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DeeZ: reference-based compression by local assembly

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Acknowledgements

We thank the Natural Sciences and Engineering Research Council of Canada (NSERC) for the Discovery Frontiers “Cancer Genome Collaboratory” project, Discovery Grants program and Genome Canada (S.C.S.) and the Vanier Canada Graduate Scholarship program (I.N.) for funding this research. We also thank L. Stein, T. Beck and H. Babaran as well as L. Ding and R.J. Mashi for testing and benchmarking the performance of DeeZ. We thank J. Bonfield for helping us to improve DeeZ. We thank J. Dale, G. Asimenos and S. Batzoglou for support in the initial stages of this research.

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Author notes

  1. Faraz Hach and Ibrahim Numanagic: These authors contributed equally to this work.

Authors and Affiliations

  1. School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada

    Faraz Hach, Ibrahim Numanagic & S Cenk Sahinalp

  2. Vancouver Prostate Centre, Vancouver, British Columbia, Canada

    Faraz Hach & S Cenk Sahinalp

  3. Division of Computer Science, School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA

    Ibrahim Numanagic & S Cenk Sahinalp

Authors
  1. Faraz Hach
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  2. Ibrahim Numanagic
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  3. S Cenk Sahinalp
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Corresponding author

Correspondence to S Cenk Sahinalp.

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The authors declare no competing financial interests.

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Hach, F., Numanagic, I. & Sahinalp, S. DeeZ: reference-based compression by local assembly. Nat Methods 11, 1082–1084 (2014). https://doi.org/10.1038/nmeth.3133

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