Component [F 1, 18) = 6.01, p < .05, η = 0.25], suggesting that the PM component was more impaired than the RM component with aMCI individuals.
The model allows decomposing marker effects and genomic variance into components that are stable across environments (main effects) and components that are environment-specific (interaction terms).
The first 'main effect' component arose as score test from a standard logistic regression of case (1) versus control (0) status on number of minor SNP alleles and potential confounding factors.
Counter to expectations, recent work shows that fitting full models, instead of testing marker main effect and interaction components separately, in exhaustive multi-locus genome scans can have higher power to detect loci when epistasis is present than single-locus scans, and improvement that comes despite a much larger multiple testing alpha-adjustment in such searches.
Global main effects principal component analysis was performed as previously described (Box et al., 2005).
Figure 1 figure supplement 1 provides a global main effects principal component analysis for all GF and SM used in this second screen.
Consistent with this observation, a global main effects principal component analysis of all GF and SM revealed that CHR, WNT, Rspondin and FGF exerted the most potent effects on GFP expression.
DOI: http://dx.doi.org/10.7554/eLife.08413.003 10.7554/eLiFigure1 figureigure 1—figure supplement 1. Global main effects principal component analysis of GF and SM ACME screen demonstrates that WNT and FGF agonists exert positive effects on T-GFP expression.
