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 visualisation functions to help efficiently preprocess, analyze, and interpret single-cell data.
Please refer to the documentation, in particular, the API documentation.
You need to have Python 3.10 or newer installed on your system. We recommend creating a dedicated conda environment.
conda create -n do_py11 python=3.11
conda activate do_py11There are several alternative options to install DOTools_py:
- Install the latest release of
DOTools_pyfrom PyPI:
pip install dotools-py- Install the latest development version:
pip install git+https://github.com/davidrm-bio/DOTools_py.git@mainFinally, to use this environment in jupyter notebook, add jupyter kernel for this environment:
python -m ipykernel install --user --name=do_py11 --display-name=do_py11Some 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-cpuWe also have an R implementation of the DOTools. This can be
installed with devtools:
devtools::install_github("MarianoRuzJurado/DOtools")See the changelog.
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: [email protected].
t.b.a
