DOTools_py
Convenient and user-friendly package to streamline common workflows in single-cell RNA sequencing data analysis using the scverse ecosystem. It provides high-level wrappers and visualization functions to help efficiently preprocess, analyze, and interpret single-cell data.
Getting started
Please refer to the documentation, in particular, the API documentation.
Installation
You need to have Python 3.10 or newer installed on your system. We recommend creating a dedicated conda environment.
conda create -n scrna_py11 python=3.11 -y
conda activate scrna_py11
pip install uv
There are several alternative options to install DOTools_py:
- Install the latest release of
DOTools_pyfrom PyPI:
uv pip install dotools-py
- Install the latest development version:
uv pip install git+https://github.com/davidrm-bio/DOTools_py.git@main
Finally, to use this environment in jupyter notebook, add jupyter kernel for this environment:
python -m ipykernel install --user --name=scrna_py11 --display-name=scrna_py11
Requirements
This package has been tested on macOS, Linux and Windows System. For a standard dataset (e.g., 6 samples with 10k cells each) we suggest 16GB of RAM and at least 5 CPUs.
Some methods are run through R and require additional dependencies
including: Seurat, MAST, scDblFinder, zellkonverter, data.table and optparse.
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
install.packages("optparse", Ncpus=8)
install.packages('remotes', Ncpus=8)
install.packages('data.table', Ncpus = 8)
remotes::install_github("satijalab/seurat", "seurat5", quiet = TRUE) # Seurat
BiocManager::install("MAST")
BiocManager::install("scDblFinder")
BiocManager::install("zellkonverter")
BiocManager::install('glmGamPoi')
For old CPU architectures there can be problems with polars making the kernel die when importing the package. In this case run
pip install --no-cache polars-lts-cpu
R version
We also have an R implementation of the DOTools. This can be installed from Bioconductor:
if (!requireNamespace("BiocManager", quietly=TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("DOtools")
devtools::install_github("MarianoRuzJurado/DOtools")
The developmental version can be downloaded using devtools:
devtools::install_github("MarianoRuzJurado/DOtools", ref="devel")
Release notes
See the changelog.
Contact
Raising up an issue in this GitHub repository might be the fastest way of submitting suggestions and bugs. Alternatively you can write to my email: rodriguezmorales@med.uni-frankfurt.de.
Citation
Ruz Jurado, Mariano, David Rodriguez Morales, Lukas Zanders, Elijah Genetzakis, Stefanie Dimmeler, and David John. 2026. “DoTools: A Cross Platform Framework to Streamline Common Single Cell Workflows.” Bioinformatics Advances: vbag098. https://doi.org/10.1093/bioadv/vbag098
Release files for DOTools-py 0.0.4
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dotools_py-0.0.4.tar.gz | 10.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dotools_py-0.0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.5 MB
Release files / dotools_py-0.0.4.tar.gz
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| Size | 10.5 MB |
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