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
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...[Show more]
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