High resolution ms2 peak assignment
Use when you have high-resolution MS2 data in .ms2 format from lipid A samples and need to perform automated structure annotation to identify lipid A molecular variants and their fragmentation patterns at scale.From its SKILL.md
npx -y skills add HolobiomicsLab/asb-skill-collections --skill high-resolution-ms2-peak-assignmentAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 15 stars15 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its file declares
Copied from the file, not written here
The file declares its own license as CC-BY-4.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
6.3 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it
high-resolution-ms2-peak-assignment
Summary
Automated structure annotation of lipid A from high-resolution tandem mass spectrometry (MS2) data by assigning fragment peaks to lipid A structural moieties. This skill is essential when you have MS2 spectra and need to identify and annotate lipid A molecular structures at systems level.
When to use
Apply this skill when you have high-resolution MS2 data in .ms2 format from lipid A samples and need to perform automated structure annotation to identify lipid A molecular variants and their fragmentation patterns at scale.
When NOT to use
- Input data is not in .ms2 format — first convert using MSConvert (ProteoWizard) with Peak Picking (CWT algorithm) and MS Level 2 filters
- Your mass spectrometry data is from non-lipid A samples or low-resolution instruments not suitable for structure annotation
- You are running on MacOS or Linux — LipidA-IDER has only been tested on Windows; use on other platforms has not been validated
Inputs
- .ms2 format mass spectrometry data files
- LipidAIDER_AnalysisParam.csv parameter settings file
- LipidAIDER_BatchAnalysisFiles.csv batch specification (for CLI mode)
Outputs
- Annotated lipid A structure assignments
- Fragment peak annotations with m/z assignments
- Batch output folder (Logger/<YYYYMMDD_HHMMSS>/Batch Output)
How to apply
LipidA-IDER performs peak assignment by accepting .ms2 format input files containing high-resolution tandem mass spectrometry data. The tool uses configurable analysis parameters (stored in LipidAIDER_AnalysisParam.csv) to control peak picking, m/z tolerance, and structural annotation thresholds. Users prepare input files and parameter settings, then execute the analysis via either GUI (python LipidAIDER_GUI.py) or CLI (python LIPIDAIDER_main.py). The analysis generates annotated output in a timestamped Logger directory containing structural assignments for detected lipid A species. Success is verified by confirming that annotated lipid A structure outputs are generated and saved to the specified output directory with assigned fragment annotations.
Related tools
- Python (Execution environment for LipidA-IDER GUI and CLI interfaces)
- git (Repository cloning tool to obtain LipidA-IDER source code) — https://github.com/Systems-Biology-Of-Lipid-Metabolism-Lab/LipidA-IDER
- MSConvert (ProteoWizard) (Data format conversion to .ms2 with peak picking (CWT algorithm, MS Level 2)) — https://proteowizard.sourceforge.io/download.html
Examples
$ python LIPIDAIDER_main.py -m /path/to/demo_input_files/sample.ms2
Evaluation signals
- Output files are generated in the timestamped Logger directory with expected structure (Logger/<YYYYMMDD_HHMMSS>/Batch Output)
- Annotated lipid A structural assignments are present in output with fragment peak m/z values assigned
- No runtime errors or warnings in terminal/CLI output indicating parameter or data format issues
- Output files contain expected number of annotated lipid A species matching input sample count
- Batch Output folder contains dated subdirectory matching analysis run timestamp
Limitations
- LipidA-IDER has only been tested on Windows; use on MacOS and Linux has not been tested
- Currently accepts only .ms2 format data files; other formats require preprocessing with MSConvert
- Requires .ms2 input files to have been processed with Peak Picking using CWT algorithm at MS Level 2
- Performance and accuracy depend on appropriate parameter tuning in LipidAIDER_AnalysisParam.csv for the specific MS data nature
Evidence
- [readme] LipidA-IDER is an automated structure annotation tool for systems-level scale identification of lipid A from high resolution tandem mass spectrometry (MS2) data: "LipidA-IDER is an automated structure annotation tool for systems-level scale identification of lipid A from high resolution tandem mass spectrometry (MS2) data"
- [readme] LipidAIDER currently accepts data in .ms2 format. To convert to .ms2, use MSConvert (ProteoWizard) (download from: https://proteowizard.sourceforge.io/download.html) Settings: Output format: .ms2, Filters: Peak Picking, Algorithm: CWT, MS Levels: 2: "LipidAIDER currently accepts data in .ms2 format. To convert to .ms2, use MSConvert (ProteoWizard) Settings: Output format: .ms2, Filters: Peak Picking, Algorithm: CWT, MS Levels: 2"
- [readme] As of current, LipidA-IDER has only been tested on Windows. Use of LipidA-IDER on MacOS and Linux has not been tested: "LipidA-IDER has only been tested on Windows. Use of LipidA-IDER on MacOS and Linux has not been tested"
- [readme] Upon completion of the analysis. the generated output will be found in the '\Logger<YYYYMMDD_HHMMSS>\Batch Output' subfolder: "Upon completion of the analysis. the generated output will be found in the '\Logger<YYYYMMDD_HHMMSS>\Batch Output' subfolder"
- [readme] The default parameters are provided in \Settings\LipidAIDER_AnalysisParam.csv. Users may edit this file to according to the nature of their data: "Users may edit this file to according to the nature of their data"
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.