Give user more specific error information about input_type

[elephantoid]

Describe the bug
I was going to run alphaquant pipeline. I ran pipeline with something input type and then I wanted to run also other types.
but i got an error like "format not specified in intable_config.yaml!".
This message is not enough for resolving problems. so I had to go through all the relevant code.
It was really terrible user experience.

To Reproduce
Steps to reproduce the behavior:

1. Prepare the Spectronnut Report without FG.Quantity column
2. Run AlphaQuant pipeline with spectronaut_precursor_fragion_ms1_protein
3. See error

Expected behavior
When I think, when a failure occurs, I think enough information should be provided to solve it.
so this is my suggest for that

def get_input_type_and_config_dict(input_file, input_type_to_use=None):
    all_config_dicts = _load_config(INTABLE_CONFIG)
    type2relevant_columns = _get_type2relevant_cols(all_config_dicts)

    if "aq_reformat.tsv" in input_file:
        input_file = _get_original_file_from_aq_reformat(input_file)

    sep = _get_seperator(input_file)

    uploaded_data_columns = quantreader_utils.read_columns_from_file(
        input_file, sep=sep
    )

    missing_columns = []
    available_columns = []
    failed_input_type = None

    for input_type in type2relevant_columns:
        if (input_type_to_use is not None) and (input_type != input_type_to_use):
            continue
        relevant_columns = type2relevant_columns.get(input_type)
        relevant_columns = [x for x in relevant_columns if x]  # filter None values
        if set(relevant_columns).issubset(uploaded_data_columns):
            config_dict = all_config_dicts.get(input_type)
            return input_type, config_dict, sep
        else:
            if input_type_to_use is not None and input_type == input_type_to_use:
                failed_input_type = input_type
                missing_columns = list(
                    set(relevant_columns) - set(uploaded_data_columns)
                )
                available_columns = list(
                    set(relevant_columns) & set(uploaded_data_columns)
                )

    if input_type_to_use is not None and failed_input_type is not None:
        raise ValueError(
            f"Input type '{input_type_to_use}' requires columns that are missing from your data file.\n"
            f"Missing columns: {missing_columns}\n"
            f"Available columns: {available_columns}\n"
            f"Data file columns: {uploaded_data_columns}\n\n"
            f"Please check your data file or try a different input_type_to_use."
        )
    else:
        available_types = list(type2relevant_columns.keys())
        raise ValueError(
            f"No suitable input type found for the given data file.\n"
            f"Data file columns: {uploaded_data_columns}\n"
            f"Available input types: {available_types}\n\n"
            f"Please check your data file or specify a different input_type_to_use."
        )