Research Paper Volume 13, Issue 1 pp 555—577

Figure 2. Autophagy genes can distinguish healthy and periodontitis samples. (A) Univariate logistic regression investigated the relationship between dysregulated autophagy genes and periodontitis. (B) Least absolute shrinkage and selection operator (LASSO) coefficient profiles of 16 periodontitis-related autophagy genes. (C) Ten-fold cross-validation for tuning parameter selection in the LASSO regression. The partial likelihood deviance is plotted against log (λ), where λ is the tuning parameter. Partial likelihood deviance values are shown, with error bars representing SE. The dotted vertical lines are drawn at the optimal values by minimum criteria and 1-SE criteria. (D) Distinguishing signature with 10 autophagy genes was developed by multivariate logistic regression and the risk scores for periodontitis were calculated. (E) The risk distribution between healthy and periodontitis, where periodontitis has a much higher risk score than healthy samples. (F) Principal component analysis (PCA) of 10 periodontitis-related autophagy genes between healthy and periodontitis. The two first principal components (PC1, PC2) which could explain most of the variables are plotted. (G) The discrimination ability for healthy and periodontitis samples by autophagy genes was analyzed by the ROC curve and evaluated by AUC value.