# Research Object Crate for TF-Prioritizer

Original URL: https://workflowhub.eu/workflows/433/ro_crate?version=1

# 1. About TF-Prioritizer This pipeline gives you a full analysis of nfcore chromatine accessibility peak data (ChIP-Seq, ATAC-Seq or DNAse-Seq) and nfcore RNA-seq count data. It performs DESeq2, TEPIC and DYNAMITE including all preprocessing and postprocessing steps necessary to transform the data. It also gives you plots for deep analysis of the data. The general workflow is sketched in the images below: ## Graphical abstract: ![Graphical abstrat](https://raw.githubusercontent.com/biomedbigdata/TF-Prioritizer/master/media/graphicalAbstract.png) ## Technical workflow: ![Technical workflow](https://github.com/biomedbigdata/TF-Prioritizer/raw/master/media/technicalWorkflow.png) # 2. License and Citing TF-Prioritizer is distributed under the [GNU General Public License](https://www.gnu.org/licenses/gpl-3.0.en.html). The Graphical Abstract and the Technical Workflow was created using [biorender.com](https://biorender.com/). # 3. Usage The software can be executed using docker. For the following command, only [python3](https://www.python.org/downloads/), [curl](https://curl.se/download.html) and [docker](https://docs.docker.com/get-docker/) are required. Explanations about the configs can be found in the [config readme](https://github.com/biomedbigdata/TF-Prioritizer/blob/master/configTemplates/README.md). ```bash curl -s https://raw.githubusercontent.com/biomedbigdata/TF-Prioritizer/master/docker.py | python3 - -c [config_file] -o [output_dir] -t [threads] ``` Note, that for this approach an internet connection is required. The docker image will be downloaded from [DockerHub](https://hub.docker.com/r/nicotru/tf-prioritizer) on the first execution as well as with every update we release. Furthermore, the wrapper script will be fetched from GitHub with every execution. If curl is not available (for example if you are using windows), or you want to be able to execute the software without an internet connection, you can download the wrapper script from [here](https://raw.githubusercontent.com/biomedbigdata/TF-Prioritizer/pipeJar/docker.py). You can then execute the script using ```bash python3 [script_path] -c [config_file] -o [output_dir] -t [threads] ``` ## If you want to use the pipeline without docker We do not recommend using the pipeline without docker, because the dependencies are very complex, and it is very hard to install them correctly. However, if you want to use the pipeline without docker, you can do so by installing the dependencies manually. The dependencies and their correct installation process can be derived from the [Dockerfile](https://github.com/biomedbigdata/TF-Prioritizer/blob/master/Dockerfile) and the environment scripts which can be found in the [environment directory](https://github.com/biomedbigdata/TF-Prioritizer/tree/master/environment).

Author
License
  LGPL-3.0

## Contents

Main Workflow: TF-Prioritizer
Size: 2005 bytes
Main Workflow Diagram: media/technicalWorkflow.png
Size: 1828513 bytes