CoTRA: an integrated R/Shiny framework for transparent bulk and single-cell RNA-seq analysis
- 1University of Eastern Finland
Abstract
Bulk RNA-seq and single-cell RNA-seq (scRNA-seq) are widely used to investigate gene-expression changes, but downstream analysis often requires multiple statistical,visualization, and reporting tools, creating fragmented workflows that are difficult to configure and reproduce. We developed CoTRA (Comprehensive Toolbox for RNA-seq Analysis), an open-source R/Shiny package providing independent bulk and scRNA-seq workflows within a common graphical environment. CoTRA supports quality control, differential expression, annotation, enrichment, dimensionality reduction, clustering, marker detection, cell-type annotation, differential abundance, trajectory inference, pathway activity, cell-cell communication, and reporting while exposing key analytical parameters. Compared with 14 other platforms across 49 predefined criteria, CoTRA fully supported 46 and partially supported three. Under matched inputs and parameters, CoTRA reproduced direct DESeq2, edgeR, and Seurat implementations, including identical significant bulk gene sets and scRNA-seq clustering (ARI = 1.000; NMI = 1.000). Retinal case studies recapitulated degeneration-associated transcriptional changes and demonstrated cell-type-resolved analysis. Synthetic scRNA-seq benchmarking scaled to 50,000 cells with 5.10 GB peak memory. CoTRA v1.0.0 requires R [≥] 4.4.0, has been tested on Linux, Windows, and macOS, is GPL-3 licensed, and is available at https://github.com/UmairSeemab/CoTRA, and support is provided through GitHub Issues.
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BibTeX
@misc{seemab2026cotra,
title = {{CoTRA: an integrated R/Shiny framework for transparent bulk and single-cell RNA-seq analysis}},
author = {U. Seemab and K. Vainionpaa and Z. Tanoli and H. O. Leinonen},
howpublished = {bioRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.25.747017},
url = {https://www.biorxiv.org/content/10.64898/2026.08.25.747017v2},
note = {CC BY},
}
RIS
TY - UNPB
TI - CoTRA: an integrated R/Shiny framework for transparent bulk and single-cell RNA-seq analysis
AU - U. Seemab
AU - K. Vainionpaa
AU - Z. Tanoli
AU - H. O. Leinonen
PY - 2026
DA - 2026/08/25
PB - bioRxiv
DO - 10.64898/2026.08.25.747017
UR - https://www.biorxiv.org/content/10.64898/2026.08.25.747017v2
AB - Bulk RNA-seq and single-cell RNA-seq (scRNA-seq) are widely used to investigate gene-expression changes, but downstream analysis often requires multiple statistical,visualization, and reporting tools, creating fragmented workflows that are difficult to configure and reproduce. We developed CoTRA (Comprehensive Toolbox for RNA-seq Analysis), an open-source R/Shiny package providing independent bulk and scRNA-seq workflows within a common graphical environment. CoTRA supports quality control, differential expression, annotation, enrichment, dimensionality reduction, clustering, marker detection, cell-type annotation, differential abundance, trajectory inference, pathway activity, cell-cell communication, and reporting while exposing key analytical parameters. Compared with 14 other platforms across 49 predefined criteria, CoTRA fully supported 46 and partially supported three. Under matched inputs and parameters, CoTRA reproduced direct DESeq2, edgeR, and Seurat implementations, including identical significant bulk gene sets and scRNA-seq clustering (ARI = 1.000; NMI = 1.000). Retinal case studies recapitulated degeneration-associated transcriptional changes and demonstrated cell-type-resolved analysis. Synthetic scRNA-seq benchmarking scaled to 50,000 cells with 5.10 GB peak memory. CoTRA v1.0.0 requires R [≥] 4.4.0, has been tested on Linux, Windows, and macOS, is GPL-3 licensed, and is available at https://github.com/UmairSeemab/CoTRA, and support is provided through GitHub Issues.
ER -