XYomics: detecting sex-dependent molecular mechanisms in omics data
Sophie Le Bars1, Mohamed Soudy1, Enrico Glaab1
1Biomedical Data Science Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, Belvaux 4367, Luxembourg.
Nucleic Acids Research
|July 30, 2026
Summary
XYomics is a new R package for analyzing sex-dependent differences in omics data. It helps uncover sex-specific and sex-dimorphic changes in diseases like Alzheimer's, crucial for precision medicine.
Area of Science:
- Bioinformatics
- Genomics
- Precision Medicine
Background:
- Sex as a Biological Variable (SABV) is crucial for understanding disease, yet current bioinformatics tools lack systematic approaches for sex-related molecular mechanisms.
- Treating sex as a confounding variable can obscure important sex-specific, sex-dimorphic, and sex-modulated biological differences.
- Existing methods often aggregate data across sexes, potentially masking critical sex-dependent disease insights.
Purpose of the Study:
- To introduce XYomics, an open-source R package designed for systematic analysis of sex-dependent alterations in biomedical omics data.
- To enable the identification of sex-specific, sex-dimorphic, and sex-modulated changes at both individual feature and systems levels.
- To facilitate the discovery of sex-specific biomarkers and disease mechanisms often missed in sex-aggregated analyses.
Main Methods:
- XYomics implements dual analytical modes: sex-disease interaction term modeling and sex-stratified analysis with non-significance filtering.
- The package integrates statistical categorization with pathway enrichment and network analysis.
- Utilizes a curated hormone signaling interactome for enhanced biological interpretation.
Main Results:
- XYomics successfully identifies sex-specific, sex-dimorphic, and sex-modulated changes in omics data.
- Demonstrated utility in single-cell RNA sequencing data from Alzheimer's disease patients, revealing largely undetected sex-dimorphic genes.
- Facilitates discovery of sex-specific biomarkers and molecular mechanisms.
Conclusions:
- XYomics provides a systematic approach to analyze sex-dependent omics data, addressing limitations of current bioinformatics tools.
- The package enhances the understanding of sex-related molecular mechanisms in diseases, supporting precision medicine initiatives.
- Enables more comprehensive discovery of sex-specific biological insights previously obscured by sex-aggregated analyses.
Related Concept Videos
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02:50Dosage Compensation
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02:24Ribosome Profiling
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