def main():
input_result_filename = sys.argv[1]
output_result_filename = sys.argv[2]
spectrum_id_cache = {}
input_rows, input_table = ming_fileio_library.parse_table_with_headers(input_result_filename)
output_table = defaultdict(list)
output_headers = ["SpectrumID", "Compound_Name", "Ion_Source", "Instrument", "Compound_Source", "PI", "Data_Collector", "Adduct"]
output_headers += ["Precursor_MZ", "ExactMass", "Charge", "CAS_Number", "Pubmed_ID", "Smiles", "INCHI", "INCHI_AUX", "Library_Class"]
output_headers += ["IonMode", "UpdateWorkflowName", "LibraryQualityString", "#Scan#", "SpectrumFile", "MQScore", "Organism"]
output_headers += ["TIC_Query", "RT_Query", "MZErrorPPM", "SharedPeaks", "MassDiff", "LibMZ", "SpecMZ", "SpecCharge"]
output_headers += ["MoleculeExplorerDatasets", "MoleculeExplorerFiles"]
for header in output_headers:
output_table[header] = []
number_hits_per_query = defaultdict(lambda: 0)
for i in range(input_rows):
number_hits_per_query[input_table["FileScanUniqueID"][i]] += 1
molecule_explorer_df = pd.DataFrame(ming_gnps_library.get_molecule_explorer_dataset_data())
for i in range(input_rows):
spectrum_id = input_table["LibrarySpectrumID"][i]
score = input_table["MQScore"][i]
filename = input_table["SpectrumFile"][i]
libfilename = input_table["LibraryName"][i]
scan = input_table["#Scan#"][i]
TIC_Query = input_table["UnstrictEvelopeScore"][i]
RT_Query = input_table["p-value"][i]
SpecCharge = input_table["Charge"][i]
SpecMZ = input_table["SpecMZ"][i]
MZErrorPPM = input_table["mzErrorPPM"][i]
SharedPeaks = input_table["LibSearchSharedPeaks"][i]
MassDiff = input_table["ParentMassDiff"][i]
print(spectrum_id)
gnps_library_spectrum = None
try:
gnps_library_spectrum = None
if spectrum_id in spectrum_id_cache:
gnps_library_spectrum = spectrum_id_cache[spectrum_id]
else:
gnps_library_spectrum = ming_gnps_library.get_library_spectrum(spectrum_id)
spectrum_id_cache[spectrum_id] = gnps_library_spectrum
except KeyboardInterrupt:
raise
except:
continue
gnps_library_spectrum["annotations"] = sorted(gnps_library_spectrum["annotations"], key=lambda annotation: annotation["create_time"], reverse=True)
output_table["SpectrumID"].append(spectrum_id)
output_table["Compound_Name"].append(gnps_library_spectrum["annotations"][0]["Compound_Name"].replace("\t", ""))
output_table["Ion_Source"].append(gnps_library_spectrum["annotations"][0]["Ion_Source"].replace("\t", ""))
output_table["Instrument"].append(gnps_library_spectrum["annotations"][0]["Instrument"].replace("\t", ""))
output_table["Compound_Source"].append(gnps_library_spectrum["annotations"][0]["Compound_Source"].replace("\t", ""))
output_table["PI"].append(gnps_library_spectrum["annotations"][0]["PI"].replace("\t", ""))
output_table["Data_Collector"].append(gnps_library_spectrum["annotations"][0]["Data_Collector"].replace("\t", ""))
output_table["Adduct"].append(gnps_library_spectrum["annotations"][0]["Adduct"].replace("\t", ""))
output_table["Precursor_MZ"].append(gnps_library_spectrum["annotations"][0]["Precursor_MZ"].replace("\t", ""))
output_table["ExactMass"].append(gnps_library_spectrum["annotations"][0]["ExactMass"].replace("\t", ""))
output_table["Charge"].append(gnps_library_spectrum["annotations"][0]["Charge"].replace("\t", ""))
output_table["CAS_Number"].append(gnps_library_spectrum["annotations"][0]["CAS_Number"].replace("\t", ""))
output_table["Pubmed_ID"].append(gnps_library_spectrum["annotations"][0]["Pubmed_ID"].replace("\t", ""))
