Package: xlmhglite
XL-mHG LiteUseful links:Documentation|Source code|Bug reports|||||xlmhgis an efficient Python/Cython implementation of the semiparametricXL-mHG testfor enrichment in ranked lists. The XL-mHG test is an extension
of the nonparametricmHG test, which was developed byDr. Zohar
Yakhiniand colleagues.xlmhgliteis a fork of the originalxlmhgpackage (which is unfortunately no longer being maintained).
This fork was updated to support modern Python versions (Python >=3.8), fix bugs in the original implementation,
and reduce the mandatory dependencies of the project to a minimum.
To that end, the plotting functionality ofxlmhgis not part of the corexlmhglitepackage, instead being an optional requirement.InstallationTo install the core (“lite”) version ofxlmhglite:
.. code-block:: bash$ pip install xlmhgliteTo install the complete version ofxlmhglite(including the plotting functionality):
.. code-block:: bash$ pip install xlmhglite[‘all’]Getting startedThexlmhglitepackage provides two functions (one simple and more more advanced)
for performing XL-mHG tests. These functions are documented in theUser Manual. Here’s a quick example using the “simple” test function:importxlmhglitestat,cutoff,pval=xlmhglite.xlmhg_test(v,X,L)Where:vis the ranked list of 0’s and 1’s, represented by a NumPy array of
integers,XandLare the XL-mHG parameters, and the return values have
the following meanings:stat: The XL-mHG test statisticcutoff: The cutoff at which XL-mHG test statistic was attainedpval: The XL-mHG p-valueXL-mHG Lite DocumentationPlease refer to theXL-mHG User Manual.Citing XL-mHGIf you use the XL-mHG test in your research, please citeEden et al. (PLoS
Comput Biol, 2007)andWagner (PLoS One, 2015).Copyright and LicenseCopyright (c) 2015-2019 Florian WagnerRedistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.

* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.

* Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.

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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.History1.1.0 (2023-06-11)This version improves clarity of warning messages and addresses some additional bugs.
Moreover, the project has been transitioned to use pyproject.toml and setup.cfg, and old code was cleaned up for better maintainability.ChangedWarning messages regarding failed import of the cython module were made more informative.Transitioned the project to use pyproject.toml and setup.cfg, and cleaned up legacy code from setup.py.FixedFixed bug where calculating enrichment scores using the pure Python implementation would raise an AttributeError.Fixed bug where the pure Python implementation would raise an ImportError if numba is not already installed on the system.1.0.1 (2023-06-11)Minor patch addressing installation issues.1.0.0 (2023-06-10)First stable release.