Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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    "FORMAT.2": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
    "FORMAT.3": "<ID=ID,Number=1,Type=String,Description=\"Study variant identifier\">",
    "FORMAT.4": "<ID=LP,Number=A,Type=Float,Description=\"-log10 p-value for effect estimate\">",
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    "FORMAT.6": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
    "FORMAT.7": "<ID=SI,Number=A,Type=Float,Description=\"Accuracy score of summary data imputation\">",
    "FORMAT.8": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
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    "INFO.1": "<ID=ReverseComplementedAlleles,Number=0,Type=Flag,Description=\"The REF and the ALT alleles have been reverse complemented in liftover since the mapping from the previous reference to the current one was on the negative strand.\">",
    "INFO.2": "<ID=SwappedAlleles,Number=0,Type=Flag,Description=\"The REF and the ALT alleles have been swapped in liftover due to changes in the reference. It is possible that not all INFO annotations reflect this swap, and in the genotypes, only the GT, PL, and AD fields have been modified. You should check the TAGS_TO_REVERSE parameter that was used during the LiftOver to be sure.\">",
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    "file_date": "2019-10-26T21:43:34.442520",
    "gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005038/EBI-a-GCST005038_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/hg38/hg38.fa; 1.1.1",
    "reference": "file:/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta",
    "bcftools_annotateVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "bcftools_annotateCommand": "annotate -a /mnt/storage/home/gh13047/mr-eve/vcf-reference-datasets/dbsnp/dbsnp.v153.b37.vcf.gz -c ID -o /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005038/EBI-a-GCST005038.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005038/EBI-a-GCST005038_data.vcf.gz; Date=Sat Oct 26 21:57:28 2019",
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    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST005038/ebi-a-GCST005038.vcf.gz; Date=Sun May 10 12:16:52 2020"
}

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005038/EBI-a-GCST005038.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005038/ldsc.txt \
--snplist /data/ref/snplist.gz \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Sat Oct 26 22:21:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005038/EBI-a-GCST005038.vcf.gz ...
and extracting SNPs specified in /data/ref/snplist.gz ...
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
    sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 165, in _read_sumstats
    sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna, slh=args.snplist)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 85, in sumstats
    x = read_vcf(fh, alleles, slh)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 161, in read_vcf
    with gzip.open(slh) as f:
  File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 34, in open
    return GzipFile(filename, mode, compresslevel)
  File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 94, in __init__
    fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
IOError: [Errno 2] No such file or directory: '/data/ref/snplist.gz'

Analysis finished at Sat Oct 26 22:22:12 2019
Total time elapsed: 55.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.0972,
    "inflation_factor": 1.1856,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 8133670,
    "n_clumped_hits": 74,
    "n_p_sig": 8826,
    "n_mono": 0,
    "n_ns": 352173,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 20939,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": "NA",
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

Flags

name value
af_correlation TRUE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio TRUE
ldsc_intercept_beta TRUE
n_clumped_hits FALSE
r2_sum1 FALSE
r2_sum2 FALSE
r2_sum3 FALSE
r2_sum4 FALSE

Definitions

General metrics

  • af_correlation: Correlation coefficient between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

  • n_est: Estimated sample size value, \(\widehat{n}\).
  • ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
  • mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

  • r2_sum<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
    • 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
    • 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

  • ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
  • ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
  • ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
  • ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
  • ldsc_lambda_gc: Lambda GC statistics.
  • ldsc_mean_chisq: Mean \(\chi^2\) statistics.
  • ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

