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(==2.7.1)", "scikit-build (==0.11.1)", "scikit-build (==0.16.1)"] -tests-strict = ["codecov (==2.0.15)", "pytest (==4.6.0)", "pytest (==4.6.0)", "pytest (==6.2.5)", "pytest-cov (==3.0.0)", "typing (==3.7.4)"] +tests-strict = ["pytest (==4.6.0)", "pytest (==4.6.0)", "pytest (==6.2.5)", "pytest-cov (==3.0.0)", "typing (==3.7.4)"] [[package]] name = "zipp" @@ -3000,4 +3021,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8.0,<3.11.0" -content-hash = "5c60fd12a66022e2a593a7ce2d7e9b79171300c05ef479c9dbbdfb8216fb1e5a" +content-hash = "a3d0db1999319115215e03726a6051359ddc7775e0c5f7bd456fb99a64fad1a5" diff --git a/pyproject.toml b/pyproject.toml index 1ca1acd..09f8db8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,7 +30,7 @@ pymzml = "^2.5.0" pyteomics = "^4.3.3" lxml= '^4.5.2' tables = "^3.6.1" -spectrum-fundamentals = ">=0.4.3,<0.5.0" +spectrum-fundamentals = ">=0.4.4,<0.5.0" [tool.poetry.dev-dependencies] pytest = ">=6.2.3" diff --git a/spectrum_io/raw/msraw.py b/spectrum_io/raw/msraw.py index 1b1826c..578aca0 100644 --- a/spectrum_io/raw/msraw.py +++ b/spectrum_io/raw/msraw.py @@ -25,7 +25,7 @@ def check_analyzer(mass_analyzers: Dict[str, str]) -> Dict[str, str]: accession = mass_analyzers[elem] if accession in ["MS:1000079", "MS:1000484"]: # fourier transform ion cyclotron, orbitrap mass_analyzers[elem] = "FTMS" - elif accession in ["MS:1000082", "MS:1000264" "MS:1000078"]: # quadrupole ion-trap, ion-trap, linear ion-trap + elif accession in ["MS:1000082", "MS:1000264", "MS:1000078"]: # quadrupole ion-trap, ion-trap, linear ion-trap mass_analyzers[elem] = "ITMS" elif accession in ["MS:1000084"]: # TOF mass_analyzers[elem] = "TOF" @@ -135,43 +135,124 @@ def read_mzml( :return: pd.DataFrame with intensities and m/z values """ file_list = MSRaw.get_file_list(source, ext) - data = {} # type: Dict[str, Any] + if package == "pymzml": - with warnings.catch_warnings(): - warnings.filterwarnings("ignore", category=ImportWarning) - for file_path in file_list: - logger.info(f"Reading mzML file: {file_path}") - MSRaw._get_scans_pymzml(file_path, data, scanidx, *args, **kwargs) + data = MSRaw._read_mzml_pymzml(file_list, scanidx, *args, **kwargs) elif package == "pyteomics": + data = MSRaw._read_mzml_pyteomics(file_list, *args, **kwargs) + else: + raise AssertionError("Choose either 'pymzml' or 'pyteomics'") + + data["SCAN_NUMBER"] = pd.to_numeric(data["SCAN_NUMBER"]) + return data + + @staticmethod + def _read_mzml_pymzml(file_list: List[Path], scanidx: Optional[List] = None, *args, **kwargs) -> pd.DataFrame: + data_dict = {} + with warnings.catch_warnings(): + warnings.filterwarnings("ignore", category=ImportWarning) for file_path in file_list: - mass_analyzer = get_mass_analyzer(file_path) logger.info(f"Reading mzML file: {file_path}") - data_iter = mzml.read(source=str(file_path), *args, **kwargs) + data_iter = pymzml.run.Reader(file_path, args=args, kwargs=kwargs) file_name = file_path.stem - for spec in data_iter: - if spec["ms level"] != 1: # filter out ms1 spectra if there are any - spec_id = spec["id"].split("scan=")[-1] - instrument_configuration_ref = spec["scanList"]["scan"][0]["instrumentConfigurationRef"] - fragmentation = spec["scanList"]["scan"][0]["filter string"].split("@")[1][:3].upper() - mz_range = spec["scanList"]["scan"][0]["filter string"].split("[")[1][:-1] - rt = spec["scanList"]["scan"][0]["scan start time"] - key = f"{file_name}_{spec_id}" - data[key] = [ - file_name, - spec_id, - spec["intensity array"], - spec["m/z array"], - mz_range, - rt, - mass_analyzer[instrument_configuration_ref], - fragmentation, - ] + mass_analyzer = get_mass_analyzer(file_path) + namespace = "{http://psi.hupo.org/ms/mzml}" + + if scanidx is None: + spectra = data_iter + else: + # this does not work if some spectra are filtered out, e.g. mzML files with only MS2 spectra, see: + # https://github.com/pymzml/pymzML/blob/a883ff0e61fd97465b0a74667233ff594238e335/pymzml/file_classes + # /standardMzml.py#L81-L84 + spectra = (data_iter[idx] for idx in scanidx) + + for spec in spectra: + if spec.ms_level != 2: + continue # filter out ms1 spectra if there are any + key = f"{file_name}_{spec.ID}" + scan = spec.get_element_by_path(["scanList", "scan"])[0] + instrument_configuration_ref = scan.get("instrumentConfigurationRef", "") + activation = spec.get_element_by_path(["precursorList", "precursor", "activation"])[0] + fragmentation = "unknown" + collision_energy = 0.0 + for cv_param in activation: + name = cv_param.get("name") + if name == "collision energy": + collision_energy = float(cv_param.get("value")) + continue + if "beam-type" in name: + fragmentation = "HCD" + elif "collision-induced dissociation" in name: + fragmentation = "CID" + else: + fragmentation = name + scan_window = scan.find(f".//{namespace}scanWindow") + scan_lower_limit = float( + scan_window.find(f'./{namespace}cvParam[@accession="MS:1000501"]').get("value") + ) + scan_upper_limit = float( + scan_window.find(f'./{namespace}cvParam[@accession="MS:1000500"]').get("value") + ) + mz_range = f"{scan_lower_limit}-{scan_upper_limit}" + data_dict[key] = [ + file_name, + spec.ID, + spec.i, + spec.mz, + mz_range, + spec.scan_time_in_minutes(), + mass_analyzer.get(instrument_configuration_ref, "unknown"), + fragmentation, + collision_energy, + ] data_iter.close() - else: - raise AssertionError("Choose either 'pymzml' or 'pyteomics'") + data = pd.DataFrame.from_dict(data_dict, orient="index", columns=MZML_DATA_COLUMNS) + return data - data = pd.DataFrame.from_dict(data, orient="index", columns=MZML_DATA_COLUMNS) - data["SCAN_NUMBER"] = pd.to_numeric(data["SCAN_NUMBER"]) + @staticmethod + def _read_mzml_pyteomics(file_list: List[Path], *args, **kwargs) -> pd.DataFrame: + data_dict = {} + for file_path in file_list: + mass_analyzer = get_mass_analyzer(file_path) + logger.info(f"Reading mzML file: {file_path}") + data_iter = mzml.read(source=str(file_path), *args, **kwargs) + file_name = file_path.stem + for spec in data_iter: + if spec["ms level"] != 2: + continue # filter out ms1 spectra if there are any + spec_id = spec["id"].split("scan=")[-1] + scan = spec["scanList"]["scan"][0] + instrument_configuration_ref = scan.get("instrumentConfigurationRef", "") + activation = spec["precursorList"]["precursor"][0]["activation"] + fragmentation = "unknown" + collision_energy = 0.0 + for key, value in activation.items(): + if key == "collision energy": + collision_energy = value + elif "beam-type" in key: + fragmentation = "HCD" + elif "collision-induced dissociation" in key: + fragmentation = "CID" + else: + fragmentation = key + scan_lower_limit = scan["scanWindowList"]["scanWindow"][0]["scan window lower limit"] + scan_upper_limit = scan["scanWindowList"]["scanWindow"][0]["scan window upper limit"] + mz_range = f"{scan_lower_limit}-{scan_upper_limit}" + rt = spec["scanList"]["scan"][0]["scan start time"] + key = f"{file_name}_{spec_id}" + data_dict[key] = [ + file_name, + spec_id, + spec["intensity array"], + spec["m/z array"], + mz_range, + rt, + mass_analyzer.get(instrument_configuration_ref, "unknown"), + fragmentation, + collision_energy, + ] + data_iter.close() + data = pd.DataFrame.from_dict(data_dict, orient="index", columns=MZML_DATA_COLUMNS) return data @staticmethod @@ -206,62 +287,3 @@ def get_file_list(source: Union[str, Path, List[Union[str, Path]]], ext: str = " else: raise TypeError("source can only be a single str or Path or a list of files.") return file_list - - @staticmethod - def _get_scans_pymzml( - file_path: Union[str, Path], data: Dict, scanidx: Optional[List] = None, *args, **kwargs - ) -> None: - """ - Reads mzml and generates a dataframe containing intensities and m/z values. - - :param file_path: path to a single mzml file. - :param data: dictionary to be added to by this function - :param scanidx: optional list of scan numbers to extract. if not specified, all scans will be extracted - :param args: additional positional arguments - :param kwargs: additional keyword arguments - """ - if isinstance(file_path, str): - file_path = Path(file_path) - data_iter = pymzml.run.Reader(file_path, args=args, kwargs=kwargs) - file_name = file_path.stem - mass_analyzer = get_mass_analyzer(file_path) - if scanidx is None: - for spec in data_iter: - if spec.ms_level != 1: # filter out ms1 spectra if there are any - key = f"{file_name}_{spec.ID}" - instrument_configuration_ref = spec["scanList"]["scan"][0]["instrumentConfigurationRef"] - filter_string = str(spec.element.find(".//*[@accession='MS:1000512']").get("value")) - fragmentation = filter_string.split("@")[1][:3].upper() - mz_range = filter_string.split("[")[1][:-1] - data[key] = [ - file_name, - spec.ID, - spec.i, - spec.mz, - mz_range, - spec.scan_time_in_minutes(), - mass_analyzer[instrument_configuration_ref], - fragmentation, - ] - else: - for idx in scanidx: - spec = data_iter[idx] - # this does not work if some spectra are filtered out, e.g. mzML files with only MS2 spectra, see: - # https://github.com/pymzml/pymzML/blob/a883ff0e61fd97465b0a74667233ff594238e335/pymzml/file_classes - # /standardMzml.py#L81-L84 - key = f"{file_name}_{spec.ID}" - instrument_configuration_ref = spec["scanList"]["scan"][0]["instrumentConfigurationRef"] - filter_string = str(spec.element.find(".//*[@accession='MS:1000512']").get("value")) - fragmentation = filter_string.split("@")[1][:3].upper() - mz_range = filter_string.split("[")[1][:-1] - data[key] = [ - file_name, - spec.ID, - spec.i, - spec.mz, - mz_range, - spec.scan_time_in_minutes(), - mass_analyzer[instrument_configuration_ref], - fragmentation, - ] - data_iter.close() diff --git a/tests/unit_tests/data/testdf.pkl b/tests/unit_tests/data/testdf.pkl new file mode 100644 index 0000000..4da3f6a Binary files /dev/null and b/tests/unit_tests/data/testdf.pkl differ diff --git a/tests/unit_tests/test_msraw.py b/tests/unit_tests/test_msraw.py index c9f05ba..8f6dbe8 100644 --- a/tests/unit_tests/test_msraw.py +++ b/tests/unit_tests/test_msraw.py @@ -1,3 +1,4 @@ +import pickle import unittest from pathlib import Path @@ -8,16 +9,24 @@ import spectrum_io.raw.msraw as msraw +def _test_read_mzml(package: str): + source = Path(__file__).parent / "data/test.mzml" + + msraw_obj = msraw.MSRaw(source, source) + df = msraw_obj.read_mzml(source, package=package) + # pickle.dump(df, open(Path(__file__).parent / "data/testdf.pkl", "wb")) + + target_df = pickle.load(open(Path(__file__).parent / "data/testdf.pkl", "rb")) + pd.testing.assert_frame_equal(df, target_df) + + class TestMsraw(unittest.TestCase): """Class to test msraw.""" - def test_read_mzml(self): + def test_read_mzml_with_pyteomics(self): """Test read_mzml.""" - source = Path(__file__).parent / "data/test.mzml" - - msraw_obj = msraw.MSRaw(source, source) - df = msraw_obj.read_mzml(source) + _test_read_mzml(package="pyteomics") - self.assertIsInstance(df, pd.DataFrame) - self.assertEqual(df.shape[1], 8) - self.assertListEqual(list(df.columns), MZML_DATA_COLUMNS) + def test_read_mzml_with_pymzml(self): + """Test read_mzml.""" + _test_read_mzml(package="pymzml")