TL;DR
This paper refines a recent constant-time backward-stepping method for run-length compressed BWT, demonstrating practical improvements and tradeoffs through experiments on genomic data.
Contribution
It introduces a refined approach with a time-space tradeoff, a permutation decomposition scheme for better compression, and experimental validation on real datasets.
Findings
Backward-stepping is faster without compression but uses more space.
Compressed data structures achieve a good balance of time and space.
Practical implementation shows near-constant query times with compression.
Abstract
Until recently, most experts would probably have agreed we cannot backwards-step in constant time with a run-length compressed Burrows-Wheeler Transform (RLBWT), since doing so relies on rank queries on sparse bitvectors and those inherit lower bounds from predecessor queries. At ICALP '21, however, Nishimoto and Tabei described a new, simple and constant-time implementation. For a permutation , it stores an -space table -- where is the number of positions where either or -- that enables the computation of successive values of by table look-ups and linear scans. Nishimoto and Tabei showed how to increase the number of rows in the table to bound the length of the linear scans such that the query time for computing is constant while maintaining -space. In this paper we refine Nishimoto and Tabei's…
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