BESCA (BEDA's Single Cell Analysis library)

The BESCA (BEDA’s single cell sequencing analysis) package contains many useful python functions to use for your single-cell analysis.

The package has been grouped into 3 categories:

• preprocessing functions: this submodule contains all functions relevant to data preprocessing
• plotting functions: additional plot types not available in the standard scanpy package
• tools: contains additional tools to e.g. perform differential gene analysis or load/export data

For more information please view the package documentation: https://bedapub.github.io/besca/

Please find our preprint posted on bioRxiv here: https://biorxiv.org/cgi/content/short/2020.08.11.245795v2

If you are interested in contributing you can check the repository wiki for helpful information on contributing: https://github.com/bedapub/besca/wiki

Installation

If you are familiar with python packages simply install it using pip:

pip install git+https://github.com/bedapub/besca.git

Besca comes with a binary called reformat written in C and was compiled in linux-64. Therefore, besca runs exclusively on linux-64.

Set the executable flag to the binary file reformat

In some cases the binary file needs to be made executeable. To do so, run the following one-liner.

pip show besca | grep Location | cut -f 2 -d ":" | awk -v OFS="" '{print "chmod u+x" $0 "/besca/export/reformat"}' | bash

If you want to avoid piping to bash, or want to it step by step, here is how to. Show the location of the path and navigate to the besca package.

pip show besca
cd Location/besca

Navigate in the directory containing the binary and make it executeable.

cd export
chmod u+x reformat

Python beginner guide

If you are not very familiar with python packages here is a detailled description.

If you don't have a conda python installation download and install miniconda. While installing I recommend to accept everything asked by the miniconda installation.

As a next step we create a separate environment for besca which is also called besca.

conda create --name besca python=3.7.1

We can activate this environment.

conda activate besca

Within this enviroment we can install besca using pip.

pip install git+https://github.com/bedapub/besca.git

Now following the instrution above to set the executable flag to the binary file shipped with besca.

You should now have successfully installed besca.

In case you met any problems, please report an issue.

Running besca on a HPC with a SLURM worklod manager

If you have access to an HCP which uses SLURM as a workload manger you can run the jupyter notebooks coming with besca located in workbooks/ with dedicated resources.
To do so, start an interactive session on your HPC.

interactive -c 8 -m 16G -t 180 # This allocates 8 CPUs, 16 GB of memory for 3 hours

If you have installed besca in a conda environment like explained above activate the environment.

conda activate besca

Start a jupyter notebook.

jupyter-notebook --ip=* --no-browser

You can now run the jupyter notebooks coming with besca.

Datasets and Analysis notebooks

Besca run-examples and datasets annotations notebook can be found in:

https://github.com/bedapub/besca_publication_results

All processed datasets were uploaded to Zenodo, within the Besca community:

https://zenodo.org/communities/besca/