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add support for maldi prmpasef spectra to TdfSpectrum
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@gtluu
gtluu committed Jul 23, 2024
1 parent 7eb44a9 commit 6c58bb1
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Showing 3 changed files with 127 additions and 44 deletions.
2 changes: 1 addition & 1 deletion docsrc/source/conf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
project = 'pyTDFSDK'
copyright = '2024, Gordon T. Luu'
author = 'Gordon T. Luu'
release = '0.3.7'
release = '0.4.0'

# -- General configuration ---------------------------------------------------
# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
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167 changes: 125 additions & 42 deletions pyTDFSDK/classes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -465,11 +465,6 @@ def get_lcms_tdf_data(self):
elif int(frames_dict['ScanMode']) == 4 and int(frames_dict['MsMsType']) == 2:
framemsmsinfo_dict = self.tdf_data.analysis['FrameMsMsInfo'][self.tdf_data.analysis['FrameMsMsInfo']['Frame'] ==
self.frame].to_dict(orient='records')[0]
self.scan_type = 'MSn spectrum'
self.ms_level = 2
self.activation = 'collision-induced dissociation'
self.collision_energy = float(framemsmsinfo_dict['CollisionEnergy'])
self.ms2_no_precursor = True
if not self.exclude_mobility:
self.mz_array, self.intensity_array, self.mobility_array = extract_3d_tdf_spectrum(self.tdf_data,
self.frame,
Expand All @@ -487,6 +482,11 @@ def get_lcms_tdf_data(self):
if self.mz_array is not None and self.intensity_array is not None and \
self.mz_array.size != 0 and self.intensity_array.size != 0 and \
self.mz_array.size == self.intensity_array.size:
self.scan_type = 'MSn spectrum'
self.ms_level = 2
self.activation = 'collision-induced dissociation'
self.collision_energy = float(framemsmsinfo_dict['CollisionEnergy'])
self.ms2_no_precursor = True
self.total_ion_current = sum(self.intensity_array)
base_peak_index = np.where(self.intensity_array == np.max(self.intensity_array))
self.base_peak_mz = self.mz_array[base_peak_index][0].astype(float)
Expand Down Expand Up @@ -618,43 +618,59 @@ def get_maldi_tdf_data(self):
self.polarity = frames_dict['Polarity']
self.centroided = get_centroid_status(self.mode)[0]
self.retention_time = 0
if not self.exclude_mobility:
self.mz_array, self.intensity_array, self.mobility_array = extract_3d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict[
'NumScans']))
elif self.exclude_mobility:
self.mz_array, self.intensity_array = extract_2d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict['NumScans']),
self.mode,
self.profile_bins,
self.mz_encoding,
self.intensity_encoding)
if self.mz_array is not None and self.intensity_array is not None and \
self.mz_array.size != 0 and self.intensity_array.size != 0 and \
self.mz_array.size == self.intensity_array.size:
self.total_ion_current = sum(self.intensity_array)
base_peak_index = np.where(self.intensity_array == np.max(self.intensity_array))
self.base_peak_mz = self.mz_array[base_peak_index][0].astype(float)
self.base_peak_intensity = self.intensity_array[base_peak_index][0].astype(float)
self.high_mz = float(max(self.mz_array))
self.low_mz = float(min(self.mz_array))
# MS1
if int(frames_dict['MsMsType']) == 0:
self.scan_type = 'MS1 spectrum'
self.ms_level = 1
elif int(frames_dict['MsMsType']) in [2, 8, 9]:
msms_mode_id = self.tdf_data.analysis['PropertyDefinitions'][self.tdf_data.analysis['PropertyDefinitions']['PermanentName'] ==
'Mode_ScanMode'].to_dict(orient='records')[0]['Id']
msms_mode = self.tdf_data.analysis['Properties'][(self.tdf_data.analysis['Properties']['Frame'] == self.frame) &
(self.tdf_data.analysis['Properties']['Property'] == msms_mode_id)].to_dict(orient='records')[0]['Value']
# MS1
if int(frames_dict['MsMsType']) == 0:
self.scan_type = 'MS1 spectrum'
self.ms_level = 1
if not self.exclude_mobility:
self.mz_array, self.intensity_array, self.mobility_array = extract_3d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict['NumScans']))
elif self.exclude_mobility:
self.mz_array, self.intensity_array = extract_2d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict['NumScans']),
self.mode,
self.profile_bins,
self.mz_encoding,
self.intensity_encoding)
if self.mz_array is not None and self.intensity_array is not None and \
self.mz_array.size != 0 and self.intensity_array.size != 0 and \
self.mz_array.size == self.intensity_array.size:
self.total_ion_current = sum(self.intensity_array)
base_peak_index = np.where(self.intensity_array == np.max(self.intensity_array))
self.base_peak_mz = self.mz_array[base_peak_index][0].astype(float)
self.base_peak_intensity = self.intensity_array[base_peak_index][0].astype(float)
self.high_mz = float(max(self.mz_array))
self.low_mz = float(min(self.mz_array))
elif int(frames_dict['MsMsType']) in [2, 8, 9]:
msms_mode_id = self.tdf_data.analysis['PropertyDefinitions'][self.tdf_data.analysis['PropertyDefinitions']['PermanentName'] ==
'Mode_ScanMode'].to_dict(orient='records')[0]['Id']
msms_mode = self.tdf_data.analysis['Properties'][(self.tdf_data.analysis['Properties']['Frame'] == self.frame) &
