<p>Multi-index Bloom filters: a probabilistic data structure for sensitive multi-reference sequence classification with multiple spaced seeds</p>

Justin Chu; Emre Erhan; Hamid Mohamadi; Ben Vandervalk; Jeffery Tse; Readman Chiu; Sarah Yeo; Shaun Jackman; Ka Ming Nip; René L. Warren; Inanc Birol

doi:10.7490/f1000research.1115397.1

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Chu J, Erhan E, Mohamadi H et al. Multi-index Bloom filters: a probabilistic data structure for sensitive multi-reference sequence classification with multiple spaced seeds [version 1; not peer reviewed]. F1000Research 2018, 7:482 (poster) (https://doi.org/10.7490/f1000research.1115397.1)

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Multi-index Bloom filters: a probabilistic data structure for sensitive multi-reference sequence classification with multiple spaced seeds

Justin Chu¹, Emre Erhan, Hamid Mohamadi, Ben Vandervalk, Jeffery Tse, Readman Chiu, Sarah Yeo, Shaun Jackman, Ka Ming Nip, René L. Warren, Inanc Birol

Published 21 Apr 2018 (https://doi.org/10.7490/f1000research.1115397.1)

Author Affiliations

¹ Canada's Michael Smith Genome Sciences Centre, Canada

Copyright © 2018 Chu J et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 21 Apr 2018

Multi-index Bloom filters: a probabilistic data structure for sensitive multi-reference sequence classification with multiple spaced seeds
[version 1; not peer reviewed]

Justin Chu¹, Emre Erhan, Hamid Mohamadi, Ben Vandervalk, Jeffery Tse, Readman Chiu, Sarah Yeo, Shaun Jackman, Ka Ming Nip, René L. Warren, Inanc Birol

Author Affiliations

¹ Canada's Michael Smith Genome Sciences Centre, Canada

Presented at

8th RECOMB Satellite Workshop on Massively Parallel Sequencing (RECOMB-Seq) 2018

21th International Conference on Research in Computational Molecular Biology (RECOMB) 2017

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Spaced seeds, Bloom filters, sequence classification, probabilistic data structures, sequence mapping

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