output_table["Smiles"].append(gnps_library_spectrum["annotations"][0]["Smiles"].replace("\t", ""))
output_table["INCHI"].append(gnps_library_spectrum["annotations"][0]["INCHI"].replace("\t", ""))
output_table["INCHI_AUX"].append(gnps_library_spectrum["annotations"][0]["INCHI_AUX"].replace("\t", ""))
output_table["Library_Class"].append(gnps_library_spectrum["annotations"][0]["Library_Class"].replace("\t", ""))
output_table["IonMode"].append(gnps_library_spectrum["annotations"][0]["Ion_Mode"].replace("\t", ""))
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "1":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-GOLD")
output_table["LibraryQualityString"].append("Gold")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "2":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-SILVER")
output_table["LibraryQualityString"].append("Silver")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "3":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Bronze")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "4":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Insilico")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "5":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Insilico")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "10":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Challenge")
else:
print("BULLLSHIT", gnps_library_spectrum["annotations"][0]["Library_Class"])
output_table["#Scan#"].append(scan)
output_table["SpectrumFile"].append(filename)
output_table["LibraryName"].append(libfilename)
output_table["MQScore"].append(score)
output_table["Organism"].append(gnps_library_spectrum["spectruminfo"]["library_membership"])
output_table["TIC_Query"].append(TIC_Query)
output_table["RT_Query"].append(RT_Query)
output_table["MZErrorPPM"].append(MZErrorPPM)
output_table["SharedPeaks"].append(SharedPeaks)
output_table["MassDiff"].append(MassDiff)
output_table["LibMZ"].append(gnps_library_spectrum["annotations"][0]["Precursor_MZ"])
output_table["SpecMZ"].append(SpecMZ)
output_table["SpecCharge"].append(SpecCharge)
output_table["FileScanUniqueID"].append(input_table["FileScanUniqueID"][i])
output_table["NumberHits"].append(number_hits_per_query[input_table["FileScanUniqueID"][i]])
tag_list = [ (tag["tag_desc"] + "[" + tag["tag_type"] + "]") for tag in gnps_library_spectrum["spectrum_tags"]]
tag_string = "||".join(tag_list).replace("\t", "")
output_table["tags"].append(tag_string)
#Getting molecule explorer information
compound_name = gnps_library_spectrum["annotations"][0]["Compound_Name"].replace("\t", "")
compound_filtered_df = molecule_explorer_df[molecule_explorer_df["compound_name"] == compound_name]
if len(compound_filtered_df) == 1:
output_table["MoleculeExplorerDatasets"].append(compound_filtered_df.to_dict(orient="records")[0]["number_datasets"])
output_table["MoleculeExplorerFiles"].append(compound_filtered_df.to_dict(orient="records")[0]["number_files"])
else:
output_table["MoleculeExplorerDatasets"].append(0)
output_table["MoleculeExplorerFiles"].append(0)
ming_fileio_library.write_dictionary_table_data(output_table, output_result_filename)
def enrich_output(input_filename, output_filename, topk=None):
spectrum_id_cache = {}
molecule_explorer_df = pd.DataFrame(
ming_gnps_library.get_molecule_explorer_dataset_data())
input_results_df = pd.read_csv(input_filename, sep="\t")
# Here we will try to filter to topk
if topk is not None:
