WOMBAT-Pipelines

Version 1 (earliest)

• Version 2 (latest)
  
• Version 1 (earliest)
  

Introduction

wombat-p pipelines is a bioinformatics analysis pipeline that bundles different workflow for the analysis of label-free proteomics data with the purpose of comparison and benchmarking. It allows using files from the proteomics metadata standard SDRF.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. We used one of the nf-core templates.

Pipeline summary

This work contains four major different workflows for the analysis or label-free proteomics data, originating from LC-MS experiments.

1. MaxQuant + NormalyzerDE
2. SearchGui + Proline + PolySTest
3. Compomics tools + FlashLFQ + MSqRob
4. Tools from the Trans-Proteomic Pipeline + ROTS

Initialization and parameterization of the workflows is based on tools from the SDRF pipelines, the ThermoRawFileParser with our own contributions and additional programs from the wombat-p organizaion [https://github.com/wombat-p/Utilities] as well as our fork. This includes setting a generalized set of data analysis parameters and the calculation of a multiple benchmarks.

Credits

nf-core/wombat was originally written by the members of the ELIXIR Implementation study Comparison, benchmarking and dissemination of proteomics data analysis pipelines under the lead of Veit Schwämmle and major participation of David Bouyssié and Fredrik Levander.

Citations

Manuscript in preparation

As the workflows are using an nf-core template, we refer to the publication:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.