CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis
Figure 2
Overview of R/cape workflow and visualization tools using example data [1].
(A) Phenotypes are first decomposed into orthogonal eigentraits (ETs). Phenotype composition and global variance fraction are displayed for each ET, facilitating the selection of ETs for interaction analysis. In this study, the first two ETs were selected, which contained the correlated signal between all phenotypes and a divergence between phenotypes, respectively. (B) Pair-wise linear regression is next performed on each ET. Symmetric matrices of all marker pair interaction terms are displayed in matrix form, with gray and white bars along the axes to mark chromosome boundaries. The first two ETs for this study are shown. (C) Regression parameters are next reparametrized (Figure 1) to derive models of directed interactions between markers and from markers to phenotypes. In the adjacency matrix view (left), markers are designated as sources or targets of directed interactions, and marker-to-phenotype influences are in the rightmost columns. Only variants with significant main effect or interaction are shown, and gray dots mark pairs that were not included in the model due to linkage disequilibrium. In the network view (right), arrows are directed from source to target marker positions across all chromosomes. Red arrows indicate suppressive (negative) interactions. Main effects are represented below the variants with green indicating an effect that increases phenotype and gray indicating no significant main effect on phenotype.