IsoProt

This project provides a reproducible pipeline to analyse isobarically labelled mass spectrometry based quantitative proteomics data.

The different workflows are created using the jupyter notebook environment. They look like normal documents with interactive elements (like buttons, etc.) in them and are based on our standard workflow template. Thereby, they also provide completely reproducible records of the bioinformatic pipeline used to analyse the data.

The pipelines are made available as Docker containers. These are light-weight virtual machines that contain the complete software necessary to run the pipeline. Thereby, you do not have to worry about installing any additional required software.

This project is still under development. All resources are only intended to be used for testing. We are simply not done yet.

Citation

IsoProt: A fully reproducible one-stop-shop for the analysis of iTRAQ/TMT data. Johannes Griss, Goran Vinterhalter, Veit Schwaemmle. bioRxiv 446070; doi: https://doi.org/10.1101/446070

Installation / Usage

Requirements

• You need to have the docker engine installed. For more details, see https://docs.docker.com/engine/installation/ In the case of not having a compatible operating system (e.g. Windows 7), you need to install the Docker Toolbox: https://docs.docker.com/toolbox/toolbox_install_windows/#what-you-get-and-how-it-works

docker-launcher

The easiest way to run ProtProtocol protocols is through our docker-launcher application. It provides a simple graphical user interface that takes care of downloading the protocol and launching the docker image taking care of all required parameters. As it is a Java application it supports Windows, Mac OS X, and Linux.

Manual launch

To launch docker images manually, you need to open your operating system's command prompt (ie. PowerShell on Windows). The docker commands are the same on all operating systems.

• Download the latest stable version of the protocol (you might need to be administrator):

docker pull protprotocols/isoprot:release-0.2

• Download the latest development version of the protocol (you might need to be administrator):

docker pull protprotocols/isoprot:latest

• Run the image (add :"release-x" or :"latest" when you have downloaded both versions)

docker run -it -p 8888:8888 protprotocols/isoprot

In order to directly access your computer's folders through the docker image (recommended option) map local directories to the containers /data (for input data) and OUT (for output data) folders:

docker run -it -p 8888:8888 -v /path/to/my/mgf/files:/data/ -v /path/to/my/result/folder:/home/biodocker/OUT protprotocols/isoprot

Note: When running Docker Toolbox (ie. only available version on Windows 7), local paths must be below C:\Users. Additionally, paths need to specified in the following format:

# to map C:\Users\Johannes\Downloads
docker run -it -p 8888:8888 -v /c/users/johannes/downloads:/data/ -v /c/users/johannes/results:/home/biodocker/OUT protprotocols/isoprot

• Open your favorite web browser and access the image via 0.0.0.0:8888

• You can start with the example use case by clicking on the file Isobaric_Workflow.ipynb

Releases

Release 0.2: Feature complete version of the protocol supporting complex experimental designs. This version was used during the analysis of the benchmark studies in the IsoProt manuscript.

Release 0.1: First fully functional version for analyzing iTRAQ/TMT data.

Feedback

In case you have any questions about using the pipeline or find an issue, please simply submit an issue through this GitHub page.

Development

Any code fixes / enhancements are highly welcome as pull requests.

Repository directory structure

Jupyter notebooks (.ipnyb) files are kept in the main directory.

• DockerSetup: files related to building the docker image
• RELEASE: (deprecated) Directory to bundle release files. This functionality has been taken over by docker-launcher
• Scripts: Collection of python modules that provide functionality shared between protocols (display of GUI for search parameters, etc.)
• Test: Example dataset to test the pipeline
• misc: Images etc. to make things look nice

Acknowledgements

This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 788042.