code: def _get_best_percentile(self, cluster, counts):
          ''' return all UMIs with counts >1% of the
          median counts in the cluster '''
  
          if len(cluster) == 1:
              return list(cluster)
          else:
              threshold = np.median(list(counts.values()))/100
              return [read for read in cluster if counts[read] > thresholdf _get_best_percentile(self, cluster, counts):
          ''' return all UMIs with counts >1% of the
          median counts in the cluster '''
  
          if len(cluster) == 1:
              return list(cluster)
          else:
              threshold = np.median(list(counts.values()))/100
              return [read for read in cluster if counts[read] > threshold]
docs: return all UMIs with counts >1% of the
          median counts in the cluster