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.
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.