HTGAnalyzer: An accessible R package with a web interface for enhanced transcriptomic analysis in precision medicine

Area of Science:

• Molecular Biology
• Bioinformatics
• Clinical Diagnostics

Background:

• Transcriptomics holds promise for personalized medicine but faces challenges with formalin-fixed, paraffin-embedded (FFPE) samples.
• Automation and simplified workflows are crucial for integrating transcriptomics into routine clinical practice.
• The closure of HTG necessitates alternative solutions for analyzing HTG data.

Purpose of the Study:

• To develop HTGAnalyzer, an R package for automated bulk transcriptomics analysis.
• To provide a user-friendly tool for clinical and molecular diagnostics, integrating transcriptomic and clinical data.
• To offer robust quality control and advanced analytics for HTG and RNA-seq data.

Main Methods:

• Development of an R package, HTGAnalyzer, with a fully automatic pipeline.
• Integration of sample quality control, data normalization, and transcriptomic/clinical analyses.
• Implementation of a user-friendly Shiny app, Docker compatibility, and clinical data management system connectivity.

Main Results:

• HTGAnalyzer enables bulk transcriptomics analysis from diverse data sources (HTG EdgeSeq, RNA-seq).
• The package provides tailored quality control and analysis for HTG data, addressing a critical gap.
• A complete analytical workflow is delivered in under 20 minutes on a standard PC.
• Application to a vulvar cancer cohort generated interpretable reports with rich visual outputs.

Conclusions:

• HTGAnalyzer offers a unified tool for robust quality control and advanced transcriptomics analytics.
• The package supports the clinical application of transcriptomics in precision medicine.
• Its ease of use and speed facilitate integration into routine diagnostic workflows.