Correlating ASE motif number and expression in ASE. The power of a gene's upstream ASE motifs to predict ASE expression depends on the number and score of each ASE motif. We define a gene's top-N motif score (which estimates the probability that all N motifs are functional; see materials and methods) as the product of the top-N upstream ASE motif scores for a given gene. Meanwhile we split the genes into a positive set, consisting of the 52 ASE-expressed genes [as confirmed by reporter–GFP construct experiments (Etchberger et al. 2007)] and a negative set the remainder of the genome. Then we sort the entire list of genes according to each top-N motif score, for N = 1, 2, 4, and 8 and measure how well the score criterion places the ASE-expressed genes near the top. To visualize this sorting, we generated “receiver operator characteristic” (ROC) curves. Intuitively, a ROC curve can be understood as follows: Starting at point (0, 0) at the top of the list (gene with best score), the graph moves up (y-axis) one gene if the next gene on the list is a positive and to the right (x-axis) if the gene is a negative, and so on until the last (20,183rd) gene is encountered [point (20131, 52)] at top right corner of graph. For example, point (2000, 25) on the red curve denotes that 25 ASE-expressed genes are found in the top 2025 genes (10% of the genome) in the list sorted using the top-4 motif score. Point (2000, 14) on the green curve, by contrast, shows that only 14 of the 52 ASE-expressed genes (27%) are recovered in the same-size list when sorted by the top-1 motif score (inset). Therefore, the top-4 motif score, which assumes four functional motifs and scores accordingly, is about twice as effective at identifying ASE-expressed genes than the top-1 motif score. This is statistical evidence that, on average, multiple ASE motifs are functional in ASE expression. Additionally, the underlying data from which these graphs are derived (supplemental Methods) may be interpreted as a probability estimate for ASE expression of all C. elegans genes and used to choose candidate ASE-expressed genes for further testing.