A Novel Approach for Compressing Phylogenetic Trees

  • Suzanne J. Matthews
  • Seung-Jin Sul
  • Tiffani L. Williams
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6053)


Phylogenetic trees are tree structures that depict relationships between organisms. Popular analysis techniques often produce large collections of candidate trees, which are expensive to store. We introduce TreeZip, a novel algorithm to compress phylogenetic trees based on their shared evolutionary relationships. We evaluate TreeZip’s performance on fourteen tree collections ranging from 2,505 trees on 328 taxa to 150,000 trees on 525 taxa corresponding to 0.6 MB to 434 MB in storage. Our results show that TreeZip is very effective, typically compressing a tree file to less than 2% of its original size. When coupled with standard compression methods such as 7zip, TreeZip can compress a file to less than 1% of its original size. Our results strongly suggest that TreeZip is very effective at compressing phylogenetic trees, which allows for easier exchange of data with colleagues around the world.


Compression Ratio Evolutionary Tree Hash Table Compression Algorithm Good Compression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Suzanne J. Matthews
    • 1
  • Seung-Jin Sul
    • 1
  • Tiffani L. Williams
    • 1
  1. 1.Texas A&M UniversityCollege StationUSA

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