Several challenges are related to metagenomics, one of which is the data management. A related central concept is k-mer which means a possible subsequence of length k from a DNA (sub)sequence. In this work, the focus is on indexing k-mers and supporting box queries where a query string of length k might have multiple allowed nucleobases per position. A novel index structure: ND-GiST is introduced which has capability to handle box queries. Comparing it with full table scan and the traditional B-tree, the performance results of ND-GiST are encouraging.
CITATION STYLE
Szalai-Gindl, J. M., Kiss, A., Halász, G., Dobos, L., & Csabai, I. (2019). ND-GIST: A novel method for disk-resident k-mer indexing. In Advances in Intelligent Systems and Computing (Vol. 931, pp. 663–672). Springer Verlag. https://doi.org/10.1007/978-3-030-16184-2_63
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