RuNIE (Rust Native Inference Engine): An Open-Source Architecture for Autonomous Bioinformatics Pipeline Synthesis, Blinded Validation, and Bayesian Scope-Depth Auditing

A technical preprint monograph documenting the 35 native Rust engines of crvscience-labs, the 4-generation parallel-tempering GA-MCMC pipeline synthesizer, Dual-Pass SHA-256 blinded validation, why an orthogonal multi-stage Scope × 0–5 Beaker Bayesian depth system replaces frequentist supermatrix p-values, and a synthesis of 26 Flagged Critical Reports. Modern bioinformatics workflows often chain separate command-line programs through fragile shell scripts, where hidden formatting mismatches, database misannotations, and model misspecifications can produce 100% bootstrap support and tiny p-values for incorrect evolutionary trees. Here we present RuNIE (Rust Native Inference Engine), an open-source (GNU GPL-3.0) Rust architecture that unites 35 head-to-head validated bioinformatics tools with Dual-Pass SHA-256 blinded auditing and an orthogonal multi-stage Scope × 0–5 Beaker Bayesian calibration system across 42 validation datasets and 26 Flagged Critical Reports. We present the architecture, mathematical formulation, and full 35-tool validation ledger of CRV Science Labs (bio-suite v0.3.0) and RuNIE (Rust Native Inference Engine, v1.27.0), demonstrating why classical frequentist p-values and bootstrap percentages fail under genome-scale supermatrix variance collapse and how Dual-Pass SHA-256 blinded validation, multi-stage Research Scope tracking, and 0–5 Beaker Bayesian posterior calibration enable reproducible, bias-free computational discovery across 109+ studies. Canonical Preprint URL: https://crvscience.com/labs/preprints/runie-automated-bioinformatics-preprint Zenodo DOI: 10.5281/zenodo.23969276 Open-Source Software Repository (GNU GPL-3.0): https://github.com/bpwhite/crvscience-labs