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AllSome Sequence Bloom Trees

Chen Sun, Robert S. Harris, Rayan Chikhi, Paul Medvedev
doi: https://doi.org/10.1101/090464
Chen Sun
1Department of Computer Science and Engineering, The Pennsylvania State University, USA
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Robert S. Harris
2Department of Biology, The Pennsylvania State University, USA
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Rayan Chikhi
3CNRS, CRIStAL, University of Lille, France
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Paul Medvedev
1Department of Computer Science and Engineering, The Pennsylvania State University, USA
4Department of Biochemistry and Molecular Biology, The Pennsylvania State University, USA
5Genome Sciencies Institute of the Huck, The Pennsylvania State University, USA
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  • For correspondence: pashadag@cse.psu.edu
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Abstract

The ubiquity of next generation sequencing has transformed the size and nature of many databases, pushing the boundaries of current indexing and searching methods. One particular example is a database of 2,652 human RNA-seq experiments uploaded to the Sequence Read Archive. Recently, Solomon and Kingsford proposed the Sequence Bloom Tree data structure and demonstrated how it can be used to accurately identify SRA samples that have a transcript of interest potentially expressed. In this paper, we propose an improvement called the AllSome Sequence Bloom Tree. Results show that our new data structure significantly improves performance, reducing the tree construction time by 52.7% and query time by 39 - 85%. Notably, it can query a batch of 198,074 queries in under 8 hours(compared to around two days previously) and a whole set of k-mers from a sequencing experiment(about 27 mil k-mers) in under 11 minutes.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted December 02, 2016.
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AllSome Sequence Bloom Trees
Chen Sun, Robert S. Harris, Rayan Chikhi, Paul Medvedev
bioRxiv 090464; doi: https://doi.org/10.1101/090464
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AllSome Sequence Bloom Trees
Chen Sun, Robert S. Harris, Rayan Chikhi, Paul Medvedev
bioRxiv 090464; doi: https://doi.org/10.1101/090464

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