Giter VIP home page Giter VIP logo

phupe / geniac-demo Goto Github PK

View Code? Open in Web Editor NEW

This project forked from bioinfo-pf-curie/geniac-demo

0.0 0.0 0.0 13.29 MB

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 pipeline).

License: Other

HTML 0.10% Python 0.67% Shell 0.39% Nextflow 1.72% CMake 0.25% C++ 1.79% Dockerfile 0.01% Makefile 1.48% C 89.32% Roff 1.22% M4 1.07% Perl 1.86% Scilab 0.13%

geniac-demo's Introduction

Geniac-demo pipeline

Nextflow Install with Singularity Container available Docker Container available

Introduction

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:

Quick start

Prerequisites

  • 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

Install the geniac conda environment

# 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

Check the code, install and run the pipeline with the multiconda profile

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

Check the code, install and run the pipeline with the singularity profile

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

Advanced users

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

Pipeline documentation

The geniac-demo pipeline is a very simple bioinformatics pipeline inspired from the analysis of high-throuphput-sequencing data. More information are available here:

  1. Running the pipeline
  2. Nextflow profiles
  3. Outputs

Geniac documentation and useful resources

  • 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.

Acknowledgements

Citation

Allain F, Roméjon J, La Rosa P et al. Geniac: Automatic Configuration GENerator and Installer for nextflow pipelines. Open Research Europe 2021, 1:76.

geniac-demo's People

Contributors

phupe avatar fabriceallain avatar plarosa avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.