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ComFaceID-MSNs

In statistics, multi-parameter analysis provides a more comprehensive and robust assessment than single-parameter approaches by capturing systemic complexity, thereby reducing bias and improving predictive accuracy.

This module combined structural class concordance, molecular fingerprint similarity, and exact mass deviation of matched structures, for directly assessing structural novelty from MS² spectra. MSNs means Metabolite Structural Novelty Score.

  1. Please log in and upload files before use.

    Data preparation is described in the MSConvert Usage section.

  2. Check the parameter settings.

    The default parameters settings are designed to be compatible with Q-TOF systems from different manufacturers, such as Waters, SCIEX, Thermo, etc. Users may modify these parameters as needed for their particular analytical purposes.

    Parameter & Description Default Setting
    Filter by mass: Relative molecular mass screening thresholds in pretreatment 200
    Top hit number: output number for each input m/z. 1
    FPsearch: Whether to output FPSearch results false
    Classification: Whether to output Classification results false
    Lambda: Whether to output Lambda value false

  3. Upload the corresponding files under the option.

    For Input files option (Required), please insure that the input file contains valid MS/MS information;

    For Peaktable file option (Optional), select the peak table file corresponding to mzXML.; it supports the .csv format and must contain two columns named “mz” and “rt”. This table is optional and provides the m/z and retention time (in seconds) for precursor ions of interest. For the sample of interest, only MS2 spectra corresponding to the targeted precursor ions are included in the analysis.

    Note: when uploading a peak table, please ensure that the converted file (.mzXML) from the same original data file and its corresponding peak table (.csv) are named exactly the same.

  4. Enter a task name to start your analysis journey.

    Click "Tasks" at any time to check your analysis progress.

  5. Data output.

    After the task finishes, a "final_results.csv" file will be provided.

  6. Data analysis.

    A brief explanation of the key output results is provided below.

    Columns Description
    sid m/z and its corresponding source file.
    Precursor Precursor ions
    Fingerprint_sim Tanimoto similarity of molecular fingerprints for the matched compound and input precursor ion.
    PubChem_InChIkey The InChIkey of the matched compound, copyable to PubChem https://pubchem.ncbi.nlm.nih.gov/ for structure lookup.
    PubChem_SMILES The SMILES of the matched compound, copyable to PubChem https://pubchem.ncbi.nlm.nih.gov/ or ChemDraw software for structure lookup.
    PubChem_Exact_Mass The exact mass of the matched compound
    ComfaceID_Class_Result Highest-confidence classification result for the matched metabolite
    ABS (match-true) exact mass deviation of matched structures
    Class_P Classification confidence
    Lambda Lambda combines a power-law and an exponential function to scale the exact mass difference to the interval (0, 1]. It is highly sensitive to small variations in the exact mass difference when the difference is minimal.
    MSNs Metabolite Structural Novelty Score