Using cascading Bloom filters to improve the memory usage for de Brujin graphs

Kamil Salikhov, Gustavo Sacomoto, Gregory Kucherov

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)


Background: De Brujin graphs are widely used in bioinformatics for processing next-generation sequencing data. Due to a very large size of NGS datasets, it is essential to represent de Bruijn graphs compactly, and several approaches to this problem have been proposed recently. Results: In this work, we show how to reduce the memory required by the data structure of Chikhi and Rizk (WABI'12) that represents de Brujin graphs using Bloom filters. Our method requires 30% to 40% less memory with respect to their method, with insignificant impact on construction time. At the same time, our experiments showed a better query time compared to the method of Chikhi and Rizk.Conclusion: The proposed data structure constitutes, to our knowledge, currently the most efficient practical representation of de Bruijn graphs.

Original languageEnglish
Article number2
JournalAlgorithms for Molecular Biology
Issue number1
Publication statusPublished - 24 Feb 2014
Externally publishedYes


  • Bloom filter
  • de Brujin graph
  • Genome assembly
  • Next-generation sequencing


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