import_dataset_openms_mztab: Import a label-free DDA proteomics dataset from OpenMS,...
In ftwkoopmans/msdap: Mass Spectrometry Downstream Analysis Pipeline
import_dataset_openms_mztab R Documentation
Import a label-free DDA proteomics dataset from OpenMS, experimental feature !
Description
This parser is based on output we generated with OpenMS 2.5 using input data and parameters/instructions from: https://abibuilder.cs.uni-tuebingen.de/archive/openms/Tutorials/Data/iPRG2015_Hannes/
Usage
import_dataset_openms_mztab(filename)
Arguments
filename
full path to the mzTab file
Details
Check the file "run_lfq.sh" in the above instructions (from OpenMS team) for exact workflow and settings used.
By lack of more example mzTab files that we can adapt to, this code now only supports input data generated as in run_lfq.sh from the above example;
The main dependency / complication is that we require the peptide- and protein-scores exactly as computed in the reference OpenMS workflow.
Thus, on each mzML file, apply search engine (eg; xtandem), PercolatorAdapter, FalseDiscoveryRate, IDFilter, IDScoreSwitcher.
finally run ProteomicsLFQ on the entire dataset.
ftwkoopmans/msdap documentation built on March 5, 2025, 12:15 a.m.
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| import_dataset_openms_mztab | R Documentation |
Import a label-free DDA proteomics dataset from OpenMS, experimental feature !
Description
This parser is based on output we generated with OpenMS 2.5 using input data and parameters/instructions from: https://abibuilder.cs.uni-tuebingen.de/archive/openms/Tutorials/Data/iPRG2015_Hannes/
Usage
import_dataset_openms_mztab(filename)
Arguments
filename |
full path to the mzTab file |
Details
Check the file "run_lfq.sh" in the above instructions (from OpenMS team) for exact workflow and settings used.
By lack of more example mzTab files that we can adapt to, this code now only supports input data generated as in run_lfq.sh from the above example;
The main dependency / complication is that we require the peptide- and protein-scores exactly as computed in the reference OpenMS workflow. Thus, on each mzML file, apply search engine (eg; xtandem), PercolatorAdapter, FalseDiscoveryRate, IDFilter, IDScoreSwitcher. finally run ProteomicsLFQ on the entire dataset.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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