- Introduction
- Quick start
- Geniac documentation and useful resources
- Pipeline documentation
- Acknowledgements
- Release notes
- Citation
This is a demo pipeline with the best practises for the development of bioinformatics analysis pipelines with Nextflow and geniac (Automatic Configuration GENerator and Installer for nextflow pipelines). It runs within ~20 seconds a very simple bioinformatics pipeline inspired from the analysis of high-throuphput-sequencing data. The best practises proposed by geniac can be applied to any analysis workflow in data science.
This pipeline illustrates how geniac can automatically build:
- Nextflow profiles configuration files
- Singularity / Docker recipes and containers
- Run the pipeline with the different Nextflow profiles
- git (>= 2.0) [required]
- cmake (>= 3.0) [required]
- Nextflow (>= 21.10.6) [required]
- Singularity (>= 3.8.5) [optional]
- Docker (>= 18.0) [optional]
Install conda:
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
# Create the geniac conda environment
export GENIAC_CONDA="https://raw.githubusercontent.com/bioinfo-pf-curie/geniac/release/environment.yml"
wget ${GENIAC_CONDA}
conda create env -f environment.yml
conda activate geniac
export WORK_DIR="${HOME}/tmp/myPipeline"
export INSTALL_DIR="${WORK_DIR}/install"
export GIT_URL="https://github.com/bioinfo-pf-curie/geniac-demo.git"
# Initialization of a working directory
# with the src and build folders
geniac init -w ${WORK_DIR} ${GIT_URL}
cd ${WORK_DIR}
# Check the code
geniac lint
# Install the pipeline
geniac install . ${INSTALL_DIR}
# Test the pipeline with the multiconda profile
geniac test multiconda
Note that you need sudo
privilege to build the singularity images.
export WORK_DIR="${HOME}/tmp/myPipeline"
export INSTALL_DIR="${WORK_DIR}/install"
export GIT_URL="https://github.com/bioinfo-pf-curie/geniac-demo.git"
# Initialization of a working directory
# with the src and build folders
geniac init -w ${WORK_DIR} ${GIT_URL}
cd ${WORK_DIR}
# Install the pipeline with the singularity images
geniac install . ${INSTALL_DIR} -m singularity
sudo chown -R $(id -gn):$(id -gn) build
# Test the pipeline with the singularity profile
geniac test singularity
# Test the pipeline with the singularity and cluster profiles
geniac test singularity --check-cluster
Note that the geniac command line interface provides a wrapper to git
, cmake
and make
commands. Advanced users familiar with these commands can run the following (see geniac documentation for more details):
export WORK_DIR="${HOME}/tmp/myPipeline"
export SRC_DIR="${WORK_DIR}/src"
export INSTALL_DIR="${WORK_DIR}/install"
export BUILD_DIR="${WORK_DIR}/build"
export GIT_URL="https://github.com/bioinfo-pf-curie/geniac-demo.git"
mkdir -p ${INSTALL_DIR} ${BUILD_DIR}
# clone the repository
# the option --recursive is needed if you use geniac as a submodule
git clone --recursive ${GIT_URL} ${SRC_DIR}
cd ${BUILD_DIR}
# configure the pipeline
cmake ${SRC_DIR}/geniac -DCMAKE_INSTALL_PREFIX=${INSTALL_DIR}
# build the files needed by the pipeline
make
# install the pipeline
make install
# run the pipeline
make test_multiconda
The geniac-demo pipeline is a very simple bioinformatics pipeline inspired from the analysis of high-throuphput-sequencing data. More information are available here:
- The geniac documentation provides a set of best practises to implement Nextflow pipelines.
- The geniac source code provides the set of utilities.
- The geniac demo provides a toy pipeline to test and practise Geniac.
- The geniac demo DSL2 provides a toy pipeline to test and practise Geniac.
- The geniac template provides a pipeline template to start a new pipeline.
- Institut Curie
- Centre national de la recherche scientifique
- This project has received funding from the European Union’s Horizon 2020 research and innovation programme and the Canadian Institutes of Health Research under the grant agreement No 825835 in the framework on the European-Canadian Cancer Network.