try:
input_results_df["MQScore"] = input_results_df["MQScore"].astype(
float)
input_results_df = input_results_df.sort_values("MQScore",
ascending=False)
input_results_df = input_results_df.groupby(
'FileScanUniqueID').head(topk).reset_index(drop=True)
except:
pass
# Counting number of hits per filename
number_hits_per_query = defaultdict(lambda: 0)
for result_obj in input_results_df.to_dict(orient="records"):
number_hits_per_query[result_obj["FileScanUniqueID"]] += 1
output_list = []
for result_obj in tqdm(input_results_df.to_dict(orient="records")):
# Reading exsting data
spectrum_id = result_obj["LibrarySpectrumID"]
score = result_obj["MQScore"]
filename = result_obj["SpectrumFile"]
libfilename = result_obj["LibraryName"]
scan = result_obj["#Scan#"]
TIC_Query = result_obj["UnstrictEvelopeScore"]
RT_Query = result_obj["p-value"]
SpecCharge = result_obj["Charge"]
SpecMZ = result_obj["SpecMZ"]
MZErrorPPM = result_obj["mzErrorPPM"]
SharedPeaks = result_obj["LibSearchSharedPeaks"]
MassDiff = result_obj["ParentMassDiff"]
print(spectrum_id)
gnps_library_spectrum = None
try:
gnps_library_spectrum = None
if spectrum_id in spectrum_id_cache:
gnps_library_spectrum = spectrum_id_cache[spectrum_id]
else:
gnps_library_spectrum = ming_gnps_library.get_library_spectrum(
spectrum_id)
spectrum_id_cache[spectrum_id] = gnps_library_spectrum
#Making sure not an error
gnps_library_spectrum["annotations"][0]["Compound_Name"]
except KeyboardInterrupt:
raise
except:
continue
output_result_dict = {}
output_result_dict["SpectrumID"] = (spectrum_id)
output_result_dict["Compound_Name"] = (
gnps_library_spectrum["annotations"][0]["Compound_Name"].replace(
"\t", ""))
output_result_dict["Ion_Source"] = (
gnps_library_spectrum["annotations"][0]["Ion_Source"].replace(
"\t", ""))
output_result_dict["Instrument"] = (
gnps_library_spectrum["annotations"][0]["Instrument"].replace(
"\t", ""))
output_result_dict["Compound_Source"] = (
gnps_library_spectrum["annotations"][0]["Compound_Source"].replace(
"\t", ""))
output_result_dict["PI"] = (
gnps_library_spectrum["annotations"][0]["PI"].replace("\t", ""))
output_result_dict["Data_Collector"] = (
gnps_library_spectrum["annotations"][0]["Data_Collector"].replace(
"\t", ""))
output_result_dict["Adduct"] = (
gnps_library_spectrum["annotations"][0]["Adduct"].replace(
"\t", ""))
output_result_dict["Precursor_MZ"] = (
gnps_library_spectrum["annotations"][0]["Precursor_MZ"].replace(
"\t", ""))
output_result_dict["ExactMass"] = (
gnps_library_spectrum["annotations"][0]["ExactMass"].replace(
"\t", ""))
output_result_dict["Charge"] = (
gnps_library_spectrum["annotations"][0]["Charge"].replace(
"\t", ""))
output_result_dict["CAS_Number"] = (
gnps_library_spectrum["annotations"][0]["CAS_Number"].replace(
"\t", ""))
output_result_dict["Pubmed_ID"] = (
gnps_library_spectrum["annotations"][0]["Pubmed_ID"].replace(
"\t", ""))
output_result_dict["Smiles"] = (
gnps_library_spectrum["annotations"][0]["Smiles"].replace(
"\t", ""))
output_result_dict["INCHI"] = (
gnps_library_spectrum["annotations"][0]["INCHI"].replace("\t", ""))
output_result_dict["INCHI_AUX"] = (
gnps_library_spectrum["annotations"][0]["INCHI_AUX"].replace(
"\t", ""))
output_result_dict["Library_Class"] = (
gnps_library_spectrum["annotations"][0]["Library_Class"].replace(
"\t", ""))
output_result_dict["IonMode"] = (
gnps_library_spectrum["annotations"][0]["Ion_Mode"].replace(
"\t", ""))
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "1":
