The Omics Molecule Extractor: A Web Application for the Selection of Potential Biomarker Panels

Selecting molecular panels that are applicable to classify the health state of patients is a common task in omics data analysis. Existing software for molecule selection lacks features to select molecule panels from large data sets, requires programming experience, or lacks user-friendly interfaces. We present the Omics Molecule Extractor (OMEx), an open-source web application providing a user-friendly workflow for selecting molecules and molecule panels for sample classification from large data sets. OMEx's user interface provides interactive visualization for exploring input data and analysis results. The feature selection strategy underlying the algorithm is based on machine learning and has not been available in any software with a user interface. Extensive testing using synthetic data sets with known ground truth showed that the algorithm discovers group-separating molecules with high precision. Additionally, OMEx was tested on five real-world omics data sets, demonstrating high reproducibility and overlap with reported molecules from other feature selection methods, while also reporting alternative molecules of interest. OMEx is freely available at https://mdoa-tools.bi.denbi.de/omex/home.