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GNPS

nplinker.metabolomics.gnps

GNPSFormat

Bases: Enum

Enum class for GNPS formats or workflows.

Concept

GNPS data

The name of the enum is a short name for the workflow, and the value of the enum is the workflow name used on the GNPS website.

SNETS class-attribute instance-attribute 

SNETS = 'METABOLOMICS-SNETS'

SNETSV2 class-attribute instance-attribute 

SNETSV2 = 'METABOLOMICS-SNETS-V2'

FBMN class-attribute instance-attribute 

FBMN = 'FEATURE-BASED-MOLECULAR-NETWORKING'

Unknown class-attribute instance-attribute 

Unknown = 'Unknown-GNPS-Workflow'

GNPSDownloader 

GNPSDownloader(task_id: str, download_root: str | PathLike)

Download GNPS zip archive for the given task id.

Concept

GNPS data

Note that only GNPS workflows listed in the GNPSFormat enum are supported.

Attributes:

Parameters:

  • task_id (str) –

    GNPS task id, identifying the data to be downloaded.

  • download_root (str | PathLike) –

    Path where to store the downloaded archive.

Raises:

  • ValueError –

    If the given task id does not correspond to a supported GNPS workflow.

Examples:

>>> GNPSDownloader("c22f44b14a3d450eb836d607cb9521bb", "~/downloads")
Source code in src/nplinker/metabolomics/gnps/gnps_downloader.py 
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def __init__(self, task_id: str, download_root: str | PathLike):
    """Initialize the GNPSDownloader.

    Args:
        task_id: GNPS task id, identifying the data to be downloaded.
        download_root: Path where to store the downloaded archive.

    Raises:
        ValueError: If the given task id does not correspond to a supported
            GNPS workflow.

    Examples:
        >>> GNPSDownloader("c22f44b14a3d450eb836d607cb9521bb", "~/downloads")
    """
    gnps_format = gnps_format_from_task_id(task_id)
    if gnps_format == GNPSFormat.Unknown:
        raise ValueError(
            f"Unknown workflow type for GNPS task '{task_id}'."
            f"Supported GNPS workflows are described in the GNPSFormat enum, "
            f"including such as 'METABOLOMICS-SNETS', 'METABOLOMICS-SNETS-V2' "
            f"and 'FEATURE-BASED-MOLECULAR-NETWORKING'."
        )

    self._task_id = task_id
    self._download_root: Path = Path(download_root)
    self._gnps_format = gnps_format
    self._file_name = gnps_format.value + "-" + self._task_id + ".zip"

GNPS_DATA_DOWNLOAD_URL class-attribute instance-attribute 

GNPS_DATA_DOWNLOAD_URL: str = (
    "https://gnps.ucsd.edu/ProteoSAFe/DownloadResult?task={}&view=download_clustered_spectra"
)

GNPS_DATA_DOWNLOAD_URL_FBMN class-attribute instance-attribute 

GNPS_DATA_DOWNLOAD_URL_FBMN: str = (
    "https://gnps.ucsd.edu/ProteoSAFe/DownloadResult?task={}&view=download_cytoscape_data"
)

gnps_format property 

gnps_format: GNPSFormat

Get the GNPS workflow type.

Returns:

download 

download() -> Self

Download GNPS data.

Note: GNPS data is downloaded using the POST method (empty payload is OK).

Source code in src/nplinker/metabolomics/gnps/gnps_downloader.py 
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def download(self) -> Self:
    """Download GNPS data.

    Note: GNPS data is downloaded using the POST method (empty payload is OK).
    """
    download_url(
        self.get_url(), self._download_root, filename=self._file_name, http_method="POST"
    )
    return self

get_download_file 

get_download_file() -> str

Get the path to the downloaded file.

Returns:

  • str –

    Download path as string

Source code in src/nplinker/metabolomics/gnps/gnps_downloader.py 
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def get_download_file(self) -> str:
    """Get the path to the downloaded file.

    Returns:
        Download path as string
    """
    return str(Path(self._download_root) / self._file_name)

get_task_id 

get_task_id() -> str

Get the GNPS task id.

Returns:

  • str –

    Task id as string.

