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        <identifier>oai:drops-oai.dagstuhl.de:18644</identifier>
        <datestamp>2024-03-06T11:02:20Z</datestamp>
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          <dc:title>Fulgor: A Fast and Compact {k-mer} Index for Large-Scale Matching and Color Queries</dc:title>
          <dc:creator>Fan, Jason</dc:creator>
          <dc:creator>Singh, Noor Pratap</dc:creator>
          <dc:creator>Khan, Jamshed</dc:creator>
          <dc:creator>Pibiri, Giulio Ermanno</dc:creator>
          <dc:creator>Patro, Rob</dc:creator>
          <dc:subject>k-mers</dc:subject>
          <dc:subject>Colored de Bruijn Graph</dc:subject>
          <dc:subject>Compression</dc:subject>
          <dc:subject>Read-mapping</dc:subject>
          <dc:description>The problem of sequence identification or matching - determining the subset of reference sequences from a given collection that are likely to contain a short, queried nucleotide sequence - is relevant for many important tasks in Computational Biology, such as metagenomics and pan-genome analysis. Due to the complex nature of such analyses and the large scale of the reference collections a resource-efficient solution to this problem is of utmost importance. This poses the threefold challenge of representing the reference collection with a data structure that is efficient to query, has light memory usage, and scales well to large collections.&#13;
To solve this problem, we describe how recent advancements in associative, order-preserving, k-mer dictionaries can be combined with a compressed inverted index to implement a fast and compact colored de Bruijn graph data structure. This index takes full advantage of the fact that unitigs in the colored de Bruijn graph are monochromatic (all k-mers in a unitig have the same set of references of origin, or "color"), leveraging the order-preserving property of its dictionary. In fact, k-mers are kept in unitig order by the dictionary, thereby allowing for the encoding of the map from k-mers to their inverted lists in as little as 1+o(1) bits per unitig. Hence, one inverted list per unitig is stored in the index with almost no space/time overhead. By combining this property with simple but effective compression methods for inverted lists, the index achieves very small space.&#13;
We implement these methods in a tool called Fulgor. Compared to Themisto, the prior state of the art, Fulgor indexes a heterogeneous collection of 30,691 bacterial genomes in 3.8× less space, a collection of 150,000 Salmonella enterica genomes in approximately 2× less space, is at least twice as fast for color queries, and is 2-6 × faster to construct.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Jason Fan and Noor Pratap Singh and Jamshed Khan and Giulio Ermanno Pibiri and Rob Patro</dc:contributor>
          <dc:date>2023</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.WABI.2023.18</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-186446</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.18</dc:identifier>
          <dc:language>eng</dc:language>
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