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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. To solve this problem, we describe an efficient\n                    <jats:italic>colored de Bruijn<\/jats:italic>\n                    graph index, arising as the combination of a\n                    <jats:italic>k<\/jats:italic>\n                    -mer dictionary with a compressed inverted index. The proposed index takes full advantage of the fact that unitigs in the colored compacted de Bruijn graph are\n                    <jats:italic>monochromatic<\/jats:italic>\n                    (i.e., all\n                    <jats:italic>k<\/jats:italic>\n                    -mers in a unitig have the same set of references of origin, or\n                    <jats:italic>color<\/jats:italic>\n                    ). Specifically, the unitigs are kept in the dictionary in color order, thereby allowing for the encoding of the map from\n                    <jats:italic>k<\/jats:italic>\n                    -mers to their colors in as little as 1 +\n                    <jats:italic>o<\/jats:italic>\n                    (1) bits per unitig. Hence, one color per unitig is stored in the index with almost no space\/time overhead. By combining this property with simple but effective compression methods for integer lists, the index achieves very small space. We implement these methods in a tool called , and conduct an extensive experimental analysis to demonstrate the improvement of our tool over previous solutions. For example, compared to \u2014the strongest competitor in terms of index space vs. query time trade-off\u2014 requires significantly less space (up to 43% less space for a collection of 150,000\n                    <jats:italic>Salmonella enterica<\/jats:italic>\n                    genomes), is at least twice as fast for color queries, and is 2\u20136\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$\\times$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mo>\u00d7<\/mml:mo>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    faster to construct.\n                  <\/jats:p>","DOI":"10.1186\/s13015-024-00251-9","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T13:03:02Z","timestamp":1705928582000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Fulgor: a fast and compact k-mer index for large-scale matching and color queries"],"prefix":"10.1186","volume":"19","author":[{"given":"Jason","family":"Fan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jamshed","family":"Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noor Pratap","family":"Singh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulio Ermanno","family":"Pibiri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rob","family":"Patro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,1,22]]},"reference":[{"issue":"1","key":"251_CR1","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1186\/s13059-020-02159-0","volume":"21","author":"N LaPierre","year":"2020","unstructured":"LaPierre N, Alser M, Eskin E, Koslicki D, Mangul S. 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