automated-lipid-identification
Summary
LipidA-IDER is an automated structure annotation tool that identifies lipid A from high-resolution tandem mass spectrometry (MS2) data at systems-level scale. Use this skill to rapidly annotate and structurally characterize lipid A molecules from MS2 spectra without manual intervention.
When to use
You have high-resolution tandem mass spectrometry (MS2) data in .ms2 format and need to systematically identify and annotate lipid A molecular structures. This skill is appropriate when you lack prior lipid A structural annotations and want to apply uniform, automated structure-matching criteria across large MS2 datasets.
When NOT to use
- Your input mass spectrometry data is in a format other than .ms2 (e.g., raw vendor format, mzML, or NetCDF) without prior conversion via MSConvert.
- You are running the tool on macOS or Linux — LipidA-IDER has only been tested on Windows; use on other platforms has not been validated.
- Your data contains lipid classes other than lipid A, or you need simultaneous annotation of multiple diverse lipid classes.
Inputs
- .ms2 format mass spectrometry data files (peak-picked MS2 spectra)
- LipidAIDER_AnalysisParam.csv (parameter configuration file)
- LipidAIDER_BatchAnalysisFiles.csv (batch metadata file, optional for CLI mode)
Outputs
- Annotated lipid A structure assignments and identifications
- Batch output files in Logger//Batch Output subdirectory
How to apply
First, ensure your mass spectrometry data is in .ms2 format (convert using MSConvert with Peak Picking [CWT algorithm] and MS Levels 2 if needed). Install Python and git, then clone the LipidA-IDER repository. Open a terminal in the LipidA-IDER directory and either (1) launch the GUI via python LipidAIDER_GUI.py, select your .ms2 file(s) and default or custom parameter settings, then click 'Run Analysis'; or (2) use CLI mode by editing the batch and parameter CSV files, then invoke python LIPIDAIDER_main.py or python LIPIDAIDER_main.py -m <PATH_TO_MS2_FILE>. The tool will generate annotated lipid A structure outputs in a timestamped Logger subdirectory. Verify outputs contain expected annotation fields and compare against known lipid A reference spectra to confirm structural assignments.
Related tools
Examples
$ python LIPIDAIDER_main.py -m /path/to/demo_input_files/sample.ms2
Evaluation signals
- Output files are successfully written to the timestamped Logger//Batch Output directory with no error messages or incomplete annotation records.
- Annotated lipid A structures can be parsed and contain expected fields (e.g., structure identifiers, fragment ion assignments, scoring metrics).
- Annotation results for demo input files match documented expected outputs (compare against expected lipid A reference standards).
- CLI invocations complete without Python runtime errors; GUI mode displays 'selected files' confirmation before and 'Run Analysis' completion status after execution.
- Parameter settings from LipidAIDER_AnalysisParam.csv are correctly applied to the analysis (verify by inspecting output metadata or log files).
Limitations
- LipidA-IDER has only been tested on Windows; use on macOS and Linux has not been tested and may fail or produce unreliable results.
- Tool currently accepts only .ms2 format input; other mass spectrometry data formats require conversion via MSConvert, adding preprocessing overhead.
- No changelog is publicly available, limiting users' ability to track feature additions, bug fixes, or breaking changes across versions.
- Default parameter settings are optimized for lipid A; use on data with different sample origins or instrumental configurations may require parameter tuning via the CSV configuration file.
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] Input file format and conversion requirement for .ms2: "LipidAIDER currently accepts data in .ms2 format. To convert to .ms2, use MSConvert (ProteoWizard)"
- [readme] Platform limitation and testing scope: "As of current, LipidA-IDER has only been tested on Windows. Use of LipidA-IDER on MacOS and Linux has not been tested."
- [readme] Demo files availability for users without initial data: "In the event that you do not have initial .ms2 data, we have provided the some demo input files for your use here: [\Source\demo_input_files]"
- [readme] Output location specification: "Upon completion of the analysis. the generated output will be found in the '\Logger<YYYYMMDD_HHMMSS>\Batch Output' subfolder."
