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. Methodological components draw on standardized mean-difference estimation described by Hedges (1981) <doi:10.3102/10769986006002107>, bootstrap resampling described by Efron (1979) <doi:10.1214/aos/1176344552>, and two one-sided equivalence testing described by Schuirmann (1987) <doi:10.1007/BF01068419>.

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