OmicsBraid - Covariance-Aware Inference of Cross-Omic Effect Trajectories

A research-oriented statistical framework for comparing standardized biological effects across matched omics layers. It estimates layer-specific standardized effects, accounts for cross-omic dependence using matched-subject bootstrap correlations, tests multivariate omnibus evidence, synthesizes consensus effects with generalized least squares, quantifies cross-omic heterogeneity, performs practical-equivalence testing, fits covariance-aware ordered GLS effect trajectories, classifies hierarchical cross-layer effect patterns with separate confirmatory and suggestive states, supports analytic and subject-bootstrap confidence intervals for layer and consensus effects, supports empirical matched-subject permutation and centered-bootstrap calibration of omnibus and heterogeneity tests for non-Gaussian settings, and creates evidence-forest and effect-braid visualizations. The package is designed for analysis-ready bulk multi-omics data or externally estimated summary statistics. It does not perform raw sequencing or mass-spectrometry preprocessing.