paRDal: Bioinformatics Framework for a Parallel RNA and DNA NGS Analysis in Hereditary Cancer Diagnostics

Germline next-generation sequencing (NGS) is the gold standard for hereditary cancer diagnostics. However, clinical utility is limited by variants of uncertain significance (VUS), which may disrupt mRNA processing; consequences invisible to DNA NGS alone but identifiable by parallel RNA NGS. Here, we present paRDal (parallel RNA/DNA analytical workflow), a containerized, modular framework that integrates matched germline DNA and RNA NGS data into a single diagnostic pipeline. paRDal implements allele-aware two-pass alignment, automated splicing and expression outlier detection, allele-specific expression analysis, and comprehensive variant annotation. A bidirectionally reactive filtering engine enables both DNA-centric (variant-to-function) and RNA-centric (function-to-variant) workflows. An R/Shiny application consolidates multilayered evidence per patient and across cohorts, linking in silico predictions with observed transcriptomic consequences without requiring specialized bioinformatic expertise. Validated on 204 individuals undergoing hereditary cancer genetic testing, paRDal facilitates the application of ACMG/AMP criteria [PVS1(RNA) and PP3], improving diagnostic yield and VUS resolution in clinical germline genomics.