DoTools: a cross platform framework to streamline common single cell workflows.

Motivation: Throughout the years, single-cell RNA sequencing (scRNA-seq) has become a standard approach for characterising transcriptomic changes associated with diseases and other biological conditions. However, the rapid expansion of tools and algorithms developed in various programming languages has made single-cell data analysis increasingly complex. In particular, integrating multiple tools into a single workflow often demands substantial learning time and coding expertise. Results: To address these challenges, we developed DoTools, a unified framework for R/Bioconductor and Python/PyPI that simplifies the integration of third-party tools such as scVI, CellTypist, and CellBender into standard pipelines like Seurat, SingleCellExperiment and Scanpy. DoTools provides advanced cross-language wrappers and visualisation utilities to streamline data preprocessing, quality control, cell type annotation, and downstream analysis, while implementing best practices in scRNA-seq analysis regardless of the computational language. Its modular design and compatibility with widely used bioinformatics environments makes it accessible and valuable to both novice and experienced data scientists. Availability and implementation: DoTools is freely available for R and Python at Bioconductor and PyPI (https://bioconductor.org/packages/release/bioc/html/DOtools.html and https://pypi.org/project/DoTools-py/), the developmental versions of DoTools are maintained on GitHub (https://github.com/MarianoRuzJurado/DoTools and https://github.com/davidrm-bio/DoTools_py).