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Table 7 Results of the comparison with other clustering methods

From: Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data

Clustering method #clusters #enriched clusters #genes μ SE σ SE CQ Loss information ratio
C01 105 24 344 0.10 0.155 37.82 35.8%
C02 2 2 101 0.069 < 0.001 6.96 88.2%
F A 1 2 2 688 0.065 0.02 44.94 23.8%
F A 2 2 2 380 0.089 0.008 33.66 42.9%
CI 15 2 511 0.089 0.006 46.17 21.6%
PID-NCI graph 1 1 524 0.11 58.93. 0%
  1. The column #clusters stands for the sum of clusters. The column #enriched clusters stands for the sum of clusters which can be associated to enriched GO-terms. The column #genes stands for the number of genes in all the enriched clusters. The columns μSE and σSE stand for the mean and standard deviation for the SE value of the enriched clusters. The Loss information ratio column is computed for each clustering method c as 1−CQc/CQPID. The bold values refer to the results obtained with the component identification algorithm