RNAsum: A tool for personalised genome and transcriptome interpretation for improved cancer diagnostics

The integration of whole-genome sequencing (WGS) and whole-transcriptome sequencing (WTS) has revolutionized cancer diagnostics, enabling comprehensive molecular profiling of tumours. While WGS uncovers genomic alterations such as single nucleotide variants (SNVs), structural variants (SVs), and copy number changes, WTS provides complementary insights into transcriptomic changes, including gene expression levels, alternative splicing, and fusion events. Together, these technologies offer unparalleled potential to guide precision oncology by identifying actionable biomarkers and stratifying patients for targeted therapies or clinical trials.

However, the integration of WGS and WTS data remains a significant bioinformatics challenge due to biological variability, tumour-specific complexities, and the lack of harmonized reference datasets. To address this, we developed RNAsum, an open-source tool designed to combine and interpret WGS and WTS data from individual cancer patient samples. RNAsum compares patient data against curated cohorts from The Cancer Genome Atlas (TCGA) and integrates quantitative expression data with genomic insights to enhance diagnostic accuracy, validate genomic findings, and prioritize clinically relevant alterations.

We demonstrate the utility of RNAsum through case studies, showcasing its ability to confirm clinically reportable variants, refine diagnoses, and identify novel therapeutic targets. By bridging the gap between genome and transcriptome analyses, RNAsum represents a step forward in the routine clinical application of multi-omics for personalized cancer care. The tool is freely available as an R package on GitHub, supporting accessibility and scalability for diverse research and clinical settings.