Source code in src/nplinker/metabolomics/gnps/gnps_downloader.py 
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def get_task_id(self) -> str:
    """Get the GNPS task id.

    Returns:
        Task id as string.
    """
    return self._task_id

get_url 

get_url() -> str

Get the download URL.

Returns:

  • str –

    URL pointing to the GNPS data to be downloaded.

Source code in src/nplinker/metabolomics/gnps/gnps_downloader.py 
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def get_url(self) -> str:
    """Get the download URL.

    Returns:
        URL pointing to the GNPS data to be downloaded.
    """
    if self.gnps_format == GNPSFormat.FBMN:
        return GNPSDownloader.GNPS_DATA_DOWNLOAD_URL_FBMN.format(self._task_id)
    return GNPSDownloader.GNPS_DATA_DOWNLOAD_URL.format(self._task_id)

GNPSExtractor 

GNPSExtractor(
    file: str | PathLike, extract_dir: str | PathLike
)

Extract files from a GNPS molecular networking archive (.zip).

Concept

GNPS data

Four files are extracted and renamed to the following names:

  • file_mappings(.tsv/.csv)
  • spectra.mgf
  • molecular_families.tsv
  • annotations.tsv

The files to be extracted are selected based on the GNPS workflow type, as described below (in the order of the files above):

  1. METABOLOMICS-SNETS
    • clusterinfosummarygroup_attributes_withIDs_withcomponentID/*.tsv
    • METABOLOMICS-SNETS*.mgf
    • networkedges_selfloop/*.pairsinfo
    • result_specnets_DB/*.tsv
  2. METABOLOMICS-SNETS-V2
    • clusterinfosummarygroup_attributes_withIDs_withcomponentID/*.clustersummary
    • METABOLOMICS-SNETS-V2*.mgf
    • networkedges_selfloop/*.selfloop
    • result_specnets_DB/.tsv
  3. FEATURE-BASED-MOLECULAR-NETWORKING
    • quantification_table/.csv
    • spectra/*.mgf
    • networkedges_selfloop/*.selfloop
    • DB_result/*.tsv

Attributes:

Parameters:

  • file (str | PathLike) –

    The path to the GNPS zip file.

  • extract_dir (str | PathLike) –

    path to the directory where to extract the files to.

Raises:

  • ValueError –

    If the given file is an invalid GNPS archive.

Examples:

>>> gnps_extractor = GNPSExtractor("path/to/gnps_archive.zip", "path/to/extract_dir")
>>> gnps_extractor.gnps_format
<GNPSFormat.SNETS: 'METABOLOMICS-SNETS'>
>>> gnps_extractor.extract_dir
'path/to/extract_dir'
Source code in src/nplinker/metabolomics/gnps/gnps_extractor.py 
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def __init__(self, file: str | PathLike, extract_dir: str | PathLike):
    """Initialize the GNPSExtractor.

    Args:
        file: The path to the GNPS zip file.
        extract_dir: path to the directory where to extract the files to.

    Raises:
        ValueError: If the given file is an invalid GNPS archive.

    Examples:
        >>> gnps_extractor = GNPSExtractor("path/to/gnps_archive.zip", "path/to/extract_dir")
        >>> gnps_extractor.gnps_format
        <GNPSFormat.SNETS: 'METABOLOMICS-SNETS'>
        >>> gnps_extractor.extract_dir
        'path/to/extract_dir'
    """
    gnps_format = gnps_format_from_archive(file)
    if gnps_format == GNPSFormat.Unknown:
        raise ValueError(
            f"Unknown workflow type for GNPS archive '{file}'."
            f"Supported GNPS workflows are described in the GNPSFormat enum, "
            f"including such as 'METABOLOMICS-SNETS', 'METABOLOMICS-SNETS-V2' "
            f"and 'FEATURE-BASED-MOLECULAR-NETWORKING'."
        )

    self._file = Path(file)
    self._extract_path = Path(extract_dir)
    self._gnps_format = gnps_format
    # the order of filenames matters
    self._target_files = [
        "file_mappings",
        "spectra.mgf",
        "molecular_families.tsv",
        "annotations.tsv",
    ]

    self._extract()

gnps_format property 

gnps_format: GNPSFormat

Get the GNPS workflow type.