output_result_dict["UpdateWorkflowName"] = (
"UPDATE-SINGLE-ANNOTATED-GOLD")
output_result_dict["LibraryQualityString"] = ("Gold")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "2":
output_result_dict["UpdateWorkflowName"] = (
"UPDATE-SINGLE-ANNOTATED-SILVER")
output_result_dict["LibraryQualityString"] = ("Silver")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "3":
output_result_dict["UpdateWorkflowName"] = (
"UPDATE-SINGLE-ANNOTATED-BRONZE")
output_result_dict["LibraryQualityString"] = ("Bronze")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "4":
output_result_dict["UpdateWorkflowName"] = (
"UPDATE-SINGLE-ANNOTATED-BRONZE")
output_result_dict["LibraryQualityString"] = ("Insilico")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "5":
output_result_dict["UpdateWorkflowName"] = (
"UPDATE-SINGLE-ANNOTATED-BRONZE")
output_result_dict["LibraryQualityString"] = ("Insilico")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "10":
output_result_dict["UpdateWorkflowName"] = (
"UPDATE-SINGLE-ANNOTATED-BRONZE")
output_result_dict["LibraryQualityString"] = ("Challenge")
else:
print("Invalid Library Class",
gnps_library_spectrum["annotations"][0]["Library_Class"])
output_result_dict["#Scan#"] = (scan)
output_result_dict["SpectrumFile"] = (filename)
output_result_dict["LibraryName"] = (libfilename)
output_result_dict["MQScore"] = (score)
output_result_dict["Organism"] = (
gnps_library_spectrum["spectruminfo"]["library_membership"])
output_result_dict["TIC_Query"] = (TIC_Query)
output_result_dict["RT_Query"] = (RT_Query)
output_result_dict["MZErrorPPM"] = (MZErrorPPM)
output_result_dict["SharedPeaks"] = (SharedPeaks)
output_result_dict["MassDiff"] = (MassDiff)
output_result_dict["LibMZ"] = (
gnps_library_spectrum["annotations"][0]["Precursor_MZ"])
output_result_dict["SpecMZ"] = (SpecMZ)
output_result_dict["SpecCharge"] = (SpecCharge)
output_result_dict["FileScanUniqueID"] = (
result_obj["FileScanUniqueID"])
output_result_dict["NumberHits"] = (
number_hits_per_query[result_obj["FileScanUniqueID"]])
if "full_CCMS_path" in result_obj:
output_result_dict["full_CCMS_path"] = (
result_obj["full_CCMS_path"])
tag_list = [(tag["tag_desc"] + "[" + tag["tag_type"] + "]")
for tag in gnps_library_spectrum["spectrum_tags"]]
tag_string = "||".join(tag_list).replace("\t", "")
output_result_dict["tags"] = (tag_string)
#Getting molecule explorer information
compound_name = gnps_library_spectrum["annotations"][0][
"Compound_Name"].replace("\t", "")
compound_filtered_df = molecule_explorer_df[
molecule_explorer_df["compound_name"] == compound_name]
if len(compound_filtered_df) == 1:
output_result_dict["MoleculeExplorerDatasets"] = (
compound_filtered_df.to_dict(
orient="records")[0]["number_datasets"])
output_result_dict["MoleculeExplorerFiles"] = (
compound_filtered_df.to_dict(
orient="records")[0]["number_files"])
else:
output_result_dict["MoleculeExplorerDatasets"] = (0)
output_result_dict["MoleculeExplorerFiles"] = (0)
# Calculating inchi
if len(output_result_dict["Smiles"]) > 5 and len(
output_result_dict["INCHI"]) < 5:
try:
inchi_url = "https://gnps-structure.ucsd.edu/inchi?smiles={}".format(
urllib.parse.quote_plus(output_result_dict["Smiles"]),
urllib.parse.quote_plus(output_result_dict["INCHI"]))
r = requests.get(inchi_url)
r.raise_for_status()
output_result_dict["INCHI"] = r.text
except:
output_result_dict["INCHI"] = "N/A"
