Estimating false-positive rates of large-scale assays. (a) As described by D'haeseleer and Church , the number of true positives in an interaction dataset can be estimated by examining the ratio of intersections of two similar datasets (A and B) and a reference dataset. If intersections contain all true positives, then the ratio of areas I and II is equal to the ratio of areas III and IV, where IV contains true positives (and V false positives, not shown to scale). The number of false positives can then be determined by simple subtraction, repeating the calculation for the other dataset. (b) Calculation of false-positive rates for the most recent yeast mass spectrometry assays of Gavin et al.  and Krogan et al.  within the interactome subspace sampled by both experiments (1,243 baits) and using MIPS as the reference sample . Intersections (regions I, II, II) were determined by examining the data, and true- and false-positive populations (regions IV and V) were calculated as described in (a).