MOSClip is a topological pathway analysis tool to test survival association of pathways in a multi-omic framework.
MOSClip R package implements a statistical approach able to integrate multi-omic data and look for survival associated gene modules. It integrates multiple omics - trascriptomics, methylomics, genomic mutations, and genomic copy number variations - using various data dimensionality reduction strategies and multivariate models. Exploiting graph theory, pathways can be decomposed into their connected components, that we call modules. The analysis can then be performed at the level of entire pathways or pathway modules. MOSClip pathway analysis serves two primary purposes: testing the survival association of pathways or modules using the Cox proportional hazard model, and conducting a two-class analysis with a generalized linear model. Additionally, the package offers valuable graphical tools to visualize and interpret the results.
You can install MOSClip directly from GitHub writing the following commands in your R console.
# Install the package from Bioconductor
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("MOSClip")
# Install the package from GitHub
# devtools::install_github("CaluraLab/MOSClip")
Paolo Martini, Monica Chiogna, Enrica Calura, and Chiara Romualdi. 2019. “MOSClip: Multi-Omic and Survival Pathway Analysis for the Identification of Survival Associated Gene and Modules.” Nucleic Acids Research 47 (14): e80. https://doi.org/10.1093/nar/gkz324
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