code: def filter_using_summary(fq, args):
      
      data = {entry[0]: entry[1] for entry in process_summary(
          summaryfile=args.summary,
          threads="NA",
          readtype=args.readtype,
          barcoded=False)[
          ["readIDs", "quals"]].itertuples(index=False)}
      try:
          for record in SeqIO.parse(fq, "fastq"):
              if data[record.id] > args.quality \
                      and args.length <= len(record) <= args.maxlength:
                  print(record[args.headcrop:args.tailcrop].format("fastq"), end="")
      except KeyError:
          logging.error("mismatch between summary and fastq: \
                         {} was not found in the summary file.".format(record.id))
          sys.exit('\nERROR: mismatch between sequencing_summary and fastq file: \
                   {} was not found in the summary file.\nQuitting.'.format(record.id))
docs: Use quality scores from albacore summary file for filtering
  
      Use the summary file from albacore for more accurate quality estimate
      Get the dataframe from nanoget, convert to dictionary