--- name: automated-lipid-identification description: 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. license: CC-BY-4.0 metadata: edam_operation: http://edamontology.org/operation_3631 edam_topics: - http://edamontology.org/topic_0153 - http://edamontology.org/topic_3375 tools: - Python - git - MSConvert (ProteoWizard) techniques: - LC-MS derived_from: - doi: 10.1021/acs.analchem.5c00520 title: LipidA-IDER evidence_spans: - $ python LipidAIDER_GUI.py - 'Step 0: Install git (if you have not done so before)' claims: [] provenance: collection: https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v2 assembled_by: scripts/collect_metabolomics_collection.py sources: - build: coll_lipida_ider_cq doi: 10.1021/acs.analchem.5c00520 title: LipidA-IDER dedup_kept_from: coll_lipida_ider_cq schema_version: 0.2.0 attribution: generator: AgenticScienceBuilder original_doi: 10.1021/acs.analchem.5c00520 all_source_dois: - 10.1021/acs.analchem.5c00520 zenodo_doi: 10.5281/zenodo.20794027 curators: [] promoter: Louis-Félix Nothias sponsor: CNRS & Université Côte d'Azur --- # 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 `. 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 - **Python** (Runtime environment for executing the LipidA-IDER GUI and CLI scripts) - **git** (Version control and repository cloning to obtain the LipidA-IDER codebase) — https://github.com/git-guides/install-git - **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.html ## 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\\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]"