Introduction

nf-core/msproteomics is a bioinformatics pipeline for mass spectrometry-based proteomics preprocessing. It accepts raw instrument data with a CSV samplesheet and produces quantified protein/peptide/ion matrices ready for downstream statistical analysis. The pipeline supports multiple acquisition strategies through dedicated workflow types:

• DIA (Data-Independent Acquisition) -- analyzed with DIA-NN, with optional MSstats and MaxLFQ quantification
• DDA LFQ (Data-Dependent Acquisition, Label-Free Quantification) -- analyzed with the FragPipe computational platform (MSFragger, MSBooster, Percolator, IonQuant)
• TMT Label Check -- TMT labeling efficiency QC using FragPipe search followed by label incorporation analysis
• Generic FragPipe -- fully configurable FragPipe workflows driven by .workflow files

Instrument-specific settings are applied via optional config files (-c conf/instruments/*.config).

Analysis Modes

The --mode parameter selects the analysis engine. FragPipe sub-modes are controlled with --tmt_mode for TMT workflows.

Mode	Sub-mode	Description	Engine
diann	--	DIA quantitative proteomics (standard, phospho)	DIA-NN
fragpipe	(none)	Generic FragPipe workflows, configured by workflow files	FragPipe
fragpipe	--tmt_mode labelcheck	TMT labeling efficiency QC	FragPipe
fragpipe	--tmt_mode quant	TMT isobaric quantification	FragPipe

DIA method variants (e.g., phospho) and instrument-specific settings are applied via -c config files. See docs/usage.md for full details.

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a CSV samplesheet describing your samples:

sample,spectra
Sample1,/path/to/sample1.raw
Sample2,/path/to/sample2.raw
Sample3,/path/to/sample3.raw

Optional columns: condition (experimental group), label (TMT channel, e.g. TMT126), fraction (fraction number). If present, these are parsed automatically.

Then run the pipeline:

# DIA analysis
nextflow run nf-core/msproteomics \
  --mode diann \
  --input samplesheet.csv \
  --database /path/to/database.fasta \
  --outdir results \
  -profile docker

# FragPipe DDA LFQ analysis
nextflow run nf-core/msproteomics \
  --mode fragpipe \
  --fragpipe_container your-registry/fragpipe:24.0 \
  --fragpipe_workflow LFQ-MBR.workflow \
  --input samplesheet.csv \
  --database /path/to/uniprot_human.fasta \
  --outdir results \
  -profile docker

# TMT label check (TMT18 example)
nextflow run nf-core/msproteomics \
  --mode fragpipe \
  --fragpipe_container your-registry/fragpipe:24.0 \
  --tmt_mode labelcheck \
  --tmt_type TMT18 \
  --input samplesheet.csv \
  --database /path/to/uniprot_human.fasta \
  --outdir results \
  -profile docker

# TMT quantification (TMT18 example)
nextflow run nf-core/msproteomics \
  --mode fragpipe \
  --fragpipe_container your-registry/fragpipe:24.0 \
  --tmt_mode quant \
  --tmt_type TMT18 \
  --fragpipe_workflow /path/to/TMT-quant.workflow \
  --input samplesheet.csv \
  --database /path/to/uniprot_human.fasta \
  --outdir results \
  -profile docker

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline Output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

FragPipe License

FragPipe-based workflows (DDA LFQ, TMT Label Check, generic FragPipe) require a FragPipe installation with a valid license. FragPipe is free for academic use; commercial users must obtain a license from the University of Michigan. You must build or provide a Docker/Singularity container that includes FragPipe, MSFragger, IonQuant, and Philosopher under your own license terms.

Documentation

• Usage guide -- full parameter reference and workflow examples
• Output documentation -- description of pipeline output files and reports
• Module documentation -- per-module reference for all local modules
• Docker build instructions -- building the FragPipe container image

Credits

The pipeline was originally created by Dongze He and is maintained and developed by Dongze He and Fengchao Yu.

The DIA-NN workflow is inherited from quantms, developed by the bigbio community.

The advisory team includes Dr. Stefka Tyanova (Altos Labs), Dr. Daniel Itzhak (Altos Labs), Dr. Felix Krueger (Altos Labs), and Dr. Alexey I. Nesvizhskii (University of Michigan Medical School).

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on the Slack #msproteomics channel (you can join with this invite).

Citations

If you use nf-core/msproteomics for your analysis, please cite it using the nf-core publication and the underlying tools.

Underlying Tools

Please cite the tools used by this pipeline depending on the workflow you run:

FragPipe (DDA LFQ, TMT workflows): See the full list of key references at FragPipe GitHub, including MSFragger, Philosopher, IonQuant, and TMT-Integrator.

DIA-NN (DIA workflows): See the key publications at DIA-NN GitHub.

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

nf-core

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.