Returns:

extract_dir property 

extract_dir: str

Get the path where to extract the files to.

Returns:

  • str –

    Path where to extract files as string.

GNPSSpectrumLoader 

GNPSSpectrumLoader(file: str | PathLike)

Bases: SpectrumLoaderBase

Load mass spectra from the given GNPS MGF file.

Concept

GNPS data

The file mappings file is from GNPS output archive, as described below for each GNPS workflow type:

  1. METABOLOMICS-SNETS
    • METABOLOMICS-SNETS*.mgf
  2. METABOLOMICS-SNETS-V2
    • METABOLOMICS-SNETS-V2*.mgf
  3. FEATURE-BASED-MOLECULAR-NETWORKING
    • spectra/*.mgf

Parameters:

Raises:

  • ValueError –

    Raises ValueError if the file is not valid.

Examples:

>>> loader = GNPSSpectrumLoader("gnps_spectra.mgf")
>>> print(loader.spectra[0])
Source code in src/nplinker/metabolomics/gnps/gnps_spectrum_loader.py 
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def __init__(self, file: str | PathLike) -> None:
    """Initialize the GNPSSpectrumLoader.

    Args:
        file: path to the MGF file.

    Raises:
        ValueError: Raises ValueError if the file is not valid.

    Examples:
        >>> loader = GNPSSpectrumLoader("gnps_spectra.mgf")
        >>> print(loader.spectra[0])
    """
    self._file = str(file)
    self._spectra: list[Spectrum] = []

    self._validate()
    self._load()

spectra property 

spectra: list[Spectrum]

Get the list of Spectrum objects.

Returns:

  • list[Spectrum] –

    list[Spectrum]: the loaded spectra as a list of Spectrum objects.

GNPSMolecularFamilyLoader 

GNPSMolecularFamilyLoader(file: str | PathLike)

Bases: MolecularFamilyLoaderBase

Load molecular families from GNPS data.

Concept

GNPS data

The molecular family file is from GNPS output archive, as described below for each GNPS workflow type:

  1. METABOLOMICS-SNETS
    • networkedges_selfloop/*.pairsinfo
  2. METABOLOMICS-SNETS-V2
    • networkedges_selfloop/*.selfloop
  3. FEATURE-BASED-MOLECULAR-NETWORKING
    • networkedges_selfloop/*.selfloop

The ComponentIndex column in the GNPS molecular family file is treated as family id.

But for molecular families that have only one member (i.e. spectrum), named singleton molecular families, their files have the same value of -1 in the ComponentIndex column. To make the family id unique,the spectrum id plus a prefix singleton- is used as the family id of singleton molecular families.

Parameters:

  • file (str | PathLike) –

    Path to the GNPS molecular family file.

Raises:

  • ValueError –

    Raises ValueError if the file is not valid.

Examples:

>>> loader = GNPSMolecularFamilyLoader("gnps_molecular_families.tsv")
>>> print(loader.families)
[<MolecularFamily 1>, <MolecularFamily 2>, ...]
>>> print(loader.families[0].spectra_ids)
{'1', '3', '7', ...}
Source code in src/nplinker/metabolomics/gnps/gnps_molecular_family_loader.py 
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def __init__(self, file: str | PathLike) -> None:
    """Initialize the GNPSMolecularFamilyLoader.

    Args:
        file: Path to the GNPS molecular family file.

    Raises:
        ValueError: Raises ValueError if the file is not valid.

    Examples:
        >>> loader = GNPSMolecularFamilyLoader("gnps_molecular_families.tsv")
        >>> print(loader.families)
        [<MolecularFamily 1>, <MolecularFamily 2>, ...]
        >>> print(loader.families[0].spectra_ids)
        {'1', '3', '7', ...}
    """
    self._mfs: list[MolecularFamily] = []
    self._file = file

    self._validate()
    self._load()

get_mfs 

get_mfs(
    keep_singleton: bool = False,
) -> list[MolecularFamily]

Get MolecularFamily objects.

Parameters:

  • keep_singleton (bool, default: False ) –

    True to keep singleton molecular families. A singleton molecular family is a molecular family that contains only one spectrum.