(self.tdf_data.analysis['Properties']['Property'] == msms_mode_id)].to_dict(orient='records')[0]['Value']
# MALDI MS/MS, coded as MRM in the schema
if msms_mode == 3:
framemsmsinfo_dict = self.tdf_data.analysis['FrameMsMsInfo'][self.tdf_data.analysis['FrameMsMsInfo']['Frame'] ==
maldiframeinfo_dict['Frame']].to_dict(orient='records')[0]
# MALDI MS/MS, coded as MRM in the schema
if msms_mode == 3:
if not self.exclude_mobility:
self.mz_array, self.intensity_array, self.mobility_array = extract_3d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict['NumScans']))
elif self.exclude_mobility:
self.mz_array, self.intensity_array = extract_2d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict['NumScans']),
self.mode,
self.profile_bins,
self.mz_encoding,
self.intensity_encoding)
if self.mz_array is not None and self.intensity_array is not None and \
self.mz_array.size != 0 and self.intensity_array.size != 0 and \
self.mz_array.size == self.intensity_array.size:
self.scan_type = 'MSn spectrum'
self.ms_level = 2
self.target_mz = float(framemsmsinfo_dict['TriggerMass'])
Expand All @@ -664,10 +680,77 @@ def get_maldi_tdf_data(self):
self.charge_state = framemsmsinfo_dict['PrecursorCharge']
self.activation = 'collision-induced dissociation'
self.collision_energy = float(framemsmsinfo_dict['CollisionEnergy'])
# MALDI bbCID
elif msms_mode == 5:
self.total_ion_current = sum(self.intensity_array)
base_peak_index = np.where(self.intensity_array == np.max(self.intensity_array))
self.base_peak_mz = self.mz_array[base_peak_index][0].astype(float)
self.base_peak_intensity = self.intensity_array[base_peak_index][0].astype(float)
self.high_mz = float(max(self.mz_array))
self.low_mz = float(min(self.mz_array))
# MALDI bbCID
elif msms_mode == 5:
framemsmsinfo_dict = self.tdf_data.analysis['FrameMsMsInfo'][self.tdf_data.analysis['FrameMsMsInfo']['Frame'] ==
maldiframeinfo_dict['Frame']].to_dict(orient='records')[0]
if not self.exclude_mobility:
self.mz_array, self.intensity_array, self.mobility_array = extract_3d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict['NumScans']))
elif self.exclude_mobility:
self.mz_array, self.intensity_array = extract_2d_tdf_spectrum(self.tdf_data,
self.frame,
0,
int(frames_dict['NumScans']),
self.mode,
self.profile_bins,
self.mz_encoding,
self.intensity_encoding)
if self.mz_array is not None and self.intensity_array is not None and \
self.mz_array.size != 0 and self.intensity_array.size != 0 and \
self.mz_array.size == self.intensity_array.size:
self.scan_type = 'MSn spectrum'
self.ms_level = 2
self.activation = 'collision-induced dissociation'
self.collision_energy = float(framemsmsinfo_dict['CollisionEnergy'])
self.ms2_no_precursor = True
self.total_ion_current = sum(self.intensity_array)
base_peak_index = np.where(self.intensity_array == np.max(self.intensity_array))
self.base_peak_mz = self.mz_array[base_peak_index][0].astype(float)
self.base_peak_intensity = self.intensity_array[base_peak_index][0].astype(float)
self.high_mz = float(max(self.mz_array))
self.low_mz = float(min(self.mz_array))
# MALDI prmPASEF
elif msms_mode == 12:
if self.diapasef_window is not None:
if not self.exclude_mobility:
self.mz_array, self.intensity_array, self.mobility_array = extract_3d_tdf_spectrum(self.tdf_data,
self.frame,
int(self.diapasef_window['ScanNumBegin']),
int(self.diapasef_window['ScanNumEnd']))
elif self.exclude_mobility:
self.mz_array, self.intensity_array = extract_2d_tdf_spectrum(self.tdf_data,
self.frame,
int(self.diapasef_window['ScanNumBegin']),
int(self.diapasef_window['ScanNumEnd']),
self.mode,
self.profile_bins,
self.mz_encoding,
self.intensity_encoding)
if self.mz_array is not None and self.intensity_array is not None and \
self.mz_array.size != 0 and self.intensity_array.size != 0 and \
self.mz_array.size == self.intensity_array.size:
self.scan_type = 'MSn spectrum'
self.ms_level = 2
self.target_mz = float(self.diapasef_window['IsolationMz'])
self.isolation_lower_offset = float(self.diapasef_window['IsolationWidth']) / 2
self.isolation_upper_offset = float(self.diapasef_window['IsolationWidth']) / 2
self.selected_ion_mz = float(self.diapasef_window['IsolationMz'])
self.collision_energy = self.diapasef_window['CollisionEnergy']
self.total_ion_current = sum(self.intensity_array)
base_peak_index = np.where(self.intensity_array == np.max(self.intensity_array))
self.base_peak_mz = self.mz_array[base_peak_index][0].astype(float)
self.base_peak_intensity = self.intensity_array[base_peak_index][0].astype(float)
self.high_mz = float(max(self.mz_array))
self.low_mz = float(min(self.mz_array))
else:
raise Exception("diapasef_window from TdfData.analysis['DiaFrameMsMsWindows'] table required to "
"parse diaPASEF data.")
2 changes: 1 addition & 1 deletion setup.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
from setuptools import setup

setup(name='pyTDFSDK',
version='0.3.10',
version='0.4.0',
description='Python wrapper for Bruker TDF-SDK',
url='https://github.com/gtluu/pyTDFSDK',
author='Gordon T. Luu',
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