IRF9 and XAF1 as Diagnostic Markers of Primary Sjogren Syndrome

Figure 4

Screening and verification of diagnostic markers. (a) Least absolute shrinkage and selection operator (LASSO) logistic regression algorithm to screen diagnostic markers. Different colors represent different genes. Each curve corresponds to an independent variable in the full model prior to optimization. Curves indicate the path of each variable coefficient as varies. Lambda.min corresponds to which minimizes mean squared error in the model and was used for the selection of the seven predictor variables. (b) LASSO coefficient profiles of the 19 candidates in GSE66795. Plot of nonzero variable fit after cross-validation. Representation of the 10-fold cross-validation performed in LASSO that chooses the optimal . Lambda.min corresponds to which minimizes mean squared error and was used for variable selection. Lambda.1se corresponds to that is one standard error from Lambda.min. (c) Venn diagram shows the intersection of diagnostic markers obtained by LASSO and hub genes. (d) The ROC curve of the diagnostic efficacy tested by GSE51092. (e) The expression level of IRF9 between patients with pSS and HCs in GSE51092. (f) The expression level of XAF1 between patients with pSS and HCs in GSE51092. .

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