Returns:

Source code in src/nplinker/metabolomics/gnps/gnps_molecular_family_loader.py 
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def get_mfs(self, keep_singleton: bool = False) -> list[MolecularFamily]:
    """Get MolecularFamily objects.

    Args:
        keep_singleton: True to keep singleton molecular families. A
            singleton molecular family is a molecular family that contains
            only one spectrum.

    Returns:
        A list of MolecularFamily objects with their spectra ids.
    """
    mfs = self._mfs
    if not keep_singleton:
        mfs = [mf for mf in mfs if not mf.is_singleton()]
    return mfs

GNPSAnnotationLoader 

GNPSAnnotationLoader(file: str | PathLike)

Bases: AnnotationLoaderBase

Load annotations from GNPS output file.

Concept

GNPS data

The annotation file is a .tsv file from GNPS output archive, as described below for each GNPS workflow type:

  1. METABOLOMICS-SNETS
    • result_specnets_DB/*.tsv
  2. METABOLOMICS-SNETS-V2
    • result_specnets_DB/.tsv
  3. FEATURE-BASED-MOLECULAR-NETWORKING
    • DB_result/*.tsv

Parameters:

Examples:

>>> loader = GNPSAnnotationLoader("gnps_annotations.tsv")
>>> print(loader.annotations["100"])
{'#Scan#': '100',
'Adduct': 'M+H',
'CAS_Number': 'N/A',
'Charge': '1',
'Compound_Name': 'MLS002153841-01!Iobenguane sulfate',
'Compound_Source': 'NIH Pharmacologically Active Library',
'Data_Collector': 'VP/LMS',
'ExactMass': '274.992',
'INCHI': 'N/A',
'INCHI_AUX': 'N/A',
'Instrument': 'qTof',
'IonMode': 'Positive',
'Ion_Source': 'LC-ESI',
'LibMZ': '276.003',
'LibraryName': 'lib-00014.mgf',
'LibraryQualityString': 'Gold',
'Library_Class': '1',
'MQScore': '0.704152',
'MZErrorPPM': '405416',
'MassDiff': '111.896',
'Organism': 'GNPS-NIH-SMALLMOLECULEPHARMACOLOGICALLYACTIVE',
'PI': 'Dorrestein',
'Precursor_MZ': '276.003',
'Pubmed_ID': 'N/A',
'RT_Query': '795.979',
'SharedPeaks': '7',
'Smiles': 'NC(=N)NCc1cccc(I)c1.OS(=O)(=O)O',
'SpecCharge': '1',
'SpecMZ': '164.107',
'SpectrumFile': 'spectra/specs_ms.pklbin',
'SpectrumID': 'CCMSLIB00000086167',
'TIC_Query': '986.997',
'UpdateWorkflowName': 'UPDATE-SINGLE-ANNOTATED-GOLD',
'tags': ' ',
'png_url': 'https://metabolomics-usi.gnps2.org/png/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167',
'json_url': 'https://metabolomics-usi.gnps2.org/json/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167',
'svg_url': 'https://metabolomics-usi.gnps2.org/svg/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167',
'spectrum_url': 'https://metabolomics-usi.gnps2.org/spectrum/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167'}
Source code in src/nplinker/metabolomics/gnps/gnps_annotation_loader.py 
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def __init__(self, file: str | PathLike) -> None:
    """Initialize the GNPSAnnotationLoader.

    Args:
        file: The GNPS annotation file.

