Spectral Jaccard Similarity: A New Approach to Estimating Pairwise Sequence Alignments

-mer distributions. The Spectral Jaccard Similarity is computed by performing a singular value decomposition on a min-hash collision matrix. We empirically show that this new metric provides significantly better estimates for alignment sizes, and we provide a computationally efficient estimator for these spectral similarity scores.