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A Quantitative MS proteomics analysis pipeline

Build Status Nextflow DOI

install with bioconda Docker Singularity Container available


This workflow identifies peptides in mzML input data using MSGF+, and Percolator, quantifies isobarically labeled samples with OpenMS, and precursor peptides with Dinosaur, and processes that output to formatted peptide and protein/gene tables using Msstitch. Optional PTM data is analyzed by Luciphor2, and differential expression analyses can be performed using DEqMS.

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 / singularity containers making installation trivial and results highly reproducible.

How to run

nextflow run lehtiolab/ddamsproteomics --mzmls '/path/to/*.mzML' --tdb /path/to/proteins.fa --mods 'oxidation;carbamidomethylation' -profile standard,docker

Or for two sample sets of isobaric data you can:

nextflow run lehtiolab/ddamsproteomics --mzmls '/path/to/*.mzML' --tdb /path/to/proteins.fa --mods 'oxidation;carbamidomethylation --isobaric 'setA:tmt10plex:126 setB:tmt10plex:127N'

For more elaborate examples covering fractionation, PTMs, and more, the lehtiolab/ddamsproteomics pipeline comes with documentation about the pipeline, found in the docs/ directory:

There is more extensive documentation on the options inside the file.

The pipeline takes multiple mzML files as input and performs identification and quantification to output results and a QC report (an example can be found here)


lehtiolab/ddamsproteomics was originally written by Jorrit Boekel and tries to follow the nf-core best practices and templates.