quantms runs

[enryH]

• downstream ion parsing does not work yet

[enryH]

try:
    input_df = load_input_file(input_file_loc, input_format)
except pd.errors.ParserError as e:
    raise ParseError(
        f"Error parsing {input_format} file, please make sure the format is correct and the correct software tool is chosen: {e}"
    )
except Exception as e:
    raise ParseSettingsError(f"Error parsing the input file: {e}")

# Parse settings file
try:
    parse_settings = ParseSettingsBuilder(
        parse_settings_dir=self.parse_settings_dir, module_id=self.module_id
    ).build_parser(input_format)
except KeyError as e:
    raise ParseSettingsError(f"Error parsing settings file for parsing, settings seem to be missing: {e}")
except FileNotFoundError as e:
    raise ParseSettingsError(f"Could not find the parsing settings file: {e}")
except Exception as e:
    raise ParseSettingsError(f"Error parsing settings file for parsing: {e}")

try:
    standard_format, replicate_to_raw = parse_settings.convert_to_standard_format(input_df)
except KeyError as e:
    raise ConvertStandardFormatError(f"Error converting to standard format, key missing: {e}")
except Exception as e:
    raise ConvertStandardFormatError(f"Error converting to standard format: {e}")

# calculate quantification scores
try:
    quant_score = QuantScores(
        self.precursor_name, parse_settings.species_expected_ratio(), parse_settings.species_dict()
    )
except Exception as e:
    raise QuantificationError(f"Error generating quantification scores: {e}")

# generate intermediate data structure
try:
    intermediate_data_structure = quant_score.generate_intermediate(standard_format, replicate_to_raw)
except Exception as e:
    raise IntermediateFormatGenerationError(f"Error generating intermediate data structure: {e}")

Currently reading works and I advance to the generation of the intermediate output (last step above), but then fail with proteobench.exceptions.IntermediateFormatGenerationError: Error generating intermediate data structure: "['precursor ion'] not in index"

@RobbinBouwmeester any idea why?

[RobbinBouwmeester]

Hmmm interesting. I do know there is an ion warning that is sometimes thrown without good reason, could be that.

Issue there, if I remember correctly, is that it tries to read the charge state. But due to some complications at that point in the code it cannot (yet). We need to build in the check later.

Will have a look ASAP.

[enryH]

Thanks. But that is already a good hint. I will double check where the charge is used.

[enryH]

Execution is continued although it might be required. If we add an explicit error, we would need to test all parsing again.

ProteoBench/proteobench/io/parsing/parse_settings.py

Lines 168 to 175 in b52149e

	if self.analysis_level == "ion":
	if "proforma" in df_filtered_melted.columns and "Charge" in df_filtered_melted.columns:
	df_filtered_melted["precursor ion"] = (
	df_filtered_melted["proforma"] + "|Z=" + df_filtered_melted["Charge"].astype(str)
	)
	else:
	print("Not all columns required for making the ion are available.")
	return df_filtered_melted, replicate_to_raw

[enryH]

@rodvrees Was there any reason to not raise an ValueError?

[enryH]

So the answer is yes according to the test which fail for

FAILED test/test_module_dda_quant.py::TestOutputFileReading::test_benchmarking - proteobench.exceptions.ConvertStandardFormatError: Error converting to standard format.
FAILED test/test_module_dda_quant.py::TestOutputFileReading::test_input_file_initial_parsing - ValueError: Not all columns required for making the ion are available: 'proforma' and 'Charge'.
FAILED test/test_module_dda_quant.py::TestOutputFileReading::test_input_file_processing - ValueError: Not all columns required for making the ion are available: 'proforma' and 'Charge'.
FAILED test/test_module_dda_quant.py::TestWrongFormatting::test_MaxQuant_file - proteobench.exceptions.ConvertStandardFormatError: Error converting to standard format.
FAILED test/test_module_dia_quant.py::TestOutputFileReading::test_benchmarking - proteobench.exceptions.ConvertStandardFormatError: Error converting to standard format: Not all columns required for making the ion are available: 'proforma' and 'Charge'.
FAILED test/test_module_dia_quant.py::TestOutputFileReading::test_input_file_initial_parsing - ValueError: Not all columns required for making the ion are available: 'proforma' and 'Charge'.
FAILED test/test_module_dia_quant.py::TestOutputFileReading::test_input_file_processing - ValueError: Not all columns required for making the ion are available: 'proforma' and 'Charge'.
FAILED test/test_module_dia_quant.py::TestWrongFormatting::test_DIANN_file - proteobench.exceptions.ConvertStandardFormatError: Error converting to standard format: Not all columns required for making the ion are available: 'proforma' and 'Charge'.

[enryH]

Regarding the precursor ion it was mainly due to the fact that I started from the custom format which does not have a [modifications_parser] in it's toml file, leading to no proforma column being generated.

ProteoBench/proteobench/io/parsing/parse_settings.py

Lines 67 to 69 in b52149e

	parser = ParseSettings(parse_settings, parse_settings_module)
	if "modifications_parser" in parse_settings.keys():
	parser = ParseModificationSettings(parser, parse_settings)

using the ParseSettings functionality:

ProteoBench/proteobench/io/parsing/parse_settings.py

Lines 188 to 196 in b52149e

	class ParseModificationSettings:
	def __init__(self, parser: ParseSettings, parse_settings: Dict[str, Any]):
	"""
	Initialize the ParseModificationSettings object.
	Args:
	parser (ParseSettings): The base parse settings object.
	parse_settings (Dict[str, Any]): The modifications-specific parse settings.
	"""