emMAW : computing minimal absent words in external memory

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Héliou , A , Pissis , S P & Puglisi , S J 2017 , ' emMAW : computing minimal absent words in external memory ' , Bioinformatics , vol. 33 , no. 17 , pp. 2746-2749 . https://doi.org/10.1093/bioinformatics/btx209

Title: emMAW : computing minimal absent words in external memory
Author: Héliou, Alice; Pissis, Solon P.; Puglisi, Simon J.
Contributor organization: Department of Computer Science
Genome-scale Algorithmics research group / Veli Mäkinen
Algorithmic Bioinformatics
Date: 2017-09-01
Language: eng
Number of pages: 4
Belongs to series: Bioinformatics
ISSN: 1367-4803
DOI: https://doi.org/10.1093/bioinformatics/btx209
URI: http://hdl.handle.net/10138/308355
Abstract: Motivation: The biological significance of minimal absent words has been investigated in genomes of organisms from all domains of life. For instance, three minimal absent words of the human genome were found in Ebola virus genomes. There exists an O(n)-time and O(n)-space algorithm for computing all minimal absent words of a sequence of length n on a fixed-sized alphabet based on suffix arrays. A standard implementation of this algorithm, when applied to a large sequence of length n, requires more than 20n bytes of RAM. Such memory requirements are a significant hurdle to the computation of minimal absent words in large datasets. Results: We present emMAW, the first external-memory algorithm for computing minimal absent words. A free open-source implementation of our algorithm is made available. This allows for computation of minimal absent words on far bigger data sets than was previously possible. Our implementation requires less than 3 h on a standard workstation to process the full human genome when as little as 1GB of RAM is made available. We stress that our implementation, despite making use of external memory, is fast; indeed, even on relatively smaller datasets when enough RAM is available to hold all necessary data structures, it is less than two times slower than state-of-theart internal-memory implementations.
1182 Biochemistry, cell and molecular biology
113 Computer and information sciences
111 Mathematics
Peer reviewed: Yes
Usage restriction: openAccess
Self-archived version: acceptedVersion

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