Small Searchable <i>κ</i>-Spectra via Subset Rank Queries on the Spectral Burrows-Wheeler Transform
Jarno Alanko, Simon J. Puglisi, Jaakko Vuohtoniemi
Abstract
The κ-spectrum of a string is the set of all distinct substrings of length κ occurring in the string. This is a lossy but computationally convenient representation of the information in the string, with many applications in high-throughput bioinformatics. In this work, we define the notion of the Spectral Burrows-Wheeler Transform (SBWT), which is a particular sequence of subsets of the alphabet of the string that encodes κ-spectrum of the string. We explore different approaches to index the SBWT for membership queries on the underlying κ-spectrum. We identify subset rank queries as the essential subproblem, and propose three space-efficient index structures to solve it. We show, via experiments on a range of genomic data sets, that the simplicity of our new indexes translates into large performance gains in practice over prior art.