Using networks to measure similarity between genes: association index selection

This Perspective describes statistical measures commonly used to quantify whether nodes in biological networks have similar interaction profiles and discusses which indices are best suited for specific tasks. Biological networks can be used to functionally annotate genes on the basis of interaction-profile similarities. Metrics known as association indices can be used to quantify interaction-profile similarity. We provide an overview of commonly used association indices, including the Jaccard index and the Pearson correlation coefficient, and compare their performance in different types of analyses of biological networks. We introduce the Guide for Association Index for Networks (GAIN), a web tool for calculating and comparing interaction-profile similarities and defining modules of genes with similar profiles.