GSUA is extremely important in complex systems that are dominated by factor interactions rather than an additive contribution of each single factor.
In Figure 5, the contribution of each single analyte to the separation of disease from control samples (VIP) are plotted for schizophrenia and depression on the y- and x- axis, respectively, to provide a visual representation of the relative specificity of the findings.
The cat score measures the individual contribution of each single feature to separate two groups, after removing the effect of all other genes.
However, when taking into consideration that a mental disorder like schizophrenia is caused by multiple genes and the contribution of each single gene is small, increasing the statistical stringency automatically entails a loss of biological information.
$$\end{documentt} ε = ∑ l = 1 L R l f ij, C L. Condition (a) implies that the feature-pair has a joint effect relative to a class variable that is more significant than the contribution of each single feature, where the contribution is still larger than the correlation between the two features.
In the pan-genome model, parameter b is less than 1 because the contribution of each extra single genome added to the pan-genome analysis tends decrease due to the homologous genes between the each genome.
While some patterns, such as PC1 (defined by near-uniform loadings across most tooth surfaces and therefore representing global extent of decay), and FACs 7, 8 and 10 (each defined by contributions of a single pre-molar), are readily interpretable, other PCs and FACs may be difficult to relate back to the original variables.
Figure 2 shows the contribution (in terms of utility), of each single quality attribute over the entire sample (see Table 3 for the complete list of attributes and acronyms).
