Workshop: Graph compression approaches in assembly

Jason Pell, Arend Hintze, Rosangela Canino-Koning, Adina Howe, James M. Tiedje, Charles Brown

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Using a probabilistic data structure to store DNA assembly graphs results in a significant memory savings over other methods. As long as the Bloom filter remains below a specific false positive rate, it remains possible to traverse the graph. Using a Bloom filter has many applications in metagenomics, mRNAseq, read filtering, and error correction. We are currently exploring these possibilities and more.

Original languageEnglish (US)
Title of host publication2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012
DOIs
StatePublished - May 8 2012
Externally publishedYes
Event2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012 - Las Vegas, NV, United States
Duration: Feb 23 2012Feb 25 2012

Other

Other2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012
CountryUnited States
CityLas Vegas, NV
Period2/23/122/25/12

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Keywords

  • Bloom filters
  • de Bruijn graphs
  • k-mers
  • metagenomics
  • next-generation sequencing

ASJC Scopus subject areas

  • Biomedical Engineering
  • Applied Mathematics

Cite this

Pell, J., Hintze, A., Canino-Koning, R., Howe, A., Tiedje, J. M., & Brown, C. (2012). Workshop: Graph compression approaches in assembly. In 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012 [6182675] https://doi.org/10.1109/ICCABS.2012.6182675