bigbio/quantmsandes is an exploratory pipeline for data-dependent acquisition (DDA) proteomics, built on the andes search engine and following nf-core guidelines. Use it to try new algorithms and frontier approaches in proteomics, such as glycoproteomics, proteoform identification and quantification, and agentic analysis, before they are mature enough for production.
Important
The production pipeline is quantms. quantmsandes is for exploring new methods: its defaults, parameters and outputs may change between releases. For routine analyses, use quantms.
quantmsandes is one of three pipelines in the quantms ecosystem. Each is independent; pick the one that fits the use case.
| Pipeline | Use it for | Engines |
|---|---|---|
| quantms | Production analysis of DDA label-free, TMT/iTRAQ and DIA data | OpenMS-based workflow with several search engines |
| quantmsdiann | DIA analysis with DIA-NN | DIA-NN |
| quantmsandes | Exploratory DDA analysis: new algorithms, glycoproteomics, proteoforms, agentic analysis | andes |
All three read SDRF sample metadata and report quality control with pmultiqc.
- New algorithms in identification and quantification. andes is a data-driven search engine with its own scoring models, co-isolated (chimeric) peptide search, PTM refinement, and label-free quantification with match-between-runs.
- Glycoproteomics. Intact N-glycopeptide search against species-specific glycan databases.
- Proteoforms. Searching sequence variants, isoforms, mature chains and annotated modification sites from UniProt, PEFF or annotation files, with knockoff-based error estimates for variant identifications, and a per-protein-family proteoform table with quantities.
- Agentic analysis. andes exposes many advanced parameters. quantmsandes passes them through, so an AI agent such as Claude can choose and tune them for a given dataset and question, and compare the outcomes.
Warning
quantmsandes is in early development. The repository currently holds the pipeline template and the design; the workflow is not runnable yet.
Planned workflow for DDA label-free and TMT/iTRAQ data:
- Input validation: SDRF parsing and validation with sdrf-pipelines.
- Search: andes builds its fragment index once, then searches each run (Thermo
.raw, Bruker.dand mzML are read directly). - PSM rescoring: one Percolator run over all runs, on andes's features plus predicted retention-time and fragment features that andes computes during the search.
- Quantification: andes label-free quantification with match-between-runs, or reporter ion quantification for TMT/iTRAQ.
- Protein inference: andes protein inference.
- Protein quantification: mokume.
- Quality control: pmultiqc.
The containers come from quantms-containers.
Note
If you are new to Nextflow and nf-core, please refer to this page on how to set up Nextflow.
Once the workflow is available, a run will look like:
nextflow run bigbio/quantmsandes \
-profile <docker/singularity/.../institute> \
--input experiment.sdrf.tsv \
--database proteins.fasta \
--outdir <OUTDIR>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.
bigbio/quantmsandes was originally written by Yasset Perez-Riverol.
We thank the following people for their extensive assistance in the development of this pipeline:
If you would like to contribute to this pipeline, please see the contributing guidelines.
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.
This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.
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.