NETWORK-BASED MULTI-OMICS INTEGRATION TO PRIORITIZE FEATURES IN GEMMA OMICS DATASETS

NETWORK-BASED MULTI-OMICS INTEGRATION TO PRIORITIZE FEATURES IN GEMMA OMICS DATASETS

We developed a pipeline for the integrative analysis of gene-related, metabolite-related and microbiota species-related data. The pipeline relies on a network of molecular interactions and functional interactions (interactome), and on the network analysis tool “mND” (multi-layer Network Diffusion) [doi: 10.1093/bioinformatics/btz652].

Gene-related, metabolite-related and microbiota species-related input scores from GEMMA omics are mapped on the interactome (see “A network of molecular and functional interactions for GEMMA multi-omics data analysis”), and mND is used to prioritize features (genes, metabolites and microbial species), based on their input scores and reciprocal network proximity. The output feature-level score is statistically assessed based on two distinct null models, which test the relation between output scores and input scores, and between output scores and feature-feature interactions.

The top scoring features are selected based on feature-level score, network topology scores (e.g. modularity, connected components), and joint analysis of the two (e.g. distribution of feature score over the network).

We plan to release this pipeline within December 2025.