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Scatter & Distribution plot : allele frequency comparison

!! info "Available from v3.4.15"

.check_af()

Calculate the difference in allele frequency (DAF) between the effect allele frequency (EAF) in your sumstats and the alternative allele frequency (ALT_AF) in a reference VCF/BCF file.

Purpose:

  • Quality control: Identify variants with large differences in allele frequency
  • Validation: Verify EAF values are consistent with reference population frequencies
  • Detect issues: Large |DAF| values (> 0.2) may indicate allele mismatches, strand flips, or data quality issues

DAF Calculation:

  • DAF = EAF (sumstats) - ALT_AF (reference VCF)
  • Positive DAF: EAF in sumstats is higher than reference
  • Negative DAF: EAF in sumstats is lower than reference
# Check the difference between the EAF in the sumstats and the allele frequency in VCF files
mysumstats.check_af(ref_infer="path/to/reference.vcf.gz",
                  ref_alt_freq="AF",
                  maf_threshold=0.40,
                  threads=2)

Parameters:

  • ref_infer: Path to reference VCF/BCF file (must be tabix-indexed)
  • ref_alt_freq: Field name for ALT frequency in VCF INFO (e.g., "AF", "AF_popmax", "gnomAD_AF")
  • maf_threshold: MAF threshold for filtering variants (default: 0.40)
  • column_name: Column name to store DAF values (default: "DAF")
  • threads: Number of CPU threads (default: 1)

For more details, see Harmonization documentation.

.plot_daf()

#allele frequnecy correlation plot
mysumstats.plot_daf()

You need to run 'check_af()' first before plotting. For check_af(), see here.

Options for plot_daf: threshold: float, the threshold used to determine outliers.

Examples

Example

mysumstats = gl.Sumstats("t2d_bbj.txt.gz",
             snpid="SNP",
             chrom="CHR",
             pos="POS",
             ea="ALT",
             nea="REF",
             neaf="Frq",
             beta="BETA",
             se="SE",
             p="P",
             direction="Dir",
             n="N",nrows=10000)

# harmonize
mysumstats.harmonize(basic_check = True, 
                     ref_seq=gl.get_path("ucsc_genome_hg19"))


# check the difference in allele frequency with reference vcf
mysumstats.check_af(ref_infer=gl.get_path("1kg_eas_hg19"), 
                    ref_alt_freq="AF",
                    threads=2)


plot and get the outliers
outliers = mysumstats.plot_daf(threshold=0.12, 
                                save="af_correlation.png",
                                save_kwargs={"dpi":300})


outliers[1]