GenePioneer: A Comprehensive Python Package for Identification of Essential Genes and Modules in Cancer
Abstract
Summary
We propose a network-based unsupervised learning model to identify essential cancer genes and modules for 12 different cancer types, supported by a Python package for practical application. The model constructs a gene network from frequently mutated genes and biological processes, ranks genes using topological features, and detects critical modules. Evaluation across cancer types confirms its effectiveness in prioritizing cancer-related genes and uncovering relevant modules. The Python package allows users to input gene lists, retrieve rankings, and identify associated modules. This work providing a robust method for gene prioritization and module detection, along with a user-friendly package to support research and clinical decision-making in cancer genomics.
Availability
<monospace>GenePioneer</monospace> is released as an open-source software under the MIT license. The source code is available on GitHub at <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/Golnazthr/ModuleDetection">https://github.com/Golnazthr/ModuleDetection</ext-link>
Contact
<email>golnazt@kth.se</email> and <email>haerian.amirhossein@gmail.com</email>
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