Innovative Bioinformatics Tool Simplifies Transcriptomic Data Analysis for Precision Medicine

The Barcelona Institute for Global Health (ISGlobal) has introduced HTGAnalyzer, a cutting-edge, easy-to-use bioinformatics software designed to facilitate advanced transcriptomic data analysis. Built within the R statistical environment, this open-source package streamlines complex analytical workflows, making them accessible to researchers and clinicians without specialized bioinformatics training.

Transcriptomic analysis involves examining all messenger RNA molecules within a cell at a specific moment, providing insights into gene expression patterns vital for precision medicine—an approach that tailors treatment based on individual genetic profiles. However, despite its potential, widespread clinical implementation has been hindered by the technical complexity of data processing.

HTGAnalyzer addresses these challenges by automating tasks such as data import, normalization, quality control, differential gene expression assessment, functional enrichment, tumor microenvironment profiling, and survival analysis. It leverages patients' molecular data to uncover biological differences and supports clinical interpretations, making the approach more feasible for routine use.

Validation studies employed datasets including RNA-seq data from The Cancer Genome Atlas (TCGA) and a cohort of patients with vulvar cancer, a rare malignancy. Results demonstrated HTGAnalyzer’s capability to identify key differentially expressed genes, immune profiles, and pathways linked to cancer and patient survival, showcasing its potential for applications in cancer diagnosis, treatment planning, and prognosis.

This development aims to bridge the divide between complex bioinformatics and clinical practice, empowering professionals to perform essential transcriptomic analyses. Consequently, HTGAnalyzer enhances the integration of molecular insights into personalized treatment strategies, advancing the field of precision medicine.

For more information, see the full publication: Laia Díez-Ahijado et al, "HTGAnalyzer: An accessible R package with a web interface for enhanced transcriptomic analysis in precision medicine," published in Computers in Biology and Medicine (2025).