--- name: tandem-mass-spectrometry-data-interpretation description: Use when you have high-resolution MS2 data (.ms2 format) from tandem mass spectrometry analysis of lipid A-containing samples and need to perform automated structure annotation and identification at systems scale. license: CC-BY-4.0 metadata: edam_operation: http://edamontology.org/operation_3929 edam_topics: - http://edamontology.org/topic_3172 - http://edamontology.org/topic_0153 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 --- # tandem-mass-spectrometry-data-interpretation ## Summary Automated structure annotation of lipid A from high-resolution tandem mass spectrometry (MS2) data using LipidA-IDER, an open-source tool that identifies and classifies lipid A molecular species at systems scale. This skill enables conversion of raw MS2 spectral data into annotated lipid structure outputs. ## When to use You have high-resolution MS2 data (.ms2 format) from tandem mass spectrometry analysis of lipid A-containing samples and need to perform automated structure annotation and identification at systems scale. You lack established lipid A reference libraries or wish to standardize annotation across large sample batches. You want to avoid manual peak assignment and structural hypothesis generation. ## When NOT to use - Input data is in formats other than .ms2 (e.g., raw vendor formats, mzML, NetCDF) without prior conversion - Running on MacOS or Linux systems, as LipidA-IDER has only been tested and validated on Windows - Data consists of MS1 spectra only or does not include tandem MS2 fragmentation data ## Inputs - .ms2 format mass spectrometry data files - LipidAIDER_AnalysisParam.csv configuration file (optional custom parameters) - LipidAIDER_BatchAnalysisFiles.csv batch definition file (for CLI mode) ## Outputs - Annotated lipid A structure assignments - Batch output files in Logger//Batch Output directory - Per-spectrum annotation records with lipid A molecular identities ## How to apply First, prepare input data by converting raw mass spectrometry files to .ms2 format using MSConvert (ProteoWizard) with peak picking (CWT algorithm) and MS level 2 filtering. Clone the LipidA-IDER repository and install Python dependencies. Configure analysis parameters in the LipidAIDER_AnalysisParam.csv settings file to match your data characteristics (e.g., m/z accuracy, fragment ion thresholds). Execute LipidA-IDER via either the GUI ($ python LipidAIDER_GUI.py) for interactive file selection and parameter adjustment, or CLI ($ python LIPIDAIDER_main.py -m ) for batch processing. Monitor the Logger directory for timestamped output folders containing annotated lipid structures. Verify output completeness by checking that all input .ms2 records generated corresponding structure annotations. ## Related tools - **MSConvert (ProteoWizard)** (Converts raw mass spectrometry data to .ms2 format with peak picking and MS level 2 filtering) — https://proteowizard.sourceforge.io/download.html - **Python** (Runtime environment for executing LipidA-IDER GUI and CLI interfaces) - **git** (Version control tool for cloning the LipidA-IDER repository) ## Examples ``` $ python LIPIDAIDER_main.py -m /path/to/sample.ms2 ``` ## Evaluation signals - Output directory exists in Logger with correctly formatted YYYYMMDD_HHMMSS timestamp - Batch Output folder contains annotation records for all input .ms2 files without truncation or errors - Annotated lipid A structures include defined molecular identities with m/z values and fragment ion assignments consistent with input spectra - Parameter values in settings file align with expected MS data characteristics (e.g., instrument resolution, ion mode) - No error logs or warnings in stdout/stderr indicating failed spectrum processing or missing required input files ## Limitations - LipidA-IDER has only been tested on Windows; use on MacOS and Linux has not been tested and is unsupported - Accepts only .ms2 format input; conversion from other formats (raw vendor data, mzML) is required beforehand - Output quality and annotation accuracy depend on proper configuration of analysis parameters in LipidAIDER_AnalysisParam.csv; misaligned parameters may produce spurious or incomplete annotations - Tool is optimized for lipid A structures specifically; applicability to other lipid classes or modified lipid A species is not documented ## 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] As of current, LipidA-IDER has only been tested on Windows. Use of LipidA-IDER on MacOS and Linux has *not* been tested.: "As of current, LipidA-IDER has only been tested on Windows. Use of LipidA-IDER on MacOS and Linux has *not* been tested." - [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] Upon completion of the analysis. the generated output will be found in the '\Logger\\Batch Output' subfolder.: "Upon completion of the analysis. the generated output will be found in the '\Logger\\Batch Output' subfolder." - [readme] 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]: "In the event that you do not have initial .ms2 data, we have provided the some demo input files for your use"