Run Plan Validator: A Platform-Agnostic, lane-Aware Pre-Run Barcode Validation Framework for Preventing Deterministic Index Collisions in High-Throughput Sequencing

Abstract

Barcode misassignment remains a significant source of sample cross-contamination and data loss in multiplexed high-throughput sequencing. While advances in dual indexing and platform chemistry have reduced stochastic index hopping, deterministic index collisions—where two or more samples share identical barcode sequences within the same demultiplexing scope—remain entirely preventable yet continue to occur in operational sequencing pipelines. Existing tools detect conflicts post-sequencing, at which point remediation is impossible. We present RunPlanValidator, an open-source, platform-agnostic pre-run barcode validation framework designed to prevent deterministic index collisions prior to sequencing. The framework supports heterogeneous run designs, including mixed single- and dual-index libraries, variable index lengths (6–10 bp), multi-sheet run plans, and optional lane-aware demultiplexing consistent with Illumina NovaSeq and MGI platforms. In contrast to mismatch-based barcode design filters that over-restrict operational workflows, RunPlanValidator flags only index configurations guaranteed to cause demultiplexing ambiguity. Evaluation on real-world run plans (2–700 samples per run) demonstrated elimination of deterministic index clashes without rejecting valid operational reuse patterns. Deterministic pre-run barcode validation offers a low-cost, high-impact intervention to improve sequencing reliability, reduce preventable run failures, and enhance reproducibility across platforms. RunPlanValidator is deployable via command-line and graphical interfaces, enabling adoption by both bioinformaticians and laboratory personnel.