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Plink parsers

From the plink documentation: https://www.cog-genomics.org/plink/1.9/formats#bim

A text file with no header line, and one line per variant with the following six fields:

- Chromosome code (either an integer, or 'X'/'Y'/'XY'/'MT'; '0' indicates unknown) or name
- Variant identifier
- Position in morgans or centimorgans (safe to use dummy value of '0')
- Base-pair coordinate (1-based; limited to 231-2)
- Allele 1 (corresponding to clear bits in .bed; usually minor)
- Allele 2 (corresponding to set bits in .bed; usually major)

Parameters:

Name Type Description Default
plink_bfile str

The path to the plink bfile (with or without the extension).

 required
Source code in magenpy/parsers/plink_parsers.py 
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def parse_bim_file(plink_bfile):
    """
    From the plink documentation:
    https://www.cog-genomics.org/plink/1.9/formats#bim

        A text file with no header line, and one line per variant with the following six fields:

        - Chromosome code (either an integer, or 'X'/'Y'/'XY'/'MT'; '0' indicates unknown) or name
        - Variant identifier
        - Position in morgans or centimorgans (safe to use dummy value of '0')
        - Base-pair coordinate (1-based; limited to 231-2)
        - Allele 1 (corresponding to clear bits in .bed; usually minor)
        - Allele 2 (corresponding to set bits in .bed; usually major)

    :param plink_bfile: The path to the plink bfile (with or without the extension).
    :type plink_bfile: str
    """

    if ".bim" not in plink_bfile:
        if ".bed" in plink_bfile:
            plink_bfile = plink_bfile.replace(".bed", ".bim")
        else:
            plink_bfile = plink_bfile + ".bim"

    bim_df = pd.read_csv(
        plink_bfile,
        sep=r"\s+",
        names=["CHR", "SNP", "cM", "POS", "A1", "A2"],
        dtype={
            "CHR": int,
            "SNP": str,
            "cM": np.float32,
            "POS": np.int32,
            "A1": str,
            "A2": str,
        },
    )

    return bim_df

From the plink documentation: https://www.cog-genomics.org/plink/1.9/formats#fam

A text file with no header line, and one line per sample with the following six fields:

- Family ID ('FID')
- Within-family ID ('IID'; cannot be '0')
- Within-family ID of father ('0' if father isn't in dataset)
- Within-family ID of mother ('0' if mother isn't in dataset)
- Sex code ('1' = male, '2' = female, '0' = unknown)
- Phenotype value ('1' = control, '2' = case, '-9'/'0'/non-numeric = missing data if case/control)

Parameters:

Name Type Description Default
plink_bfile str

The path to the plink bfile (with or without the extension).

 required
Source code in magenpy/parsers/plink_parsers.py 
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def parse_fam_file(plink_bfile):
    """
    From the plink documentation:
    https://www.cog-genomics.org/plink/1.9/formats#fam

        A text file with no header line, and one line per sample with the following six fields:

        - Family ID ('FID')
        - Within-family ID ('IID'; cannot be '0')
        - Within-family ID of father ('0' if father isn't in dataset)
        - Within-family ID of mother ('0' if mother isn't in dataset)
        - Sex code ('1' = male, '2' = female, '0' = unknown)
        - Phenotype value ('1' = control, '2' = case, '-9'/'0'/non-numeric = missing data if case/control)

    :param plink_bfile: The path to the plink bfile (with or without the extension).
    :type plink_bfile: str
    """

    if ".fam" not in plink_bfile:
        if ".bed" in plink_bfile:
            plink_bfile = plink_bfile.replace(".bed", ".fam")
        else:
            plink_bfile = plink_bfile + ".fam"

    fam_df = pd.read_csv(
        plink_bfile,
        sep=r"\s+",
        usecols=list(range(6)),
        names=["FID", "IID", "fatherID", "motherID", "sex", "phenotype"],
        dtype={
            "FID": str,
            "IID": str,
            "fatherID": str,
            "motherID": str,
            "sex": np.float32,
            "phenotype": np.float32,
        },
        na_values={"phenotype": [-9.0], "sex": [0]},
    )

    # If the phenotype is all null or unknown, drop the column:
    if fam_df["phenotype"].isnull().all():
        fam_df.drop("phenotype", axis=1, inplace=True)

    # If the sex column is all null or unknown, drop the column:
    if fam_df["sex"].isnull().all():
        fam_df.drop("sex", axis=1, inplace=True)

    return fam_df