- [readme] Parameter configuration workflow: "If you would like to modify parameters to better suit your data, you may do so by changing the relevant setting values in the csv file found in [\Settings\LipidAIDER_AnalysisParam.csv]"
1---2name: automated-lipid-identification3description: Use when you have high-resolution tandem mass spectrometry (MS2) data in .ms2 format and need to systematically identify and annotate lipid A molecular structures.4license: CC-BY-4.05---67# automated-lipid-identification89## Summary1011LipidA-IDER is an automated structure annotation tool that identifies lipid A from high-resolution tandem mass spectrometry (MS2) data at systems-level scale. Use this skill to rapidly annotate and structurally characterize lipid A molecules from MS2 spectra without manual intervention.1213## When to use1415You have high-resolution tandem mass spectrometry (MS2) data in .ms2 format and need to systematically identify and annotate lipid A molecular structures. This skill is appropriate when you lack prior lipid A structural annotations and want to apply uniform, automated structure-matching criteria across large MS2 datasets.1617## When NOT to use1819- Your input mass spectrometry data is in a format other than .ms2 (e.g., raw vendor format, mzML, or NetCDF) without prior conversion via MSConvert.20- You are running the tool on macOS or Linux — LipidA-IDER has only been tested on Windows; use on other platforms has not been validated.21- Your data contains lipid classes other than lipid A, or you need simultaneous annotation of multiple diverse lipid classes.2223## Inputs2425- .ms2 format mass spectrometry data files (peak-picked MS2 spectra)26- LipidAIDER_AnalysisParam.csv (parameter configuration file)27- LipidAIDER_BatchAnalysisFiles.csv (batch metadata file, optional for CLI mode)2829## Outputs3031- Annotated lipid A structure assignments and identifications32- Batch output files in Logger/<YYYYMMDD_HHMMSS>/Batch Output subdirectory3334## How to apply3536First, ensure your mass spectrometry data is in .ms2 format (convert using MSConvert with Peak Picking [CWT algorithm] and MS Levels 2 if needed). Install Python and git, then clone the LipidA-IDER repository. Open a terminal in the LipidA-IDER directory and either (1) launch the GUI via `python LipidAIDER_GUI.py`, select your .ms2 file(s) and default or custom parameter settings, then click 'Run Analysis'; or (2) use CLI mode by editing the batch and parameter CSV files, then invoke `python LIPIDAIDER_main.py` or `python LIPIDAIDER_main.py -m <PATH_TO_MS2_FILE>`. The tool will generate annotated lipid A structure outputs in a timestamped Logger subdirectory. Verify outputs contain expected annotation fields and compare against known lipid A reference spectra to confirm structural assignments.3738## Related tools3940- **Python** (Runtime environment for executing the LipidA-IDER GUI and CLI scripts)41- **git** (Version control and repository cloning to obtain the LipidA-IDER codebase) — https://github.com/git-guides/install-git42- **MSConvert (ProteoWizard)** (Preprocessing tool to convert raw mass spectrometry data to .ms2 format with peak picking (CWT algorithm, MS Levels 2)) — https://proteowizard.sourceforge.io/download.html4344## Examples4546```47$ python LIPIDAIDER_main.py -m /path/to/demo_input_files/sample.ms248```4950## Evaluation signals5152- Output files are successfully written to the timestamped Logger/<YYYYMMDD_HHMMSS>/Batch Output directory with no error messages or incomplete annotation records.53- Annotated lipid A structures can be parsed and contain expected fields (e.g., structure identifiers, fragment ion assignments, scoring metrics).54- Annotation results for demo input files match documented expected outputs (compare against expected lipid A reference standards).55- CLI invocations complete without Python runtime errors; GUI mode displays 'selected files' confirmation before and 'Run Analysis' completion status after execution.56- Parameter settings from LipidAIDER_AnalysisParam.csv are correctly applied to the analysis (verify by inspecting output metadata or log files).5758## Limitations5960- LipidA-IDER has only been tested on Windows; use on macOS and Linux has not been tested and may fail or produce unreliable results.61- Tool currently accepts only .ms2 format input; other mass spectrometry data formats require conversion via MSConvert, adding preprocessing overhead.62- No changelog is publicly available, limiting users' ability to track feature additions, bug fixes, or breaking changes across versions.63- Default parameter settings are optimized for lipid A; use on data with different sample origins or instrumental configurations may require parameter tuning via the CSV configuration file.6465## Evidence6667- [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"68- [readme] Input file format and conversion requirement for .ms2: "LipidAIDER currently accepts data in .ms2 format. To convert to .ms2, use MSConvert (ProteoWizard)"69- [readme] Platform limitation and testing scope: "As of current, LipidA-IDER has only been tested on Windows. Use of LipidA-IDER on MacOS and Linux has *not* been tested."70- [readme] Demo files availability for users without initial data: "In the event that you do not have initial .ms2 data, we have provided the some demo input files for your use here: [\Source\demo_input_files]"71- [readme] Output location specification: "Upon completion of the analysis. the generated output will be found in the '\Logger\<YYYYMMDD_HHMMSS>\Batch Output' subfolder."72- [readme] Parameter configuration workflow: "If you would like to modify parameters to better suit your data, you may do so by changing the relevant setting values in the csv file found in [\Settings\LipidAIDER_AnalysisParam.csv]"