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Table 1 Distribution of TCGA and Ceccarelli study clusters associated with normal-like (NL) and other-type (OT) IDH-WT gliomas (for each category, only samples for which data are available were considered)

From: A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets

  NL OT p value (Fisher’s exact test)
RNASeqCluster (n = 53 with available data) N = 11 N = 42  
 R2 0 (0.0%) 42 (100%) 1.31e−11
 R4 11 (100%) 0 (0.0%)  
MethylationCluster (n = 57 with available data) N = 11 N = 46  
 M1 7 (63.6%) 4 (8.7%) 3.06e−04
 M4 4 (36.4%) 42 (91.3%)  
miRNACluster (n = 58 with available data) N = 11 N = 47  
 mi1 9 (81.8%) 14 (29.8%) 1.95e−02
 mi2 1 (9.1%) 10 (21.3%)  
 mi3 0 (0.0%) 11 (23.4%)  
 mi4 1 (9.1%) 12 (25.5%)  
CNCluster (n = 57 with available data) N = 10 N = 47  
 C1 8 (80.0%) 10 (21.3%) 7.96e−04
 C2 2 (20.0%) 37 (78.7%)  
Pan_Glioma_RNA_Expression_Cluster (n = 237 with available data) N = 14 N = 223  
 LGr1 0 (0.0%) 26 (11.7%) 5.00e−04
 LGr2 12 (85.7%) 4 (1.8%)  
 LGr3 0 (0.0%) 6 (2.7%)  
 LGr4 2 (14.3%) 187 (83.9%)  
Pan_Glioma_DNA_Methylation_Cluster (n = 207 with available data) N = 14 N = 193  
 LGm1 0 (0.0%) 1 (0.5%) 1.50e−03
 LGm4 3 (21.4%) 62 (32.1%)  
 LGm5 2 (14.3%) 100 (51.8%)  
 LGm6 9 (64.3%) 30 (15.5%)