Skip to main content

Table 6 Results of our clustering-based approach when applied on clusters with more than one TP.

From: Filtering of false positive microRNA candidates by a clustering-based approach

  Human Mouse (All) Mouse (Distinct) Rat
Before/After filtering before after before after before after before after
# of predictions 620 335 632 363 616 350 525 224
# of TPs 206 189 195 168 179 155 121 99
# of real miRNAs 220 220 234 234 202 202 132 132
SE 93.64% 85.91% 83.33% 71.79% 88.61% 76.73% 91.67% 75.00%
Change in SE - -7.73% - -11.54% - -11.88% - -16.67%
PPV 33.23% 56.42% 30.85% 46.28% 29.06% 44.29% 23.05% 44.20%
Change in PPV - +23.19% - +15.43% - +15.23% - +21.15%
  1. If we exclude the clusters which bear no TPs or just one TP among the candidates predicted by ProMirII-g, we can see a great improvement in PPV without a significant effect on SE after our filtering approach is applied. The results agree with the principle of our approach, which is developed based on the phenomenon of miRNA clustering. In other words, if there are no clustered miRNAs in a sequence, our approach is not going to work properly. This table presents the results of a fairer comparison, suggesting that our approach is effective in filtering FPs.