removes unneeded code after refactoring

src/qc_checkup/modules/qualimap.py

@@ -11,56 +11,6 @@ from common import present_within_range, qc_logger, write_to_yaml_file
 LOGGER = qc_logger(__name__)
 
 
-# def overall_stats(multiqc_df, sample_name, qualimap_config, outfile):
-#     """
-#     Reads overall qualimap QC summary for a particular sample using multiqc's general stats data
-#     and summarizes the result.
-#     """
-
-#     LOGGER.info(
-#         f"Analyzing overall qualimap results for sample '{sample_name}' using multiqc general stats data"
-#     )
-
-#     if sample_name not in multiqc_df.index:
-#         LOGGER.exception(
-#             f"Sample '{sample_name}' not present in multiqc's general stats data. Exiting now"
-#         )
-#         raise SystemExit(1)
-
-#     qualimap_prefix = "QualiMap_mqc-generalstats-qualimap"
-#     if pd.isnull(multiqc_df.loc[sample_name, f"{qualimap_prefix}-avg_gc"]):
-#         LOGGER.exception(
-#             f"Qualimap data not available for '{sample_name}' in multiqc's general stats data. Exiting now"
-#         )
-#         raise SystemExit(1)
-
-#     results_dict = {sample_name: {}}
-#     pass_fail = set()
-#     for qc_metric in qualimap_config:
-#         if qc_metric == "mean_cov:median_cov":
-#             mean_cov = multiqc_df.loc[sample_name, f"{qualimap_prefix}-mean_coverage"]
-#             median_cov = multiqc_df.loc[sample_name, f"{qualimap_prefix}-median_coverage"]
-#             value = (mean_cov / median_cov).round(3)
-#         else:
-#             value = multiqc_df.loc[sample_name, f"{qualimap_prefix}-{qc_metric}"]
-
-#         minimum = qualimap_config[qc_metric]["min"]
-#         maximum = qualimap_config[qc_metric]["max"]
-
-#         result = present_within_range(value, minimum, maximum)
-#         results_dict[sample_name][f"{qc_metric}_val"] = float(value)
-#         results_dict[sample_name][qc_metric] = "pass" if result else "fail"
-#         pass_fail.add(result)
-
-#     # write results to file
-#     write_to_yaml_file(results_dict, outfile)
-
-#     # summarize results to one term
-#     qc_check_status = "pass" if all(pass_fail) else "fail"
-
-#     return qc_check_status
-
-
 def stat_by_chromosome(qualimap_f, sample_name, qualimap_config, outfile):
     """
     Analyzes chromosome-level coverage QC using qualimap report file

src/qc_checkup/modules/verifybamid.py

-"""
-Read overall verifyBamID QC summary for a particular sample using multiqc's general stats data
-and summarize the result.
-"""
-
-import pandas as pd
-from common import present_within_range, qc_logger, write_to_yaml_file
-
-# setup logging
-LOGGER = qc_logger(__name__)
-
-
-def verifybamid(multiqc_df, sample_name, verifybamid_config, outfile):
-    """
-    Reads overall verifyBamID QC summary for a particular sample using multiqc's general stats data
-    and summarizes the result.
-    """
-
-    LOGGER.info(
-        f"Analyzing overall verifyBamID results for sample '{sample_name}' using multiqc general stats data"
-    )
-
-    if sample_name not in multiqc_df.index:
-        LOGGER.exception(
-            f"Sample '{sample_name}' not present in multiqc's general stats data. Exiting now"
-        )
-        raise SystemExit(1)
-
-    verifybamid_prefix = "VerifyBAMID_mqc-generalstats-verifybamid"
-    results_dict = {sample_name: {}}
-    pass_fail = set()
-    for qc_metric in verifybamid_config:
-        value = multiqc_df.loc[sample_name, f"{verifybamid_prefix}-{qc_metric}"]
-
-        minimum = verifybamid_config[qc_metric]["min"]
-        maximum = verifybamid_config[qc_metric]["max"]
-
-        result = present_within_range(value, minimum, maximum)
-        results_dict[sample_name][f"{qc_metric}_val"] = float(value)
-        results_dict[sample_name][qc_metric] = "pass" if result else "fail"
-        pass_fail.add(result)
-
-    # write results to file
-    write_to_yaml_file(results_dict, outfile)
-
-    # summarize results to one term
-    qc_check_status = "pass" if all(pass_fail) else "fail"
-
-    return qc_check_status