Skip to main content
. 2020 Jun 14;21(12):4236. doi: 10.3390/ijms21124236

Figure 7.

Figure 7

External validation of RF and SVM clinical models in public four GEO datasets (GSE99339, GSE47185, GSE30122 and GSE96804). (A) In the GSE99339 dataset, boxplot of the prognostic probabilities of the two classifiers in 11 disease groups including DN (N = 14), RPGN (N = 23), TN (N = 14), HT (N = 15), IgA nephropathy (N = 26), MGN (N = 21), SLE (N = 30), TMD (N = 3), FSGS (N = 22), FSGS&MCD (N = 6), and MCD (N = 13). (B) In the GSE30122 data set, the prognostic indexes of the two classifiers in the eight disease groups in the renal glomeruli with DN (N = 14), RPGN, (N = 23), TN (N = 17), MGN (N = 21), TMD (N = 3), FSGS (N = 23), FSGS&MCD (N = 6), and MCD (N = 15) and in the renal tubulointerstitia with DN (N = 18), RPGN (N = 21), TN (N = 6), MGN (N = 18), TMD (N = 6), FSGS (N = 13), FSGS&MCD (N = 4), and MCD (N = 15). (C) In the GSE30122 data set, the prediction values of the two classifiers in the control and disease groups in renal glomerulus (N = 26; control and N = 9; disease) and in renal tubulus (N = 24; control and N = 10; disease). (D) In the GSE30122 data set, the prediction probabilities of the two classifiers in the control (N = 20) and disease (N = 41) groups in renal glomeruli.