  • af_correlation: abs(af_correlation) < 0.7.
  • inflation_factor: inflation_factor > 1.2.
  • n: n (max reported sample size) < 10000.
  • is_snpid_non_unique: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type skim_variable n_missing complete_rate character.min character.max character.empty character.n_unique character.whitespace logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 25 0 8117496 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 54 0 14176 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 43 0 10688 0 NA NA NA NA NA NA NA NA NA NA
logical N 8117501 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.831606e+00 5.954243e+00 1.000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.885665e+07 5.619188e+07 8.280e+02 3.245672e+07 6.972416e+07 1.147296e+08 2.492165e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.100000e-05 1.508670e-02 -2.499e-01 -6.900000e-03 1.000000e-04 7.000000e-03 2.767000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.183970e-02 7.999800e-03 5.100e-03 6.400000e-03 8.500000e-03 1.450000e-02 1.354000e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.711027e-01 2.954898e-01 0.000e+00 2.086998e-01 4.627005e-01 7.275000e-01 9.995000e-01 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.710789e-01 2.954915e-01 0.000e+00 2.085452e-01 4.627202e-01 7.273717e-01 9.990892e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.657700e-01 3.528916e-01 1.020e-02 1.071000e-01 4.286000e-01 8.265000e-01 9.898000e-01 ▇▃▂▃▆
numeric AF_reference 20939 0.9974205 NA NA NA NA NA NA NA 2.581960e-01 2.509195e-01 1.997e-04 5.331470e-02 1.703270e-01 4.019570e-01 1.000000e+00 ▇▃▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 751756 rs143225517 T C -0.0053 0.0094 0.5689001 0.5728700 0.87410 0.2422120 NA
1 752307 rs201062411 AT A -0.0450 0.0182 0.0136600 0.0134161 0.04252 0.0275559 NA
1 752478 rs146277091 G A -0.0431 0.0181 0.0168702 0.0172556 0.04252 0.0277556 NA
1 752566 rs3094315 G A 0.0147 0.0087 0.0912998 0.0910939 0.16670 0.7182510 NA
1 752617 rs149886465 C A -0.0425 0.0182 0.0194800 0.0195348 0.04252 0.0275559 NA
1 752721 rs3131972 A G 0.0117 0.0084 0.1619001 0.1636630 0.83160 0.6533550 NA
1 752894 rs3131971 T C 0.0171 0.0087 0.0509401 0.0493544 0.83500 0.7531950 NA
1 753474 rs2073814 C G 0.0118 0.0084 0.1595001 0.1600921 0.83160 0.6114220 NA
1 753541 rs2073813 G A -0.0020 0.0090 0.8211001 0.8241409 0.13100 0.3019170 NA
1 754063 rs12184312 G T -0.0399 0.0179 0.0258899 0.0258106 0.03741 0.0229633 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154909877 rs586454 G T -0.0073 0.0081 0.3700999 0.3674636 0.19230 0.3557620 NA
23 154910802 rs147364233 C T -0.0002 0.0200 0.9927000 0.9920213 0.03846 0.1070200 NA
23 154912406 rs200842587 A AT -0.0115 0.0098 0.2395003 0.2406076 0.88780 0.0561589 NA
23 154913799 rs622581 T C -0.0087 0.0082 0.2850001 0.2887010 0.80770 0.3568210 NA
23 154915619 rs571421 G A -0.0086 0.0081 0.2848000 0.2883590 0.18910 0.3565560 NA
23 154918242 rs73562846 C T -0.0095 0.0097 0.3298998 0.3273915 0.11220 0.0691391 NA
23 154918383 rs641588 G T -0.0083 0.0081 0.3036002 0.3055088 0.19230 0.3565560 NA
23 154925895 rs538470 C T -0.0086 0.0081 0.2890999 0.2883590 0.20190 0.3634440 NA
23 154927199 rs645904 C T -0.0076 0.0081 0.3458000 0.3481048 0.19550 0.3674170 NA
23 154929412 rs557132 C T -0.0083 0.0081 0.3008999 0.3055088 0.19230 0.3568210 NA

