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A resource-frugal probabilistic dictionary and applications in (meta)genomics

Camille Marchet 1 Antoine Limasset 1 Lucie Bittner 2 Pierre Peterlongo 1
1 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Indexing massive data sets is extremely expensive for large scale problems. In many fields, huge amounts of data are currently generated, however extracting meaningful information from voluminous data sets, such as computing similarity between elements, is far from being trivial. It remains nonetheless a fundamental need. This work proposes a probabilistic data structure based on a minimal perfect hash function for indexing large sets of keys. Our structure out-compete the hash table for construction, query times and for memory usage, in the case of the indexation of a static set. To illustrate the impact of algorithms performances, we provide two applications based on similarity computation between collections of sequences, and for which this calculation is an expensive but required operation. In particular, we show a practical case in which other bioinformatics tools fail to scale up the tested data set or provide lower recall quality results.
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https://hal.inria.fr/hal-01322440
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Submitted on : Friday, May 27, 2016 - 11:00:32 AM
Last modification on : Friday, July 10, 2020 - 4:03:18 PM
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  • HAL Id : hal-01322440, version 1
  • ARXIV : 1605.08319

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Camille Marchet, Antoine Limasset, Lucie Bittner, Pierre Peterlongo. A resource-frugal probabilistic dictionary and applications in (meta)genomics. Discrete Applied Mathematics, Elsevier, 2020. ⟨hal-01322440⟩

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