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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def computeFrequencyOfSignificantSNPs(options):
 """Computes the frequency of the significant markers. :param options: the options. :type options: argparse.Namespace Extract a list of markers (significant after plate bias analysis) and computes their frequencies. """

    # The plink command
    plinkCommand = ["plink", "--noweb", "--bfile", options.bfile, "--extract",
                    options.out + ".significant_SNPs.txt", "--freq", "--out",
                    options.out + ".significant_SNPs"]
    runCommand(plinkCommand)

    # Reading the frequency file
    maf = {}
    with open(options.out + ".significant_SNPs.frq", "r") as i_file:
        header = {
            name: i for i, name in
            enumerate(createRowFromPlinkSpacedOutput(i_file.readline()))
        }
        for required_col in ("SNP", "MAF"):
            if required_col not in header:
                msg = "{}: missing column {}".format(
                    script_prefix + ".significant_SNPs.frq",
                    required_col,
                )
                raise ProgramError(msg)

        for line in i_file:
            row = createRowFromPlinkSpacedOutput(line)
            maf[row[header["SNP"]]] = row[header["MAF"]]

    return maf