New methods for separating causes from effects in genomics data

BMC Genomics

Table 5 Accuracy of causal orientation

Method	ECOLI	YEAST	NOTCH1	RELA
ANM	0.462	0.383	0.476	0.396
PNL	0.453	0.471	0.521	0.520
IGCI (Uniform/Entropy)	0.647	0.427	0.611	0.692
IGCI (Uniform/Integral)	0.605	0.441	0.561	0.669
IGCI (Gaussian/Entropy)	0.742	0.555	0.848	0.898
IGCI (Gaussian/Integral)	0.645	0.587	0.729	0.835
GPI-MML	0.485	0.390	0.251	0.395
ANM-MML	0.428	0.316	0.183	0.172
GPI	0.526	0.401	0.548	0.506
ANM-GAUSS	0.480	0.483	0.727	0.462
LINGAM	0.469	0.451	0.367	0.387
RANDOM	0.500	0.500	0.500	0.500

For each gold standard (column) dark orange cells correspond to methods that have high values of accuracy, while white cells correspond to methods that have low values of accuracy. Accuracies higher than 0.50 are shown in bold.

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