<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>SPUMONI 2: improved classification using a pangenome index of minimizer digests</dc:title><dc:creator>Ahmed, Omar Y.; Rossi, Massimiliano; Gagie, Travis; Boucher, Christina; Langmead, Ben</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Abstract            Genomics analyses use large reference sequence collections, like pangenomes or taxonomic databases. SPUMONI 2 is an efficient tool for sequence classification of both short and long reads. It performs multi-class classification using a novel sampled document array. By incorporating minimizers, SPUMONI 2’s index is 65 times smaller than minimap2’s for a mock community pangenome. SPUMONI 2 achieves a speed improvement of 3-fold compared to SPUMONI and 15-fold compared to minimap2. We show SPUMONI 2 achieves an advantageous mix of accuracy and efficiency in practical scenarios such as adaptive sampling, contamination detection and multi-class metagenomics classification.</dc:description><dc:publisher/><dc:date>2023-12-01</dc:date><dc:nsf_par_id>10451197</dc:nsf_par_id><dc:journal_name>Genome Biology</dc:journal_name><dc:journal_volume>24</dc:journal_volume><dc:journal_issue>1</dc:journal_issue><dc:page_range_or_elocation/><dc:issn>1474-760X</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1186/s13059-023-02958-1</dc:doi><dcq:identifierAwardId>2029552; 2013998</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>