code: def comp_overlap_table(data):
      
      headers = OrderedDict()
      headers['comp_rate'] = {
          'title': 'Compare rate',
          'description': 'Ratio of known variants found in the reference set.',
          'namespace': 'GATK',
          'min': 0,
          'max': 100,
          'suffix': '%',
          'format': '{:,.2f}',
          'scale': 'Blues',
      }
      headers['concordant_rate'] = {
          'title': 'Concordant rate',
          'description': 'Ratio of variants matching alleles in the reference set.',
          'namespace': 'GATK',
          'min': 0,
          'max': 100,
          'suffix': '%',
          'format': '{:,.2f}',
          'scale': 'Blues',
      }
      headers['eval_variants'] = {
          'title': 'M Evaluated variants',
          'description': 'Number of called variants (millions)',
          'namespace': 'GATK',
          'min': 0,
          'modify': lambda x: float(x) / 1000000.0
      }
      headers['known_sites'] = {
          'title': 'M Known sites',
          'description': 'Number of known variants (millions)',
          'namespace': 'GATK',
          'min': 0,
          'modify': lambda x: float(x) / 1000000.0
      }
      headers['novel_sites'] = {
          'title': 'M Novel sites',
          'description': 'Number of novel variants (millions)',
          'namespace': 'GATK',
          'min': 0,
          'modify': lambda x: float(x) / 1000000.0
      }
      table_html = table.plot(data, headers, {'id': 'gatk_compare_overlap', 'table_title': 'GATK - Compare Overlap'})
      return table_html
docs: Build a table from the comp overlaps output.