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.
iii. Download the pipeline and test it on a minimal dataset with a single command
nextflow run nf-core/proteomicslfq -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
singularityand set the appropriate execution settings for your local compute environment.
iv. Start running your own analysis!
nextflow run nf-core/proteomicslfq -profile <docker/singularity/conda/institute> --spectra '*.mzml' --database '*.fasta' --expdesign '*.tsv'
See usage docs for all of the available options when running the pipeline.
The nf-core/proteomicslfq pipeline comes with documentation about the pipeline, found in the
- Pipeline configuration
- Running the pipeline
- Output and how to interpret the results
nf-core/proteomicslfq was originally written by Julianus Pfeuffer, Lukas Heumos, Leon Bichmann, Timo Sachsenberg, Yasset Perez-Riverol
If you would like to contribute to this pipeline, please see the contributing guidelines.
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.
An extensive list of references for the tools used by the pipeline can be found in the