code: def parse_gene_expression(gene_expression_fp, mean=False):
      
      gene_expression_dict = OrderedDict()
      with open(gene_expression_fp) as inFile:
          inFile.readline()  # Skip header.
          for line in inFile.readlines():
              tokens = line.strip().split('\t')
              gene_identifier = tokens[0]
  
              if mean:
                  expression = np.log2(np.mean([float(t) for t in tokens[1:]]) + 1.0)
              else:
                  expression = np.log2(float(tokens[1]) + 1.0)
  
              gene_expression_dict[gene_identifier] = expression
  
      return gene_expression_dict
docs: Parses gene expression file and returns a (gene identifier)-(expression) dictionary.
      Attribute:
          gene_expression_fp (str): File path to a gene expression file.
          mean (bool): When making a normal(reference) gene expression profile, you might use
              average values of gene expressions for each gene. In this case, pass mean=True.