docs: def make_entropy_col_consensus(bg_freqs):
      """Consensus according to maximal relative entropy term (MET).
  
      For a given column i, choose the residue j with the highest relative
      entropy term::
  
          f_ij ln(f_ij/b_j)
  
      where f_ij = column aa frequency, b_j = background aa frequency.
  
      Source: http://bioinformatics.oxfordjournals.org/content/24/18/1987.long
      """
      def col_consensus(col):
          col_freqs = sequtils.aa_frequencies(col)
          entroper = entropy_func(col_freqs, bg_freqs)
          return max(col_freqs.keys(), key=entroper)
      return col_consensus