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PyCogent: a toolkit for making sense from sequence
- 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.
Published Web Location
https://doi.org/10.1186/gb-2007-8-8-r171Abstract
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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