Installation & Usage

This repository contains the entire codebase necessary to pilot STAPLE, an automated end-to-end pipeline that processes Spatial Transcriptomics datasets.

Installation & Usage

Requirements

For the current version of the pipeline, you only need two frameworks are required to run it on any system that has acces to the pipeline.

Nextflow: This can be installed by following the instructions at Nextflow’s documentation. The current working version is guaranteed to work with nextflow version 20.10, however it will soon be updated to be compatible to the most recent nextflow version.
Conda: Any form of environment management will most likely do. The recomended software is (Ana)Conda, which can be installed folowing these steps. This is used to automatically create the programming environment with all used languages and software packages without creating version conflicts.

Dependencies

Here is a list of all dependencies that were installed to run the full pipeline in case you’d like to build them from scratch. A complete list including version numbers can be found in the form of the staple.yml file, as can be described below.

python
numpy
pip
imagecodecs
scikit-image
scikit-learn
pandas
beautifusoup4
umap-learn
aicspylibczi
tensorflow
stardist
csbdeep

Installation

Clone/fork the current master branch of the pipeline to your system.

git clone https://github.com/WoutDavid/ST-nextflow-pipeline; cd ST-nextflow-pipeline

Create a conda environment containing all the dependencies of the current pipeline, and activate it.
```
conda env create --file=staple.yml --prefix ./staple_env/
conda activate ./staple_env/
```

That is everything that needs to be installed. After this, general usage of the pipeline is performed as such:

Usage

Create a personal config file containing all the parameters for your experiment.
```
nextflow config -profile iss >> iss_exp.config
```
Note that this config file is where you change everything that you want to change, such as data directory, output directory, image format etc. For more details about the configuration of a pipeline run, see Configuration.

After making the needed changes to the config file, you can run pipeline by specifying an entry point with “-entry”, which takes as argument the name of one of the workflows included in the main.nf file.

nextflow -C iss_exp.config run main.nf	                \
			        -entry iss	        \
				--with_conda staple.yml	\

The –with_conda flag is only needed if you decide not the activate the conda environment prior to running the pipeline. This can be useful when submitting jobs to a high compute cluster.