CoTRA: a comprehensive R/Shiny framework for transparent bulk and single-cell RNA-seq analysis
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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 transparency and reproducibility, particularly when analyzing scRNA-seq data.
To address this gap, we developed CoTRA (Comprehensive Toolbox for RNA-seq Analysis), an open-source R/Shiny package for bulk and scRNA analysis. CoTRA integrates established methods into modular workflows, exposes parameters, and offers alternatives at selected stages. It supports bulk RNA-seq quality assessment, differential expression, annotation, enrichment, and reporting, as well as scRNA quality control, dimensionality reduction, clustering, marker identification, cell-type annotation, differential abundance, trajectory inference, pathway activity, and cell-cell communication. CoTRA runs on workstations or HPC environments without mandatory external data submission and was tested on Linux, Windows, and macOS. Compared with 14 other platforms for bulk RNA-seq/scRNA-seq, CoTRA supported 46 of 49 predefined functionality criteria. Tool validation using published rd10 retinal bulk RNA-seq identified 1,947 shared differentially expressed genes with concordant direction and strong log2 fold-change agreement. A retinal scRNA-seq case study demonstrated appropriate clustering, cell-type resolved analysis, and pathway activity scoring.
CoTRA provides a graphical environment for bulk and single-cell RNA-seq analysis while retaining parameter transparency, methodological flexibility, and reproducible outputs. Strong concordance with the published bulk RNA-seq analysis supports the workflow consistency, while the single-cell case study demonstrates its applicability to advanced scRNA-seq analysis. The source code is freely available at https://github.com/UmairSeemab/CoTRA .
KEY POINTS
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CoTRA is an open-source R/Shiny framework that provides comprehensive downstream bulk and single-cell RNA-seq analysis within a single graphical environment, reducing the need to move between separate analysis tools.
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CoTRA retains transparency and user control by exposing key analytical parameters and providing alternative established methods for differential expression, marker detection, trajectory inference, pathway activity analysis, and other analytical steps.
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CoTRA supports reproducible and data-controlled analysis through local, institutional server, or HPC execution without mandatory external data submission, together with extensive export, reporting, processed-object, and session-information capabilities.
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Comparative assessment showed full support for 46 of 49 predefined functionality criteria, while retinal case studies demonstrated strong bulk RNA-seq reproducibility, including 1,947 concordant DEGs and Pearson r = 0.988 for log2 fold changes, and advanced cell-type-resolved scRNA-seq analysis.