bcf preview

1   751756  rs28527770  T   C   .   PASS    AF=0.8741   ES:SE:LP:AF:ID  -0.0053:0.0094:0.244964:0.8741:rs28527770
1   752307  rs201062411 AT  A   .   PASS    AF=0.04252  ES:SE:LP:AF:ID  -0.045:0.0182:1.86455:0.04252:rs201062411
1   752478  rs146277091 G   A   .   PASS    AF=0.04252  ES:SE:LP:AF:ID  -0.0431:0.0181:1.77288:0.04252:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.1667   ES:SE:LP:AF:ID  0.0147:0.0087:1.03953:0.1667:rs3094315
1   752617  rs149886465 C   A   .   PASS    AF=0.04252  ES:SE:LP:AF:ID  -0.0425:0.0182:1.71041:0.04252:rs149886465
1   752721  rs3131972   A   G   .   PASS    AF=0.8316   ES:SE:LP:AF:ID  0.0117:0.0084:0.790753:0.8316:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.835    ES:SE:LP:AF:ID  0.0171:0.0087:1.29294:0.835:rs3131971
1   753474  rs2073814   C   G   .   PASS    AF=0.8316   ES:SE:LP:AF:ID  0.0118:0.0084:0.797239:0.8316:rs2073814
1   753541  rs2073813   G   A   .   PASS    AF=0.131    ES:SE:LP:AF:ID  -0.002:0.009:0.0856039:0.131:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03741  ES:SE:LP:AF:ID  -0.0399:0.0179:1.58687:0.03741:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.04082  ES:SE:LP:AF:ID  -0.0292:0.0166:1.10419:0.04082:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8656   ES:SE:LP:AF:ID  0.0024:0.0089:0.10502:0.8656:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8656   ES:SE:LP:AF:ID  0.0021:0.0089:0.0879374:0.8656:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.04422  ES:SE:LP:AF:ID  -0.0422:0.0193:1.5373:0.04422:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.8656   ES:SE:LP:AF:ID  0.0032:0.009:0.140621:0.8656:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.1684   ES:SE:LP:AF:ID  0.0111:0.0085:0.721246:0.1684:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.95408  ES:SE:LP:AF:ID  -0.0413:0.0187:1.56543:0.95408:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.1701   ES:SE:LP:AF:ID  0.0118:0.0086:0.76523:0.1701:rs3131966
1   755890  rs3115858   A   T   .   PASS    AF=0.8673   ES:SE:LP:AF:ID  0.0059:0.0093:0.281083:0.8673:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.8622   ES:SE:LP:AF:ID  0.0074:0.0092:0.375718:0.8622:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.1361   ES:SE:LP:AF:ID  0.0023:0.0089:0.0978883:0.1361:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.1327   ES:SE:LP:AF:ID  0.0049:0.0092:0.227532:0.1327:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.1344   ES:SE:LP:AF:ID  0.0054:0.0092:0.250109:0.1344:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8537   ES:SE:LP:AF:ID  0.0092:0.0091:0.50307:0.8537:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.1327   ES:SE:LP:AF:ID  0.0049:0.0093:0.22439:0.1327:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.04252  ES:SE:LP:AF:ID  -0.039:0.0251:0.921181:0.04252:rs114525117
1   759837  rs3115851   T   A   .   PASS    AF=0.1327   ES:SE:LP:AF:ID  0.0056:0.0093:0.261616:0.1327:rs3115851
1   759970  rs145098582 A   G   .   PASS    AF=0.95578  ES:SE:LP:AF:ID  -0.0302:0.0254:0.63097:0.95578:rs145098582
1   760811  rs200712425 CTCTT   C   .   PASS    AF=0.95748  ES:SE:LP:AF:ID  -0.0301:0.0276:0.559406:0.95748:rs200712425
1   760912  rs1048488   C   T   .   PASS    AF=0.1667   ES:SE:LP:AF:ID  0.0124:0.009:0.76904:0.1667:rs1048488
1   760998  rs148828841 C   A   .   PASS    AF=0.04422  ES:SE:LP:AF:ID  -0.0193:0.0289:0.296709:0.04422:rs148828841
1   761147  rs3115850   T   C   .   PASS    AF=0.8316   ES:SE:LP:AF:ID  0.0124:0.009:0.76675:0.8316:rs3115850
1   776546  rs12124819  A   G   .   PASS    AF=0.7721   ES:SE:LP:AF:ID  0.0073:0.0091:0.370896:0.7721:rs12124819
1   796767  rs12076540  G   A   .   PASS    AF=0.284    ES:SE:LP:AF:ID  0.0122:0.0078:0.92336:0.284:rs12076540
1   797440  rs58013264  T   C   .   PASS    AF=0.8673   ES:SE:LP:AF:ID  -0.0089:0.01:0.425853:0.8673:rs58013264
1   798400  rs10900604  A   G   .   PASS    AF=0.7925   ES:SE:LP:AF:ID  -0.0044:0.0077:0.249414:0.7925:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.2075   ES:SE:LP:AF:ID  -0.0061:0.0076:0.373044:0.2075:rs11240777
1   801467  rs61768212  G   C   .   PASS    AF=0.1378   ES:SE:LP:AF:ID  -0.0096:0.0098:0.488117:0.1378:rs61768212
1   802026  rs7553096   G   A   .   PASS    AF=0.2177   ES:SE:LP:AF:ID  -0.0024:0.0079:0.115715:0.2177:rs7553096
1   802496  rs10157494  C   T   .   PASS    AF=0.1378   ES:SE:LP:AF:ID  -0.0123:0.0099:0.667764:0.1378:rs10157494
1   830791  rs184031231 C   T   .   PASS    AF=0.0119   ES:SE:LP:AF:ID  -0.0026:0.042:0.0220022:0.0119:rs184031231
1   832318  rs4500250   C   A   .   PASS    AF=0.3197   ES:SE:LP:AF:ID  0.0048:0.0073:0.294992:0.3197:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.7092   ES:SE:LP:AF:ID  0.0034:0.0074:0.18876:0.7092:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.6803   ES:SE:LP:AF:ID  -0.0048:0.0073:0.295764:0.6803:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.2517   ES:SE:LP:AF:ID  -0.0018:0.0077:0.0893222:0.2517:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.2517   ES:SE:LP:AF:ID  -0.0015:0.0077:0.0707855:0.2517:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.7483   ES:SE:LP:AF:ID  -0.0026:0.0078:0.129362:0.7483:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.7483   ES:SE:LP:AF:ID  -0.0021:0.0077:0.10502:0.7483:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.7789   ES:SE:LP:AF:ID  0.0005:0.0079:0.0201786:0.7789:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.7789   ES:SE:LP:AF:ID  0.0011:0.0079:0.0486625:0.7789:rs28385272