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01625nam a2200169Ia 4500 |
| 001 |
10.1093-bioinformatics-btac245 |
| 008 |
220706s2022 CNT 000 0 und d |
| 020 |
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|a 13674811 (ISSN)
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| 245 |
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|a Sparse and skew hashing of K-mers
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| 260 |
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|b NLM (Medline)
|c 2022
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| 856 |
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|z View Fulltext in Publisher
|u https://doi.org/10.1093/bioinformatics/btac245
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| 520 |
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|a MOTIVATION: A dictionary of k-mers is a data structure that stores a set of n distinct k-mers and supports membership queries. This data structure is at the hearth of many important tasks in computational biology. High-throughput sequencing of DNA can produce very large k-mer sets, in the size of billions of strings-in such cases, the memory consumption and query efficiency of the data structure is a concrete challenge. RESULTS: To tackle this problem, we describe a compressed and associative dictionary for k-mers, that is: a data structure where strings are represented in compact form and each of them is associated to a unique integer identifier in the range [0,n). We show that some statistical properties of k-mer minimizers can be exploited by minimal perfect hashing to substantially improve the space/time trade-off of the dictionary compared to the best-known solutions. AVAILABILITY AND IMPLEMENTATION: https://github.com/jermp/sshash. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. © The Author(s) 2022. Published by Oxford University Press.
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|a article
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|a bioinformatics
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| 650 |
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|a time trade-off method
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| 700 |
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|a Pibiri, G.E.
|e author
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| 773 |
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|t Bioinformatics (Oxford, England)
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