input: 
  from typing import List, Tuple
  
  def count_rRNA_MT_transcripts(htseq_counts_path: str, gtf_path: str) -> Tuple[int, int, int, int]:
      """ Calculate the number of reads mapping to rRNA and MT transcripts and their percentages.
      Given an HTseq_counts file and a GTF file, this function extracts the gene identifiers 
      for rRNA and MT genes, counts the reads mapping to these identifiers, and computes 
      the percentage of total reads that map to rRNA and MT.
      >>> count_rRNA_MT_transcripts('/path/to/HTseq_counts/file', '/path/to/GTF/file')
      (Cummulative_rRNA_Count, Cummulative_MT_Count, ReadCount, Perc_rRNA, Perc_MT)
      """
      import re
      rRNA_identifiers = {}
      MT_identifiers = {}
  
      with open(gtf_path, "rU") as handle:
          for line in handle:
              line.rstrip('\n')
              if 'gene_biotype "rRNA"' in line:
                  identifier = re.sub('.*gene_id "', '', line)
                  identifier = re.sub('"; gene_version.*\n', '', identifier)
                  rRNA_identifiers[identifier] = 1
              if 'MT' in line:
                  identifier = re.sub('.*gene_id "', '', line)
                  identifier = re.sub('"; gene_version.*\n', '', identifier)
                  MT_identifiers[identifier] = 1
  
      Cummulative_rRNA_Count = 0
      Cummulative_MT_Count = 0
      ReadCount = 0
      line_number = 0
  
      with open(htseq_counts_path, "rU") as handle:
          for line in handle:
              line.rstrip('\n')
              split_line = line.split("\t")
              if line_number > 0:
                  if split_line[0] in rRNA_identifiers.keys():
                      Cummulative_rRNA_Count += int(split_line[1])
                  if split_line[0] in MT_identifiers.keys():
                      Cummulative_MT_Count += int(split_line[1])
                  ReadCount += int(split_line[1])
              line_number += 1
  
      Perc_rRNA = round(100 * (Cummulative_rRNA_Count / ReadCount), 3)
      Perc_MT = round(100 * (Cummulative_MT_Count / ReadCount), 3)
  
      return Cummulative_rRNA_Count, Cummulative_MT_Count, ReadCount, Perc_rRNA, Perc_MT
  
output:     return Cummulative_rRNA_Count, Cummulative_MT_Count, ReadCount, Perc_rRNA, Perc_MT