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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).

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