    Examples:
        >>> loader = GNPSAnnotationLoader("gnps_annotations.tsv")
        >>> print(loader.annotations["100"])
        {'#Scan#': '100',
        'Adduct': 'M+H',
        'CAS_Number': 'N/A',
        'Charge': '1',
        'Compound_Name': 'MLS002153841-01!Iobenguane sulfate',
        'Compound_Source': 'NIH Pharmacologically Active Library',
        'Data_Collector': 'VP/LMS',
        'ExactMass': '274.992',
        'INCHI': 'N/A',
        'INCHI_AUX': 'N/A',
        'Instrument': 'qTof',
        'IonMode': 'Positive',
        'Ion_Source': 'LC-ESI',
        'LibMZ': '276.003',
        'LibraryName': 'lib-00014.mgf',
        'LibraryQualityString': 'Gold',
        'Library_Class': '1',
        'MQScore': '0.704152',
        'MZErrorPPM': '405416',
        'MassDiff': '111.896',
        'Organism': 'GNPS-NIH-SMALLMOLECULEPHARMACOLOGICALLYACTIVE',
        'PI': 'Dorrestein',
        'Precursor_MZ': '276.003',
        'Pubmed_ID': 'N/A',
        'RT_Query': '795.979',
        'SharedPeaks': '7',
        'Smiles': 'NC(=N)NCc1cccc(I)c1.OS(=O)(=O)O',
        'SpecCharge': '1',
        'SpecMZ': '164.107',
        'SpectrumFile': 'spectra/specs_ms.pklbin',
        'SpectrumID': 'CCMSLIB00000086167',
        'TIC_Query': '986.997',
        'UpdateWorkflowName': 'UPDATE-SINGLE-ANNOTATED-GOLD',
        'tags': ' ',
        'png_url': 'https://metabolomics-usi.gnps2.org/png/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167',
        'json_url': 'https://metabolomics-usi.gnps2.org/json/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167',
        'svg_url': 'https://metabolomics-usi.gnps2.org/svg/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167',
        'spectrum_url': 'https://metabolomics-usi.gnps2.org/spectrum/?usi1=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000086167'}
    """
    self._file = Path(file)
    self._annotations: dict[str, dict] = {}

    self._validate()
    self._load()

annotations property 

annotations: dict[str, dict]

Get annotations.

Returns:

  • dict[str, dict] –

    Keys are spectrum ids ("#Scan#" in annotation file) and values are the annotations dict

  • dict[str, dict] –

    for each spectrum.

GNPSFileMappingLoader 

GNPSFileMappingLoader(file: str | PathLike)

Bases: FileMappingLoaderBase

Class to load file mappings from GNPS output file.

Concept

GNPS data

File mappings refers to the mapping from spectrum id to files in which this spectrum occurs.

The file mappings file is from GNPS output archive, as described below for each GNPS workflow type:

  1. METABOLOMICS-SNETS
    • clusterinfosummarygroup_attributes_withIDs_withcomponentID/*.tsv
  2. METABOLOMICS-SNETS-V2
    • clusterinfosummarygroup_attributes_withIDs_withcomponentID/*.clustersummary
  3. FEATURE-BASED-MOLECULAR-NETWORKING
    • quantification_table/.csv

Parameters:

  • file (str | PathLike) –

    Path to the GNPS file mappings file.

Raises:

  • ValueError –

    Raises ValueError if the file is not valid.

Examples:

>>> loader = GNPSFileMappingLoader("gnps_file_mappings.tsv")
>>> print(loader.mappings["1"])
['26c.mzXML']
>>> print(loader.mapping_reversed["26c.mzXML"])
{'1', '3', '7', ...}
Source code in src/nplinker/metabolomics/gnps/gnps_file_mapping_loader.py 
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def __init__(self, file: str | PathLike) -> None:
    """Initialize the GNPSFileMappingLoader.

    Args:
        file: Path to the GNPS file mappings file.

    Raises:
        ValueError: Raises ValueError if the file is not valid.

    Examples:
        >>> loader = GNPSFileMappingLoader("gnps_file_mappings.tsv")
        >>> print(loader.mappings["1"])
        ['26c.mzXML']
        >>> print(loader.mapping_reversed["26c.mzXML"])
        {'1', '3', '7', ...}
    """
    self._gnps_format = gnps_format_from_file_mapping(file)
    if self._gnps_format is GNPSFormat.Unknown:
        raise ValueError("Unknown workflow type for GNPS file mappings file ")

    self._file = Path(file)
    self._mapping: dict[str, list[str]] = {}

    self._validate()
    self._load()

mappings property 

mappings: dict[str, list[str]]

Return mapping from spectrum id to files in which this spectrum occurs.

Returns:

  • dict[str, list[str]] –

    Mapping from spectrum id to names of all files in which this spectrum occurs.

mapping_reversed property 

mapping_reversed: dict[str, set[str]]

Return mapping from file name to all spectra that occur in this file.

Returns:

  • dict[str, set[str]] –

    Mapping from file name to all spectra ids that occur in this file.

gnps_format_from_archive 

gnps_format_from_archive(
    zip_file: str | PathLike,
) -> GNPSFormat

Detect GNPS format from GNPS zip archive.

