code: def parse_roadmap_gwas(fn):
      
      df = pd.read_table(fn, low_memory=False, 
                         names=['chrom', 'start', 'end', 'rsid', 'pvalue'])
      df = df[df.pvalue < 1e-5]
      df = df.sort(columns=['chrom', 'start', 'pvalue'])
      df = df.drop_duplicates(subset=['chrom', 'start'])
      df = df[df['chrom'] != 'chrY']
      df.index = df['chrom'].astype(str) + ':' + df['end'].astype(str)
      return df
docs: Read Roadmap GWAS file and filter for unique, significant (p < 1e-5)
      SNPs.
      
      Parameters
      ----------
      fn : str
          Path to (subset of) GRASP database.
      
      Returns
      -------
      df : pandas.DataFrame
          Pandas dataframe with de-duplicated, significant SNPs. The index is of
          the form chrom:pos where pos is the one-based position of the SNP. The
          columns are chrom, start, end, rsid, and pvalue. rsid may be empty or
          not actually an RSID. chrom, start, end make a zero-based bed file with
          the SNP coordinates.