Quantifying Pathogen Surveillance Using Temporal Genomic Data

Chan, Joseph M.; Rabadan, Raul

Comparison to clustering methods. Another possible surveillance measurement characterizes the cluster structure of isolates. In an ideal situation, a well-sampled population of sequences separated by genetic distance would be represented by points densely and homogeneously spread across a continuum. Therefore, clustering techniques such as hierarchical, k-means, or expectationmaximization clustering can be used to ascertain how poorly sampled a pathogen is on the basis of the number of clusters in a data set. Bar coding is an alternative strategy based on the field of per-sistent homology that identifies topologically invariant clusters in cloud data; in particular, it calculates the b 0 Betti number, the number of connected components in a set of simplicial complexes constructed from sequences at different filtration Hamming distances (see Materials and Methods) (40) . A lower b 0 would indicate better sampling.