We compared NetPTP to the drug rankings produced by the method used in Dudley et al [6], as our work uses similar data sources and is also applied to the same disease, IBD. In their method, a drug-disease score (DDS) is derived for each drug based on how anti-correlated the drug signature is as compared to the disease signature. We calculated the DDS as described in Sirota and Dudley et al [23] for all drugs and CD, and all drugs and UC using the samples in GEO9686, GEO36807, and GEO10616. GEO16879 was not included as these patients were refractory to the mainstay treatments for IBD. Following their method, we first used significance analysis of microarrays (SAM) [24] to derive lists of up-regulated and down-regulated genes, comparing diseased samples to the healthy samples in each study. We then calculated the up-regulated and down-regulated enrichment score, and subsequently the drug-disease score (DDS) for each drug-CD and drug-UC pair in each of the three studies.

We then ranked all drugs by their DDS, from most anti-correlated to least anti-correlated. The original method calls for DDS to be set to 0 if the up-regulated enrichment score and down-regulated enrichment score are the same direction, otherwise DDS is set to the difference between the two. This results in a large number of drugs all having a score of 0, and we differentiated drugs with a score of 0 by ranking them by the difference between the up-regulated and down-regulated enrichment scores.

In order to compare the rankings from the two methods, we curated the FDA approved treatments for IBD that are in CMap. These were budesonide, prednisone, prednisolone, methylprednisolone, azathioprine, mercaptopurine, sulfasalazine, mesalazine, and methotrexate. We then compared the rankings of these nine known treatments based on the DDS to our NetPTP rankings across all studies.

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