CoTRA: an integrated R/Shiny framework for transparent bulk and single-cell RNA-seq analysis
Bulk and single-cell RNA sequencing (scRNA-seq) have become essential for investigating disease mechanisms and identifying diagnostic biomarkers. However, the growing volume of transcriptomic data remains difficult to reuse efficiently for many researchers. Downstream analysis often requires multiple statistical, visualization, and reporting tools, creating fragmented workflows that reduce…
CoTRA is an open-source R/Shiny package designed for comprehensive bulk and single-cell RNA-seq analysis. It aims to address the challenges of analyzing large volumes of transcriptomic data by integrating established methods into modular workflows, exposing parameters, and providing alternatives at selected stages. The package supports various aspects of RNA-seq analysis, including quality assessment, differential expression, annotation, enrichment, and reporting for both bulk and scRNA-seq data.
CoTRA runs on workstations or HPC environments without requiring external data submission and is compatible with Linux, Windows, and macOS systems. When compared to 14 other platforms for bulk RNA-seq and scRNA-seq, CoTRA supported 46 out of 49 predefined functionality criteria. A validation study using published rd10 retinal bulk RNA-seq data found 1,947 shared differentially expressed genes with consistent direction and strong log2 fold-change agreement, demonstrating the reliability of CoTRA's analysis.
In a retinal scRNA-seq case study, CoTRA successfully performed appropriate clustering, cell-type resolution analysis, and pathway activity scoring. Overall, CoTRA offers a graphical environment for RNA-seq analysis while maintaining parameter transparency, methodological flexibility, and reproducible outputs. The source code is freely available, allowing researchers to utilize this powerful tool for their own RNA-seq analysis needs.
Written by urgent.news from bioRxiv's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
