The SAP for DNA signature analyses operates as follows. First, all available complete genomes of target were gathered into a pool with the total genome count called T. A second pool was created of all available NN complete genomes, with the total count of sequences called N. Next, we selected 10 random samples of size t targets and n NNs, for all t ranging from 1 to T and all n ranging between 1 and minimum(10,N). We ran the DNA Signature Prediction Pipeline for each sample, with signature prediction based on conservation among the t target strains and uniqueness relative to a >1 Gb database minus those NNs in the NN pool that were not chosen in that sample. Thus, for each sample, signature candidates were predicted as though we had only t target and n NN sequences, as well as the rest of the less-closely related organisms in our database that are not considered NNs. In addition to the number of TaqMan signature candidates, the fraction of the genome that is conserved among the t target sequences was also calculated. Based on the combined results of the many signature pipeline runs using random target samples of size t and n, we assessed how much sequence data, that is, the values of t and n, was required to approximate the number of signature candidates c that were predicted when the full data set (all target and NN sequences, t ¼ T and n ¼ N) was analyzed with the signature pipeline. Using the full data set will yield the fewest signatures, because lack of conservation or uniqueness will winnow away all unsuitable candidates.