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We present an algorithm for building the extended BWT (eBWT) of a stringcollection from its grammar-compressed representation. Our technique exploitsthe string repetitions captured by the grammar to boost the computation of theeBWT. Thus, the more repetitive the collection is, the lower are the resourceswe use per input symbol. We rely on a new grammar recently proposed at DCC'21whose nonterminals serve as building blocks for inducing the eBWT. A relevantapplication for this idea is the construction of self-indexes for analyzingsequencing reads -- massive and repetitive string collections of raw genomicdata. Self-indexes have become increasingly popular in Bioinformatics as theycan encode more information in less space. Our efficient eBWT constructionopens the door to perform accurate bioinformatic analyses on more massivesequence datasets, which are not tractable with current eBWT constructiontechniques.

Efficient construction of the extended BWT from grammar-compressed DNA sequencing reads