# Calculating smiles
if len(output_result_dict["Smiles"]) < 5 and len(
output_result_dict["INCHI"]) > 5:
try:
smiles_url = "https://gnps-structure.ucsd.edu/smiles?inchi={}".format(
urllib.parse.quote_plus(output_result_dict["INCHI"]),
urllib.parse.quote_plus(output_result_dict["Smiles"]))
r = requests.get(smiles_url)
r.raise_for_status()
output_result_dict["Smiles"] = r.text
except:
output_result_dict["Smiles"] = "N/A"
# Calculating molecular formula
if len(output_result_dict["Smiles"]) > 5:
try:
formula_url = "https://gnps-structure.ucsd.edu/formula?smiles={}".format(
output_result_dict["Smiles"])
r = requests.get(formula_url)
r.raise_for_status()
output_result_dict["molecular_formula"] = r.text
except:
output_result_dict["molecular_formula"] = "N/A"
else:
output_result_dict["molecular_formula"] = "N/A"
# Calculating inchi key
if len(output_result_dict["Smiles"]) < 5 and len(
output_result_dict["INCHI"]) < 5:
output_result_dict["InChIKey"] = "N/A"
output_result_dict["InChIKey-Planar"] = "N/A"
else:
try:
inchikey_url = "https://gnps-structure.ucsd.edu/inchikey?smiles={}&inchi={}".format(
urllib.parse.quote_plus(output_result_dict["Smiles"]),
urllib.parse.quote_plus(output_result_dict["INCHI"]))
r = requests.get(inchikey_url)
r.raise_for_status()
output_result_dict["InChIKey"] = r.text
output_result_dict["InChIKey-Planar"] = r.text.split("-")[0]
except:
output_result_dict["InChIKey"] = "N/A"
output_result_dict["InChIKey-Planar"] = "N/A"
# Getting Classyfire
if len(output_result_dict["InChIKey"]) > 5:
try:
classyfire_url = "https://gnps-classyfire.ucsd.edu/entities/{}.json".format(
output_result_dict["InChIKey"])
r = requests.get(classyfire_url, timeout=10)
r.raise_for_status()
classification_json = r.json()
output_result_dict["superclass"] = classification_json[
"superclass"]["name"]
output_result_dict["class"] = classification_json["class"][
"name"]
output_result_dict["subclass"] = classification_json[
"subclass"]["name"]
except:
output_result_dict["superclass"] = "N/A"
output_result_dict["class"] = "N/A"
output_result_dict["subclass"] = "N/A"
else:
output_result_dict["superclass"] = "N/A"
output_result_dict["class"] = "N/A"
output_result_dict["subclass"] = "N/A"
# Getting NP Classifier
if len(output_result_dict["Smiles"]) > 5:
try:
npclassifier_url = "https://npclassifier.ucsd.edu/classify?smiles={}".format(
output_result_dict["Smiles"])
r = requests.get(npclassifier_url, timeout=10)
r.raise_for_status()
classification_json = r.json()
output_result_dict["npclassifier_superclass"] = "|".join(
classification_json["superclass_results"])
output_result_dict["npclassifier_class"] = "|".join(
classification_json["class_results"])
output_result_dict["npclassifier_pathway"] = "|".join(
classification_json["pathway_results"])
except:
output_result_dict["npclassifier_superclass"] = "N/A"
output_result_dict["npclassifier_class"] = "N/A"
output_result_dict["npclassifier_pathway"] = "N/A"
else:
output_result_dict["npclassifier_superclass"] = "N/A"
output_result_dict["npclassifier_class"] = "N/A"
output_result_dict["npclassifier_pathway"] = "N/A"
output_list.append(output_result_dict)
pd.DataFrame(output_list).to_csv(output_filename, sep="\t", index=False)
def main():
input_result_filename = sys.argv[1]
output_result_filename = sys.argv[2]
spectrum_id_cache = {}
input_rows, input_table = ming_fileio_library.parse_table_with_headers(input_result_filename)
output_table = defaultdict(list)
