A proteomics pipeline for running labelchecks.
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.
- install Nextflow
- install Docker, Singularity, or Conda
- run pipeline:
nextflow run lehtiolab/nf-labelcheck --input '/path/to/inputdef.txt' --tdb /path/to/proteins.fa --isobaric tmt10plex
Where inputdef.txt is a tab-separated file containing a header for one-channel-per-file runs:
mzmlfile instrument setname channel
/path/to/fn.mzML qe setA 126
...
or pooled channels in a file:
mzmlfile instrument setname
/path/to/fn.mzML qe setA
...
Each of these inputs leads to a slightly different report, see examples for pooled, and non-pooled results. The pipeline performs identification and quantification, and the output contains graphs to display the amount of incorporated isobaric label per sample on both peptide and PSM level. For the non-pooled runs, a PSM/peptide is considered to be not labeled if any of its K residues or its N-term have not been labeled. For pooled reports there is information on the amount of PSMs with missing values per channel. The report also shows the amount of labeling in the different channels per sample, as well as missed cleavages.
The lehtiolab/nf-labelcheck pipeline comes with documentation about the pipeline, found in the docs/ directory:
lehtiolab/nf-labelcheck was originally written by Jorrit Boekel and took inspiration and boilerplate from the nf-core best practices and templates.