The detection is based on the filename of the zip file and the names of the files contained in the zip file.

Parameters:

  • zip_file (str | PathLike) –

    Path to the GNPS zip file.

Returns:

  • GNPSFormat –

    The format identified in the GNPS zip file.

Examples:

>>> gnps_format_from_archive("ProteoSAFe-METABOLOMICS-SNETS-c22f44b1-download_clustered_spectra.zip")
<GNPSFormat.SNETS: 'METABOLOMICS-SNETS'>
>>> gnps_format_from_archive("ProteoSAFe-METABOLOMICS-SNETS-V2-189e8bf1-download_clustered_spectra.zip")
<GNPSFormat.SNETSV2: 'METABOLOMICS-SNETS-V2'>
>>> gnps_format_from_archive("ProteoSAFe-FEATURE-BASED-MOLECULAR-NETWORKING-672d0a53-download_cytoscape_data.zip")
<GNPSFormat.FBMN: 'FEATURE-BASED-MOLECULAR-NETWORKING'>
Source code in src/nplinker/metabolomics/gnps/gnps_format.py 
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def gnps_format_from_archive(zip_file: str | PathLike) -> GNPSFormat:
    """Detect GNPS format from GNPS zip archive.

    The detection is based on the filename of the zip file and the names of the
    files contained in the zip file.

    Args:
        zip_file: Path to the GNPS zip file.

    Returns:
        The format identified in the GNPS zip file.

    Examples:
        >>> gnps_format_from_archive("ProteoSAFe-METABOLOMICS-SNETS-c22f44b1-download_clustered_spectra.zip")
        <GNPSFormat.SNETS: 'METABOLOMICS-SNETS'>
        >>> gnps_format_from_archive("ProteoSAFe-METABOLOMICS-SNETS-V2-189e8bf1-download_clustered_spectra.zip")
        <GNPSFormat.SNETSV2: 'METABOLOMICS-SNETS-V2'>
        >>> gnps_format_from_archive("ProteoSAFe-FEATURE-BASED-MOLECULAR-NETWORKING-672d0a53-download_cytoscape_data.zip")
        <GNPSFormat.FBMN: 'FEATURE-BASED-MOLECULAR-NETWORKING'>
    """
    file = Path(zip_file)
    # Guess the format from the filename of the zip file
    if GNPSFormat.FBMN.value in file.name:
        return GNPSFormat.FBMN
    # the order of the if statements matters for the following two
    if GNPSFormat.SNETSV2.value in file.name:
        return GNPSFormat.SNETSV2
    if GNPSFormat.SNETS.value in file.name:
        return GNPSFormat.SNETS

    # Guess the format from the names of the files in the zip file
    with zipfile.ZipFile(file) as archive:
        filenames = archive.namelist()
    if any(GNPSFormat.FBMN.value in x for x in filenames):
        return GNPSFormat.FBMN
    # the order of the if statements matters for the following two
    if any(GNPSFormat.SNETSV2.value in x for x in filenames):
        return GNPSFormat.SNETSV2
    if any(GNPSFormat.SNETS.value in x for x in filenames):
        return GNPSFormat.SNETS

    return GNPSFormat.Unknown

gnps_format_from_file_mapping 

gnps_format_from_file_mapping(
    file: str | PathLike,
) -> GNPSFormat

Detect GNPS format from the given file mapping file.

The GNPS file mapping file is located in different folders depending on the GNPS workflow. Here are the locations in corresponding GNPS zip archives:

  • METABOLOMICS-SNETS workflow: the .tsv file in the folder clusterinfosummarygroup_attributes_withIDs_withcomponentID
  • METABOLOMICS-SNETS-V2 workflow: the .clustersummary file (tsv) in the folder clusterinfosummarygroup_attributes_withIDs_withcomponentID
  • FEATURE-BASED-MOLECULAR-NETWORKING workflow: the .csv file in the folder quantification_table

Parameters:

  • file (str | PathLike) –

    Path to the file to peek the format for.

Returns:

  • GNPSFormat –

    GNPS format identified in the file.

