Supplementary Figure 8: Lack of genuine non-linear relationships in ProteomeHD.
From: Co-regulation map of the human proteome enables identification of protein functions
(a) Exponential and logistic (sigmoid) models were fitted to all protein pairs that scored high with treeClust or the three correlation metrics. Model fit was compared through their residual sum of squares (RSS). Exponential models only fitted better than linear ones in rare cases, but logistic models often did. Around half of the protein pairs detected specifically by PCC are better explained by a logistic than a linear model. However, this is mainly driven by Mahalanobis-type outliers. Removing those strongly reduces the number of logistic models outfitting the linear ones. (b) Two example regressions where an exponential (left) or logistic (right) model fits better than a linear one. Note that this clearly reflects overfitting due to outliers rather than genuine non-linear relationships.