output_headers = ["SpectrumID", "Compound_Name", "Ion_Source", "Instrument", "Compound_Source", "PI", "Data_Collector", "Adduct"]
output_headers += ["Precursor_MZ", "ExactMass", "Charge", "CAS_Number", "Pubmed_ID", "Smiles", "INCHI", "INCHI_AUX", "Library_Class"]
output_headers += ["IonMode", "UpdateWorkflowName", "LibraryQualityString", "#Scan#", "SpectrumFile", "MQScore", "Organism"]
output_headers += ["TIC_Query", "RT_Query", "MZErrorPPM", "SharedPeaks", "MassDiff", "LibMZ", "SpecMZ", "SpecCharge"]
for header in output_headers:
output_table[header] = []
number_hits_per_query = defaultdict(lambda: 0)
for i in range(input_rows):
number_hits_per_query[input_table["FileScanUniqueID"][i]] += 1
for i in range(input_rows):
spectrum_id = input_table["LibrarySpectrumID"][i]
score = input_table["MQScore"][i]
filename = input_table["SpectrumFile"][i]
libfilename = input_table["LibraryName"][i]
scan = input_table["#Scan#"][i]
TIC_Query = input_table["UnstrictEvelopeScore"][i]
RT_Query = input_table["p-value"][i]
SpecCharge = input_table["Charge"][i]
SpecMZ = input_table["SpecMZ"][i]
MZErrorPPM = input_table["mzErrorPPM"][i]
SharedPeaks = input_table["LibSearchSharedPeaks"][i]
MassDiff = input_table["ParentMassDiff"][i]
print(spectrum_id)
gnps_library_spectrum = None
try:
gnps_library_spectrum = None
if spectrum_id in spectrum_id_cache:
gnps_library_spectrum = spectrum_id_cache[spectrum_id]
else:
gnps_library_spectrum = ming_gnps_library.get_library_spectrum(spectrum_id)
spectrum_id_cache[spectrum_id] = gnps_library_spectrum
except KeyboardInterrupt:
raise
except:
continue
gnps_library_spectrum["annotations"] = sorted(gnps_library_spectrum["annotations"], key=lambda annotation: annotation["create_time"], reverse=True)
output_table["SpectrumID"].append(spectrum_id)
output_table["Compound_Name"].append(gnps_library_spectrum["annotations"][0]["Compound_Name"].replace("\t", ""))
output_table["Ion_Source"].append(gnps_library_spectrum["annotations"][0]["Ion_Source"].replace("\t", ""))
output_table["Instrument"].append(gnps_library_spectrum["annotations"][0]["Instrument"].replace("\t", ""))
output_table["Compound_Source"].append(gnps_library_spectrum["annotations"][0]["Compound_Source"].replace("\t", ""))
output_table["PI"].append(gnps_library_spectrum["annotations"][0]["PI"].replace("\t", ""))
output_table["Data_Collector"].append(gnps_library_spectrum["annotations"][0]["Data_Collector"].replace("\t", ""))
output_table["Adduct"].append(gnps_library_spectrum["annotations"][0]["Adduct"].replace("\t", ""))
output_table["Precursor_MZ"].append(gnps_library_spectrum["annotations"][0]["Precursor_MZ"].replace("\t", ""))
output_table["ExactMass"].append(gnps_library_spectrum["annotations"][0]["ExactMass"].replace("\t", ""))
output_table["Charge"].append(gnps_library_spectrum["annotations"][0]["Charge"].replace("\t", ""))
output_table["CAS_Number"].append(gnps_library_spectrum["annotations"][0]["CAS_Number"].replace("\t", ""))
output_table["Pubmed_ID"].append(gnps_library_spectrum["annotations"][0]["Pubmed_ID"].replace("\t", ""))
output_table["Smiles"].append(gnps_library_spectrum["annotations"][0]["Smiles"].replace("\t", ""))
output_table["INCHI"].append(gnps_library_spectrum["annotations"][0]["INCHI"].replace("\t", ""))
output_table["INCHI_AUX"].append(gnps_library_spectrum["annotations"][0]["INCHI_AUX"].replace("\t", ""))
output_table["Library_Class"].append(gnps_library_spectrum["annotations"][0]["Library_Class"].replace("\t", ""))
