Fig. 1

Approach to quantify if patterns of de novo within a mutational class are unusual. Our approach involves three steps. First, we identify the genomic target (base pair territory) in which mutations will be characterized, and the total number of mutations found in that territory. We then distribute this total number of mutations over the target territory using a background model of mutation rate. Second, we find the expected number of mutations in different categories (Exon, mutational type like Nonsense or specific Amino Acid) using the previous distribution samples. Third and finally, we compare this to the observed number of mutation to detect statistical enrichment in a category beyond expectation. In this toy example depicted here, we focus on the genomic territory that can generate nonsense mutation (shown in red), and imagine that we have identified 10 de novo mutations that are nonsense. First, we identify eligible base pairs and that can result in a nonsense change. Next, we calculate the probability of mutation at each eligible base pair as the sum of substitution probabilities of that sequence context changing to a stop codon (shown in red). Second, we then distribute the mutations over multiple simulations from a multinomial distribution, and find the distribution of the expected number of mutations at each of these eligible base pairs. We are particularly interested in cases where the observed number of mutations at a subclass (exon or an amino acid) is greater than what we see in simulations, as this is compatible with disease-relevant pathogenicity for this class of mutation, or position where the mutation(s) is located. Third and finally, for a particular subclass we combine the expected mutations at different eligible base pairs and compare the overall expected distribution with observed, and conclude enrichment