The package contains functions to:
- perform network diffusion (ND) on molecular networks;
- obtain ND input matrix X0 from gene expression data via kernel estimation;
- permute the vertices of a graph, freely, conserving vertex degree and/or conserving disntinct vertex subsets;
- normalize adjacency matrix;
- normalize ND output matrix Xs;
- calculate gene set scores from Xs;
- create an enrichment map;
- perform over-representation analysis (ORA);
- perform gene-set enrichment analysis (GSEA);
- plot heatmaps of multiple ORA/GSEA runs.
If you use this package please cite the following articles:
- Di Nanni N, Gnocchi M, Moscatelli M, Milanesi L and Mosca E, Gene relevance based on multiple evidences in complex networks, Bioinformatics, Volume 36, Issue 3, 1 February 2020, Pages 865–871, https://doi.org/10.1093/bioinformatics/btz652
- Bersanelli*, M., Mosca*, E., Remondini, D. et al. Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules. Sci Rep 6, 34841 (2016). https://doi.org/10.1038/srep34841
- Chiodi A, Pelucchi P, Mosca E, Cross-talk quantification in molecular networks with application to pathway-pathway and cell-cell interactions. bioRxiv (2023), https://doi.org/10.1101/2023.08.10.552776