Fig. 3: CLC as benchmark for cancer driver predictions. | Communications Biology

Fig. 3: CLC as benchmark for cancer driver predictions.

From: Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis

Fig. 3

a CLC benchmarking of ExInAtor driver lncRNA predictions using PCAWG whole genome tumours at q-value (false discovery rate) cutoff of 0.1. Genes sorted increasingly by q-value are ranked on x-axis. Percentage of CLC genes amongst cumulative set of predicted candidates at each step of the ranking (precision), are shown on the y-axis. Black line shows the baseline, being the percentage of CLC genes in the whole list of genes tested. Coloured dots represent the number of candidates predicted under the q-value cutoff of 0.1. “n” in the legend shows the number of CLC and total candidates for each cancer type. b Rate of driver-gene predictions amongst CLC and non-CLC genesets (q-value cutoff of 0.1) by all the individual methods and the combined list of drivers developed in PCAWG. p-value is calculated using Fisher’s exact test for the difference between CLC and non-CLC genesets. c Rate of driver-gene predictions amongst CGC and nonCGC genesets (q-value cutoff of 0.1) by all the individual methods and the combined list of drivers developed in PCAWG. p-value is calculated using Fisher’s exact test for the difference between CGC and nonCGC genesets.

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