Source code in src/nplinker/metabolomics/gnps/gnps_format.py 
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def gnps_format_from_file_mapping(file: str | PathLike) -> GNPSFormat:
    """Detect GNPS format from the given file mapping file.

    The GNPS file mapping file is located in different folders depending on the
    GNPS workflow. Here are the locations in corresponding GNPS zip archives:

    - `METABOLOMICS-SNETS` workflow: the `.tsv` file in the folder
        `clusterinfosummarygroup_attributes_withIDs_withcomponentID`
    - `METABOLOMICS-SNETS-V2` workflow: the `.clustersummary` file (tsv) in the folder
        `clusterinfosummarygroup_attributes_withIDs_withcomponentID`
    - `FEATURE-BASED-MOLECULAR-NETWORKING` workflow: the `.csv` file in the folder
        `quantification_table`

    Args:
        file: Path to the file to peek the format for.

    Returns:
        GNPS format identified in the file.
    """
    with open(file, "r") as f:
        header = f.readline().strip()

    if re.search(r"\bAllFiles\b", header):
        return GNPSFormat.SNETS
    if re.search(r"\bUniqueFileSources\b", header):
        return GNPSFormat.SNETSV2
    if re.search(r"\b{}\b".format(re.escape("row ID")), header):
        return GNPSFormat.FBMN
    return GNPSFormat.Unknown

gnps_format_from_task_id 

gnps_format_from_task_id(task_id: str) -> GNPSFormat

Detect GNPS format for the given task id.

Parameters:

  • task_id (str) –

    GNPS task id.

Returns:

  • GNPSFormat –

    The format identified in the GNPS task.

Examples:

>>> gnps_format_from_task_id("c22f44b14a3d450eb836d607cb9521bb")
<GNPSFormat.SNETS: 'METABOLOMICS-SNETS'>
>>> gnps_format_from_task_id("189e8bf16af145758b0a900f1c44ff4a")
<GNPSFormat.SNETSV2: 'METABOLOMICS-SNETS-V2'>
>>> gnps_format_from_task_id("92036537c21b44c29e509291e53f6382")
<GNPSFormat.FBMN: 'FEATURE-BASED-MOLECULAR-NETWORKING'>
>>> gnps_format_from_task_id("0ad6535e34d449788f297e712f43068a")
<GNPSFormat.Unknown: 'Unknown-GNPS-Workflow'>
Source code in src/nplinker/metabolomics/gnps/gnps_format.py 
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def gnps_format_from_task_id(task_id: str) -> GNPSFormat:
    """Detect GNPS format for the given task id.

    Args:
        task_id: GNPS task id.

    Returns:
        The format identified in the GNPS task.

    Examples:
        >>> gnps_format_from_task_id("c22f44b14a3d450eb836d607cb9521bb")
        <GNPSFormat.SNETS: 'METABOLOMICS-SNETS'>
        >>> gnps_format_from_task_id("189e8bf16af145758b0a900f1c44ff4a")
        <GNPSFormat.SNETSV2: 'METABOLOMICS-SNETS-V2'>
        >>> gnps_format_from_task_id("92036537c21b44c29e509291e53f6382")
        <GNPSFormat.FBMN: 'FEATURE-BASED-MOLECULAR-NETWORKING'>
        >>> gnps_format_from_task_id("0ad6535e34d449788f297e712f43068a")
        <GNPSFormat.Unknown: 'Unknown-GNPS-Workflow'>
    """
    task_html = httpx.get(GNPS_TASK_URL.format(task_id))
    soup = BeautifulSoup(task_html.text, features="html.parser")
    try:
        # find the td tag that follows the th tag containing 'Workflow'
        workflow_tag = soup.find("th", string="Workflow").find_next_sibling("td")  # type: ignore
        workflow_format = workflow_tag.contents[0].strip()  # type: ignore
    except AttributeError:
        return GNPSFormat.Unknown

    if workflow_format == GNPSFormat.FBMN.value:
        return GNPSFormat.FBMN
    if workflow_format == GNPSFormat.SNETSV2.value:
        return GNPSFormat.SNETSV2
    if workflow_format == GNPSFormat.SNETS.value:
        return GNPSFormat.SNETS
    return GNPSFormat.Unknown