xlmhg 2.4.6

XL-mHG: A Semiparametric Test for Enrichment

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This is an efficient Python/Cython implementation of the semiparametric XL-mHG test for enrichment in ranked lists. The XL-mHG test is an extension of the nonparametric mHG test, which was developed by Dr. Zohar Yakhini and colleagues.

Installation

$ pip install xlmhg

Getting started

The xlmhg package provides two functions (one simple and more more advanced) for performing XL-mHG tests. These functions are documented in the User Manual. Here’s a quick example using the “simple” test function:

import xlmhg
stat, cutoff, pval = xlmhg.xlmhg_test(v, X, L)

Where: v is the ranked list of 0’s and 1’s, represented by a NumPy array of integers, X and L are the XL-mHG parameters, and the return values have the following meanings:

• stat: The XL-mHG test statistic

• cutoff: The cutoff at which XL-mHG test statistic was attained

• pval: The XL-mHG p-value

Documentation

Please refer to the XL-mHG User Manual (hosted on ReadTheDocs).

Citing XL-mHG

If you use the XL-mHG test in your research, please cite Eden et al. (PLoS Comput Biol, 2007) and Wagner (PLoS One, 2015).

Copyright and License

Copyright (c) 2015-2017 Florian Wagner

XL-mHG is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License, Version 3,
as published by the Free Software Foundation.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.