2021/02/08 by Diego Diaz-Dominguez annd Gonzalo Navarro, Navarro, Diego Diaz-Dominguez annd Gonzalo
Biochemistry, Genetics and Molecular Biology · Computer Science · #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Genomics and Phylogenetic Studies #Natural Language Processing Techniques
paper · pdf · doi:10.48550/arxiv.2102.03961
openalex publication_date 2021/02/08 · openalex created_date 2024/04/11 · openalex updated_date 2026/07/28
We present an algorithm for building the extended BWT (eBWT) of a string collection from its grammar-compressed representation. Our technique exploits the string repetitions captured by the grammar to boost the computation of the eBWT. Thus, the more repetitive the collection is, the lower are the resources we use per input symbol. We rely on a new grammar recently proposed at DCC'21 whose nonterminals serve as building blocks for inducing the eBWT. A relevant application for this idea is the construction of self-indexes for analyzing sequencing reads -- massive and repetitive string collections of raw genomic data. Self-indexes have become increasingly popular in Bioinformatics as they can encode more information in less space. Our efficient eBWT construction opens the door to perform accurate bioinformatic analyses on more massive sequence datasets, which are not tractable with current eBWT construction techniques.