Figure 1.

IDBOS scoring schemes. The method presented is an extension to the interaction detection based on shuffling (IDBOS) method used for mass spectrometry co-purification data [22]. We compared the set of known protein-protein interactions (PPIs) with randomized versions, which preserve the number of interactions per protein, to obtain a Z-score and a p-value for each interaction. These quantities are schematically outlined at the top, where a randomized probability density distribution function (PDF) is used to illustrate the p-value and Z-score calculations for a particular interaction between proteins i and j. To evaluate these scoring schemes, we analyzed interactions derived from crystallographic complexes in the PDB. Each human PPI was compared to a PPI derived from protein structure data in the PDB and assigned to one of two subsets: interactions or non-interactions. If the PPI was present in the PDB interaction data set, the pair was assigned to the interactions set, otherwise the pair was assigned to the non-interactions set. It is reasonable to assume that the first subset should be enriched with actual PPIs. (A) Distribution of Z-scores corresponding to “interactions” and “non-interactions” assigned to PDB-derived PPIs, and (B) the corresponding p-value distributions. We found that both p-values and Z-scores could distinguish these subsets, suggesting that they are useful metrics.

Yu et al. BMC Bioinformatics 2012 13:79   doi:10.1186/1471-2105-13-79
Download authors' original image