Proteomics Tandem Mass Tags quantification (TMT) analysis pipeline using OpenMS and MSstats, with feature quantification, feature summarization, quality control and group-based statistical analysis..

Introduction

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

Quick Start

1. Install nextflow

2. Install either Docker or Singularity for full pipeline reproducibility (please only use Conda as a last resort; see docs)

3. Download the pipeline and test it on a minimal dataset with a single command:

   nextflow run nf-core/proteomicstmt -profile test,<docker/singularity/conda/institute>

   Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

4. Start running your own analysis!

   nextflow run nf-core/proteomicstmt \
     -profile <docker/singularity/conda/institute> \
     --input '*.mzml' \
     --database 'myProteinDB.fasta' \
     --expdesign 'myDesign.tsv'

Citation

If you use nf-core/proteomicsTMT for your analysis, please cite it using the following doi: 10.5281/zenodo.XXXXXX

You can cite the nf-core publication as follows:

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. ReadCube: Full Access Link

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.