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Table 8 The performance of Spectral versus Spectral plus DSD at different edge removal thresholds when the input parameter K in all cases is set to 300, but then we discard clusters of size < 3 and split clusters of size > 100

From: RETRACTED ARTICLE: Detangling PPI networks to uncover functionally meaningful clusters

Method Enriched Clusters # NEC % NEC # NEC S % NEC S
PPI 234/324 (72.22%) 3082.0 50.54% 2158.0 35.39%
4.5 194/266 (72.93%) 1647.0 27.02% 1330.0 21.82%
5.0 199/309 (64.40%) 3589.0 58.87% 2203.0 36.14%
5.5 189/291 (64.95%) 3765.0 61.76% 2228.0 36.55%
6.0 177/249 (71.08%) 4670.0 76.61% 2490.0 40.85%
  1. NEC= “Nodes in Enriched Clusters”. We calculate %NEC in two settings: %NEC is enrichment in the GO hierarchy with terms above the fifth level filtered out, and %NEC S uses the same filtered GO hierarchy, but then only gives a node credit if there is a match between one of the node’s labels and one of the terms for which there is GO enrichment for the cluster. For every threshold we tested ≥ 5, the percentage of nodes in enriched clusters is better than Spectral run alone for both measures
  2. Bolded values represent the best values achieved for the %NEC and %NEC S statistics comparing the PPI network and different DSD detangling thresholds
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BMC Systems Biology

ISSN: 1752-0509

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