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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.
Abstract

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 http://sourceforge.net/projects/pycogent.

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