This repository contains the R code used for the Factor Analysis of Mixed Data (FAMD) as part of our research on the impact of environmental and lifestyle factors on cancer risk. Our study focuses on the role of extracellular vesicle oncomiRs in cancer development, analyzing how these microRNAs respond to various environmental and lifestyle influences.
The study investigated plasma levels of EV-borne oncomiRs in a population with a body mass index > 25 kg/m^2, aiming to understand the regulatory networks of miRNAs in response to exogenous influences. By leveraging the Multivariate Adaptive Regression Splines (MARS) model, we explored interactions between environmental/lifestyle exposures and EV oncomiRs, uncovering non-linear relationships among variables.
FAMD was employed to investigate multivariate relationships among miRNA expressions and exposure variables, serving as a critical tool for understanding the complex interplay between these factors. This analysis facilitated the identification of significant predictors and their non-linear/non-additive effects on miRNA expression, contributing significantly to our comprehension of miRNA regulation in the context of cancer risk factors.
Data/: Contains datasets used for FAMD analysis. Scripts/: R scripts for performing FAMD and subsequent analyses. Results/: Visualizations and output from the FAMD analysis. Docs/: Documentation on data sources, methodology, and findings.
Instructions on how to replicate the FAMD analysis, including requirements for running the R scripts, data format specifications, and step-by-step guides.
Please cite our paper if you use this code or data in your research:
Bollati, V.; Monti, P.; Biganzoli, D.; Marano, G.; Favero, C.; Iodice, S.; Ferrari, L.; Dioni, L.; Bianchi, F.; Pesatori, A.C.; et al. Environmental and Lifestyle Cancer Risk Factors: Shaping Extracellular Vesicle OncomiRs and Paving the Path to Cancer Development. Cancers 2023, 15, 4317. https://doi.org/10.3390/cancers15174317