output_table["IonMode"].append(gnps_library_spectrum["annotations"][0]["Ion_Mode"].replace("\t", ""))
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "1":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-GOLD")
output_table["LibraryQualityString"].append("Gold")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "2":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-SILVER")
output_table["LibraryQualityString"].append("Silver")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "3":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Bronze")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "4":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Insilico")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "5":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Insilico")
elif gnps_library_spectrum["annotations"][0]["Library_Class"] == "10":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Challenge")
else:
print("BULLLSHIT", gnps_library_spectrum["annotations"][0]["Library_Class"])
output_table["#Scan#"].append(scan)
output_table["SpectrumFile"].append(filename)
output_table["LibraryName"].append(libfilename)
output_table["MQScore"].append(score)
output_table["Organism"].append(gnps_library_spectrum["spectruminfo"]["library_membership"])
output_table["TIC_Query"].append(TIC_Query)
output_table["RT_Query"].append(RT_Query)
output_table["MZErrorPPM"].append(MZErrorPPM)
output_table["SharedPeaks"].append(SharedPeaks)
output_table["MassDiff"].append(MassDiff)
output_table["LibMZ"].append(gnps_library_spectrum["annotations"][0]["Precursor_MZ"])
output_table["SpecMZ"].append(SpecMZ)
output_table["SpecCharge"].append(SpecCharge)
output_table["FileScanUniqueID"].append(input_table["FileScanUniqueID"][i])
output_table["NumberHits"].append(number_hits_per_query[input_table["FileScanUniqueID"][i]])
tag_list = [ (tag["tag_desc"] + "[" + tag["tag_type"] + "]") for tag in gnps_library_spectrum["spectrum_tags"]]
tag_string = "||".join(tag_list).replace("\t", "")
output_table["tags"].append(tag_string)
ming_fileio_library.write_dictionary_table_data(output_table, output_result_filename)
def main():
input_result_filename = sys.argv[1]
output_result_filename = sys.argv[2]
input_rows, input_table = ming_fileio_library.parse_table_with_headers(input_result_filename)
output_table = defaultdict(list)
output_headers = ["SpectrumID", "Compound_Name", "Ion_Source", "Instrument", "Compound_Source", "PI", "Data_Collector", "Adduct"]
output_headers += ["Precursor_MZ", "ExactMass", "Charge", "CAS_Number", "Pubmed_ID", "Smiles", "INCHI", "INCHI_AUX", "Library_Class"]
output_headers += ["IonMode", "UpdateWorkflowName", "LibraryQualityString", "#Scan#", "SpectrumFile", "MQScore", "Organism"]
output_headers += ["TIC_Query", "RT_Query", "MZErrorPPM", "SharedPeaks", "MassDiff", "LibMZ", "SpecMZ", "SpecCharge"]
for header in output_headers:
output_table[header] = []
for i in range(input_rows):
spectrum_id = input_table["LibrarySpectrumID"][i]
score = input_table["MQScore"][i]
filename = input_table["SpectrumFile"][i]
libfilename = input_table["LibraryName"][i]
scan = input_table["#Scan#"][i]
TIC_Query = input_table["UnstrictEvelopeScore"][i]
RT_Query = input_table["p-value"][i]
SpecCharge = input_table["Charge"][i]
SpecMZ = input_table["SpecMZ"][i]
MZErrorPPM = input_table["mzErrorPPM"][i]
SharedPeaks = input_table["LibSearchSharedPeaks"][i]
MassDiff = input_table["ParentMassDiff"][i]
