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Open Access Publications from the University of California

PyCogent: a toolkit for making sense from sequence.

  • Author(s): Knight, Rob
  • Maxwell, Peter
  • Birmingham, Amanda
  • Carnes, Jason
  • Caporaso, J Gregory
  • Easton, Brett C
  • Eaton, Michael
  • Hamady, Micah
  • Lindsay, Helen
  • Liu, Zongzhi
  • Lozupone, Catherine
  • McDonald, Daniel
  • Robeson, Michael
  • Sammut, Raymond
  • Smit, Sandra
  • Wakefield, Matthew J
  • Widmann, Jeremy
  • Wikman, Shandy
  • Wilson, Stephanie
  • Ying, Hua
  • Huttley, Gavin A
  • et al.

We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from

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