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DoTools: a cross platform framework to streamline common single cell workflows
Mariano Ruz Jurado1,2,3, David Rodriguez Morales1,2,3, Lukas Zanders1,2,4
1Institute of Cardiovascular Regeneration, Goethe University Frankfurt, Theodor-Stern-Kai 7, Frankfurt am Main, Hessia, 60590, Germany.
Bioinformatics Advances
|May 11, 2026
Summary
DoTools simplifies complex single-cell RNA sequencing (scRNA-seq) analysis by unifying R and Python tools. This framework integrates popular third-party applications, making advanced scRNA-seq data analysis more accessible.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Single-cell RNA sequencing (scRNA-seq) is crucial for understanding biological conditions.
- The proliferation of analysis tools across different programming languages complicates scRNA-seq data integration and workflow development.
- Significant coding expertise and learning time are often required to combine various scRNA-seq analysis tools.
Purpose of the Study:
- To develop a unified framework, DoTools, that simplifies the integration of diverse third-party scRNA-seq analysis tools.
- To provide a solution that bridges R/Bioconductor and Python/PyPI environments for seamless scRNA-seq data analysis.
- To enhance accessibility and efficiency in scRNA-seq data preprocessing, quality control, cell type annotation, and downstream analysis.
Main Methods:
- Developed DoTools, a cross-language framework compatible with R/Bioconductor and Python/PyPI.
- Implemented wrappers for integrating popular tools like scVI, CellTypist, and CellBender.
- Incorporated visualization utilities and best practices for scRNA-seq analysis pipelines (e.g., Seurat, SingleCellExperiment, Scanpy).
Main Results:
- DoTools successfully integrates multiple third-party tools into unified scRNA-seq analysis workflows.
- The framework streamlines essential analysis steps, including data preprocessing, quality control, and cell type annotation.
- DoTools supports both novice and experienced users by providing an accessible and modular approach to complex scRNA-seq analysis.
Conclusions:
- DoTools significantly reduces the complexity and technical barriers associated with integrating diverse scRNA-seq analysis tools.
- The framework promotes standardized and efficient scRNA-seq data analysis across different computational environments.
- DoTools enhances the accessibility of advanced scRNA-seq analysis techniques for a broader scientific community.
