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Improving the efficiency of de Bruijn graph construction using compact universal hitting sets

Yael Ben-Ari, Lianrong Pu, View ORCID ProfileYaron Orenstein, View ORCID ProfileRon Shamir
doi: https://doi.org/10.1101/2020.11.08.373050
Yael Ben-Ari
1Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
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Lianrong Pu
1Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
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Yaron Orenstein
2School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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Ron Shamir
1Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
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  • ORCID record for Ron Shamir
  • For correspondence: rshamir@tau.ac.il
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Abstract

High-throughput sequencing techniques generate large volumes of DNA sequencing data at ultra-fast speed and extremely low cost. As a consequence, sequencing techniques have become ubiquitous in biomedical research and are used in hundreds of genomic applications. Efficient data structures and algorithms have been developed to handle the large datasets produced by these techniques. The prevailing method to index DNA sequences in those data structures and algorithms is by k-mers (k-long substrings) known as minimizers. Minimizers are the smallest k-mers selected in every consecutive window of a fixed length in a sequence, where the smallest is determined according to a predefined order, e.g., lexicographic. Recently, a new k-mer order based on a universal hitting set (UHS) was suggested. While several studies have shown that orders based on a small UHS have improved properties, the utility of using a small UHS in high-throughput sequencing analysis tasks has not been demonstrated to date.

Here, we demonstrate the practical benefit of UHSs for the first time, in the genome assembly task. Reconstructing a genome from billions of short reads is a fundamental task in high-throughput sequencing analyses. de Bruijn graph construction is a key step in genome assembly, which often requires very large amounts of memory and long computation time. A critical bottleneck lies in the partitioning of DNA sequences into bins. The sequences in each bin are assembled separately, and the final de Bruijn graph is constructed by merging the bin-specific subgraphs. We incorporated a UHS-based order in the bin partition step of the Minimum Substring Partitioning algorithm of Li et al. (2013). Using a UHS-based order instead of lexicographic- or random-ordered minimizers produced lower density minimizers with more balanced bin partitioning, which led to a reduction in both runtime and memory usage.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/Shamir-Lab/MSP_UHS

Copyright 
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 November 08, 2020.
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Improving the efficiency of de Bruijn graph construction using compact universal hitting sets
Yael Ben-Ari, Lianrong Pu, Yaron Orenstein, Ron Shamir
bioRxiv 2020.11.08.373050; doi: https://doi.org/10.1101/2020.11.08.373050
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Improving the efficiency of de Bruijn graph construction using compact universal hitting sets
Yael Ben-Ari, Lianrong Pu, Yaron Orenstein, Ron Shamir
bioRxiv 2020.11.08.373050; doi: https://doi.org/10.1101/2020.11.08.373050

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