👉 SOX, or the Statistical Modeling Extensions for R, is a package that extends the capabilities of the R programming language for statistical modeling, particularly in bioinformatics and genomics. It provides a suite of tools for fitting various statistical models to biological data, including linear models, generalized linear models, and mixed-effects models. SOX simplifies the process of model selection and validation by offering functions for cross-validation, model comparison using AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion), and diagnostics to assess model fit. It also supports advanced techniques like Bayesian inference and regularization, making it a powerful resource for researchers dealing with complex biological datasets.
