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improved permutation p-value estimates, python port from originally published matlab code
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README.md

gpdPerm - genral pareto dist. for permutation testing

Python module to improve pvalue estimation from a null distribution that is approximated by permutation testing. Uses a generalized pereto distribution to approximate the tail of the null distribution, as described in Knijnenburg 2009. Authors publicly provided the original analysis as a set of matlab scripts.

To run the full procedure given a test statistic, x0, and a vector of permutations, y, call gdpPerm::est(x0,y)

Knijnenburg 2009 - Knijnenburg et al., Bioinformatics, Vol. 25 ISMB 2009, pages i161-i168

The current version is limited to the maximum likelihood method for performing the fit.

Original code by: Theo Knijnenburg, Institute for Systems Biology, Jan 6 2009 Tranfered from matlab to python by: Ryan Tasseff, Institute for Systems Biology, Dec 2011

license

Original Warranty Disclaimer and Copyright Notice attached to the matlab scripts:

Copyright (C) 2003-2010 Institute for Systems Biology, Seattle, Washington, USA.

The Institute for Systems Biology and the authors make no representation about the suitability or accuracy of this software for any purpose, and makes no warranties, either express or implied, including merchantability and fitness for a particular purpose or that the use of this software will not infringe any third party patents, copyrights, trademarks, or other rights. The software is provided "as is". The Institute for Systems Biology and the authors disclaim any liability stemming from the use of this software. This software is provided to enhance knowledge and encourage progress in the scientific community.

This is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version.

You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA

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