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. 2010 Mar 22;5(3):e9803. doi: 10.1371/journal.pone.0009803

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Madar et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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We present the relative merit of five methods, with and without knock-out filtration, to resolve causation (i.e. directionality of regulatory interactions). For each method we computed the fraction of correctly resolved true regulatory interactions (true positives, TPs) out of the total number of TPs the method had identified. We define a TP interaction, , as correctly resolved, if its score, (according to each method or method combination), was bigger than the confidence score of the reverse (false) regulatory interaction, . The original CLR method without filtration results in symmetric confidence scores, , and thus cannot resolve causation (fraction correct = ). In each bar plot we report the absolute number of correctly (incorrectly) resolved interactions. We show that, without filtration, Inferelator 1.0 has the most power at resolving causation ( correct), and that for all methods knock-out filtration helps resolve causation. For Inferelator 1.0 filtration helps recover more TPs. Error bars for methods involving Inferelator 1.0 are less than and are not shown.

Inline graphic — We present the relative merit of five methods, with and without knock-out filtration, to resolve causation (i.e. directionality of regulatory interactions). For each method we computed the fraction of correctly resolved true regulatory interactions (true positives, TPs) out of the total number of TPs the method had identified. We define a TP interaction, , as correctly resolved, if its score, (according to each method or method combination), was bigger than the confidence score of the reverse (false) regulatory interaction, . The original CLR method without filtration results in symmetric confidence scores, , and thus cannot resolve causation (fraction correct = ). In each bar plot we report the absolute number of correctly (incorrectly) resolved interactions. We show that, without filtration, Inferelator 1.0 has the most power at resolving causation ( correct), and that for all methods knock-out filtration helps resolve causation. For Inferelator 1.0 filtration helps recover more TPs. Error bars for methods involving Inferelator 1.0 are less than and are not shown.