Abstract
K-mer Mapping, an internal process for De Novo NGS genome fragments assembly methods, constitutes a computational challenge due to its high main memory consumption. We present a study of index-based methods to deal with this problem, considering a RDBMS environment. We propose an ad-hoc I/O cost model and analyze the performance of hash and B-tree versions for index structures. Furthermore, we present a novel approach for an index based on hashing that takes into account the notion of minimum substrings. An actual RDBMS implementation for experiments with a sugarcane dataset shows that one can obtain considerable performance gains while reducing main memory requirements.
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de Armas, E.M., Ferreira, P.C.G., Haeusler, E.H., de Holanda, M.T., Lifschitz, S. (2020). K-mer Mapping and RDBMS Indexes. In: Kowada, L., de Oliveira, D. (eds) Advances in Bioinformatics and Computational Biology. BSB 2019. Lecture Notes in Computer Science(), vol 11347. Springer, Cham. https://doi.org/10.1007/978-3-030-46417-2_7
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DOI: https://doi.org/10.1007/978-3-030-46417-2_7
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