Fig. 3
Example Scn9aR185H Gdaphen analysis. A Variance explained by top the ten PCA components and cumulative variance using the full model containing the 14 variables. B Variance explained by top the ten PCA components and cumulative variance using the sel30% model containing 9 variables. C 3D-PCA plots showing the individuals clustering on the first 3 dimensions and colored based on each genotype and sex combination. Left panel shows all the genotypes and sexes, the middle plot shows only wild-type and heterozygous data, and the right plot shows only wild-type and homozygous data. D Classifiers results for the 6 variables included in the Sel30% model showing the most important variables to genotype discrimination after scaling to the top discriminative one. E Classifiers results for all the 18 variables included in the full model showing the most important variables to genotype discrimination after scaling to the top discriminative one. F 2D-PCA plots showing the individuals clustering on the first 3 dimensions. On the upper panel coloring is based on genotype and sex combinations. On the lower panel coloring is just by genotype. G Categorical variables discrimination component map. The panels show the distribution in 2 dimensions of the categorical variables PCA coordinates calculated in the MFA analysis using the MFAmix function from PCAmixdata R package [21]. H Square loadings plot with coordinates calculated in the MFA analysis using the MFAmix function from PCAmixdata R package [21]. I Parallel plot showing the non-scaled results of the most influencing variables to the discrimination colored by genotype and sex showing the mean of the variable per group of genotype and sex. In the left parallel, the plot using all the genotypes and sex data. The middle panel shows only heterozygous and wild-types and the right panel only homozygous and wild-types