print(spectrum_id)
gnps_library_spectrum = None
try:
gnps_library_spectrum = ming_gnps_library.get_library_spectrum(spectrum_id)
except KeyboardInterrupt:
raise
except:
continue
output_table["SpectrumID"].append(spectrum_id)
output_table["Compound_Name"].append(gnps_library_spectrum["annotations"][0]["Compound_Name"])
output_table["Ion_Source"].append(gnps_library_spectrum["annotations"][0]["Ion_Source"])
output_table["Instrument"].append(gnps_library_spectrum["annotations"][0]["Instrument"])
output_table["Compound_Source"].append(gnps_library_spectrum["annotations"][0]["Compound_Source"])
output_table["PI"].append(gnps_library_spectrum["annotations"][0]["PI"])
output_table["Data_Collector"].append(gnps_library_spectrum["annotations"][0]["Data_Collector"])
output_table["Adduct"].append(gnps_library_spectrum["annotations"][0]["Adduct"])
output_table["Precursor_MZ"].append(gnps_library_spectrum["annotations"][0]["Precursor_MZ"])
output_table["ExactMass"].append(gnps_library_spectrum["annotations"][0]["ExactMass"])
output_table["Charge"].append(gnps_library_spectrum["annotations"][0]["Charge"])
output_table["CAS_Number"].append(gnps_library_spectrum["annotations"][0]["CAS_Number"])
output_table["Pubmed_ID"].append(gnps_library_spectrum["annotations"][0]["Pubmed_ID"])
output_table["Smiles"].append(gnps_library_spectrum["annotations"][0]["Smiles"])
output_table["INCHI"].append(gnps_library_spectrum["annotations"][0]["INCHI"])
output_table["INCHI_AUX"].append(gnps_library_spectrum["annotations"][0]["INCHI_AUX"])
output_table["Library_Class"].append(gnps_library_spectrum["annotations"][0]["Library_Class"])
output_table["IonMode"].append(gnps_library_spectrum["annotations"][0]["Ion_Mode"])
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "1":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-GOLD")
output_table["LibraryQualityString"].append("Gold")
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "2":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-SILVER")
output_table["LibraryQualityString"].append("Silver")
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "3":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Bronze")
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "4":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Insilico")
if gnps_library_spectrum["annotations"][0]["Library_Class"] == "10":
output_table["UpdateWorkflowName"].append("UPDATE-SINGLE-ANNOTATED-BRONZE")
output_table["LibraryQualityString"].append("Challenge")
output_table["#Scan#"].append(scan)
output_table["SpectrumFile"].append(filename)
output_table["LibraryName"].append(libfilename)
output_table["MQScore"].append(score)
output_table["Organism"].append(gnps_library_spectrum["spectruminfo"]["library_membership"])
output_table["TIC_Query"].append(TIC_Query)
output_table["RT_Query"].append(RT_Query)
output_table["MZErrorPPM"].append(MZErrorPPM)
output_table["SharedPeaks"].append(SharedPeaks)
output_table["MassDiff"].append(MassDiff)
output_table["LibMZ"].append(gnps_library_spectrum["annotations"][0]["Precursor_MZ"])
output_table["SpecMZ"].append(SpecMZ)
output_table["SpecCharge"].append(SpecCharge)
tag_string = ""
for tag in gnps_library_spectrum["spectrum_tags"]:
tag_string += tag["tag_desc"].replace("\t", "") + "||"
if len(tag_string) > 3:
tag_string = tag_string[:-2]
output_table["tags"].append(tag_string)
ming_fileio_library.write_dictionary_table_data(output_table, output_result_filename)