def METHOD_NAME():
    parser = optparse.OptionParser()
    parser.add_option("--input")
    parser.add_option("--output")
    parser.add_option("--decoy_prefix")
    parser.add_option("--identifiers_column")
    parser.add_option("--separator", default="TAB")
    parser.add_option("--fdr_type", default="global_conservative")
    parser.add_option("--scaling")
    parser.add_option("--score_column", default=None)
    # By default higher score is better.
    parser.add_option("--invert_score", default=False, action="store_true")
    (options, args) = parser.parse_args()
    decoy_prefix = options.decoy_prefix
    identifiers_column = options.identifiers_column
    score_column = options.score_column
    separator = SEPARATORS[options.separator]
    settings = {"decoy_prefix": decoy_prefix,
                "identifiers_index": int(identifiers_column) - 1,
                "fdr_type": options.fdr_type,
                "separator": separator,
                "scaling": options.scaling,
                "invert_score": options.invert_score
               }
    if score_column:
        settings["score_column"] = int(score_column) - 1
    else:
        settings["score_column"] = None
        # Assume data is descending, use index as score and invert.
        settings["invert_score"] = True
    with open(options.output, 'w') as output:
        append_fdr(options.input, output, settings)