{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:14:35Z","timestamp":1787008475225,"version":"3.56.0"},"reference-count":2,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Summary: Counting all the k-mers (substrings of length k) in DNA\/RNA sequencing reads is the preliminary step of many bioinformatics applications. However, state of the art k-mer counting methods require that a large data structure resides in memory. Such structure typically grows with the number of distinct k-mers to count. We present a new streaming algorithm for k-mer counting, called DSK (disk streaming of k-mers), which only requires a fixed user-defined amount of memory and disk space. This approach realizes a memory, time and disk trade-off. The multi-set of all k-mers present in the reads is partitioned, and partitions are saved to disk. Then, each partition is separately loaded in memory in a temporary hash table. The k-mer counts are returned by traversing each hash table. Low-abundance k-mers are optionally filtered. DSK is the first approach that is able to count all the 27-mers of a human genome dataset using only 4.0 GB of memory and moderate disk space (160 GB), in 17.9 h. DSK can replace a popular k-mer counting software (Jellyfish) on small-memory servers.<\/jats:p>\n                  <jats:p>Availability: \u00a0http:\/\/minia.genouest.org\/dsk<\/jats:p>\n                  <jats:p>Contact: \u00a0rayan.chikhi@ens-cachan.org<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt020","type":"journal-article","created":{"date-parts":[[2013,1,17]],"date-time":"2013-01-17T02:02:12Z","timestamp":1358388132000},"page":"652-653","source":"Crossref","is-referenced-by-count":269,"title":["DSK:\n                    <i>k<\/i>\n                    -mer counting with very low memory usage"],"prefix":"10.1093","volume":"29","author":[{"given":"Guillaume","family":"Rizk","sequence":"first","affiliation":[{"name":"1 Algorizk, 75013 Paris and 2ENS Cachan Brittany\/IRISA, Campus de Beaulieu, 35700 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dominique","family":"Lavenier","sequence":"additional","affiliation":[{"name":"1 Algorizk, 75013 Paris and 2ENS Cachan Brittany\/IRISA, Campus de Beaulieu, 35700 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rayan","family":"Chikhi","sequence":"additional","affiliation":[{"name":"1 Algorizk, 75013 Paris and 2ENS Cachan Brittany\/IRISA, Campus de Beaulieu, 35700 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2013,1,16]]},"reference":[{"key":"2023051607330453100_btt020-B1","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1093\/bioinformatics\/btr011","article-title":"A fast, lock-free approach for efficient parallel counting of occurrences of k-mers","volume":"27","author":"Mar\u00e7ais","year":"2011","journal-title":"Bioinformatics"},{"key":"2023051607330453100_btt020-B2","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1186\/1471-2105-12-333","article-title":"Efficient counting of k-mers in DNA sequences using a bloom filter","volume":"12","author":"Melsted","year":"2011","journal-title":"BMC Bioinformatics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/29\/5\/652\/50335664\/bioinformatics_29_5_652.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/29\/5\/652\/50335664\/bioinformatics_29_5_652.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T03:54:26Z","timestamp":1684209266000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/29\/5\/652\/253092"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,1,16]]},"references-count":2,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2013,3,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btt020","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2013,3,1]]},"published":{"date-parts":[[2013,1,16]]}}}