Hrms Data Format Parsing

hrms-data-format-parsing

Summary

Parse and load experimental high-resolution tandem mass spectrometry (HRMS/MS) data from instrument-specific file formats (mzML, CSV peaklists, vendor formats) into a standardized in-memory representation suitable for fragment m/z matching and lipid identification workflows. This skill bridges raw instrument output to downstream lipidomics analysis.

When to use

You have raw or processed HRMS/MS data from Q-Exactive, Agilent Q-TOF, Bruker Q-TOF, or SCIEX Q-TOF instruments in formats such as mzML, CSV peaklists, or vendor-specific formats, and you need to extract experimental fragment m/z values and their intensities for comparison against in-silico lipid fragmentation libraries.

When NOT to use

• Input is already a vendor-independent, harmonized peaklist or feature table from peak-picking software (MZmine, XCMS, MS-DIAL, or Compound Discoverer); use that output directly.
• Data is from Waters UHPLC-HRMS/MS instruments; LipidMatch does not currently support Waters files.
• Raw m/z values have already been matched to library fragments; this skill applies only to raw or minimally processed experimental data.

Inputs

• mzML files from Q-Exactive or Q-TOF UHPLC-HRMS/MS
• CSV peaklist files (Q-Exactive or Q-TOF format) with m/z and intensity columns
• Vendor-specific raw files or vendor-converted CSV exports

Outputs

• Structured peaklist table (m/z, intensity, optional: retention time, charge state)
• In-memory array of experimental fragment m/z values
• Validated peaklist ready for downstream m/z matching and lipid identification

How to apply

Load experimental peaklist files in CSV or mzML-derived table format containing m/z and intensity pairs from your HRMS/MS instrument (Q-Exactive orbitrap or Q-TOF platforms). Parse the file headers and data columns to extract fragment m/z values and associated metadata. Ensure mass values are in the same mass tolerance units (typically ppm or Da) that will be used in the downstream m/z matching step. Validate that the parsed m/z range and intensity distribution are consistent with the acquisition method (targeted, data-dependent MS/MS top-N, or all-ion fragmentation). Output a structured table or in-memory array of m/z–intensity pairs ready for matching against the LipidMatch in-silico library.

Related tools

• MZmine (Peak picking and peaklist generation from raw HRMS/MS data; produces CSV or other formats compatible with LipidMatch input)
• XCMS (Centroiding and peak detection from mzML or netCDF; exports peaklist for m/z matching workflows)
• MS-DIAL (Peak picking and spectral deconvolution for HRMS/MS data; generates peaklists for downstream matching)
• Compound Discoverer (Commercial peak picking and annotation software compatible with LipidMatch input format)
• Q-Exactive orbitrap (Thermo HRMS/MS instrument producing mzML and vendor-format files containing experimental fragment m/z data)
• Agilent Q-TOF UHPLC-HRMS/MS (Agilent TOF instrument generating peaklists and raw files with fragment m/z values)
• Bruker Q-TOF UHPLC-HRMS/MS (Bruker TOF instrument producing raw and converted peaklist formats for fragment matching)
• SCIEX Q-TOF UHPLC-HRMS/MS (SCIEX TOF instrument generating peaklists compatible with LipidMatch input specifications)

Evaluation signals

• Parsed peaklist contains m/z values in expected range (typically 100–1200 m/z for lipidomics), with no missing or corrupted entries.
• Intensity values are positive and span a reasonable dynamic range (e.g., 1e4 to 1e8 for orbitrap data); no negative or zero intensities in valid peaks.
• Header row and column mapping are correctly identified; optional metadata (retention time, charge state) are present and non-null where expected.
• Parsed data structure matches the input format specification (e.g., CSV with columns [m/z, intensity, ...] or mzML scan-level m/z–intensity arrays).
• Data integrity check: file size, row count, and column count are consistent; no truncated or corrupted records detected.

Limitations

• Waters UHPLC-HRMS/MS files are not currently supported by downstream LipidMatch matching; data from Waters instruments cannot proceed in this workflow.
• mzML parsing requires correct mzML format compliance; malformed or non-standard mzML variants may fail to parse correctly.
• CSV peaklist parsing is format-dependent; inconsistent column headers, delimiters, or decimal formats across vendor implementations may cause parsing errors.
• Mass calibration errors in raw data are not corrected during parsing; ensure instrument mass calibration is adequate before file acquisition.

Evidence

• [other] Load experimental fragment m/z values from a peaklist file (Q-Exactive or Q-TOF format, e.g., CSV or mzML-derived table): "Load experimental fragment m/z values from a peaklist file (Q-Exactive or Q-TOF format, e.g., CSV or mzML-derived table)"
• [readme] LipidMatch identifications are obtained by matching experimental fragment m/z values with simulated library m/z values using in-silico fragmentation libraries: "LipidMatch identifications are obtained by matching experimental fragment m/z values with simulated library m/z values using in-silico fragmentation libraries"
• [readme] LipidMatch has been tested and validated using Q-Exactive orbitrap UHPLC-HRMS/MS data obtained from multiple sample types using targeted, data-dependent top-N (ddMS2-topN), and all ion fragmentation (AIF) approaches, as well as Agilent, Bruker and SCIEX Q-TOF UHPLC-HRMS/MS experiments: "LipidMatch has been tested and validated using Q-Exactive orbitrap UHPLC-HRMS/MS data obtained from multiple sample types using targeted, data-dependent top-N (ddMS2-topN), and all ion fragmentation"
• [readme] The software does not currently support Waters files: "The software does not currently support Waters files"
• [readme] LipidMatch can be used with various peak picking software (for example MZmine, XCMS, MS-DIAL, and Compound Discoverer): "LipidMatch can be used with various peak picking software (for example MZmine, XCMS, MS-DIAL, and Compound Discoverer)"