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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}

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/ukb-d-import/processed/ukb-d-5001/ukb-d-5001.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/ukb-d-import/processed/ukb-d-5001/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 17:19:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5001/ukb-d-5001.vcf.gz ...
Read summary statistics for 13562422 SNPs.
Dropped 12682 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0519 (0.0069)
Lambda GC: 1.0945
Mean Chi^2: 1.0959
Intercept: 1.009 (0.0067)
Ratio: 0.0936 (0.0696)
Analysis finished at Mon Nov 25 17:22:34 2019
Total time elapsed: 2.0m:34.73s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0564,
    "mean_EFFECT": -0,
    "n": 84560,
    "n_snps": 13562422,
    "n_clumped_hits": 1,
    "n_p_sig": 4,
    "n_mono": 0,
    "n_ns": 1251044,
    "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": 561700,
    "n_est": 84918.6656,
    "ratio_se_n": 1.0021,
    "mean_diff": -0.0001,
    "ratio_diff": 36.2459,
    "sd_y_est1": 0.3312,
    "sd_y_est2": 0.3319,
    "r2_sum1": 0,
    "r2_sum2": 0.0004,
    "r2_sum3": 0.0004,
    "r2_sum4": 0.0004,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.0519,
    "ldsc_observed_scale_h2_se": 0.0069,
    "ldsc_intercept_beta": 1.009,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0945,
    "ldsc_mean_chisq": 1.0959,
    "ldsc_ratio": 0.0938
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 13550404 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57048 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33325 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051606e+00 6.185015e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902533e+07 5.591631e+07 3.0200e+02 3.292938e+07 7.013786e+07 1.148565e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.320000e-05 9.410000e-03 -1.4600e-01 -2.539500e-03 6.900000e-06 2.569000e-03 1.011260e-01 ▁▁▇▃▁
numeric SE 0 1.0000000 NA NA NA NA NA 6.734100e-03 6.487600e-03 1.3242e-03 1.925300e-03 3.539200e-03 9.668400e-03 3.320140e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.912087e-01 2.907072e-01 0.0000e+00 2.371488e-01 4.881587e-01 7.429404e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.912068e-01 2.907083e-01 0.0000e+00 2.371459e-01 4.881566e-01 7.429404e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911313e-01 2.544796e-01 1.0000e-03 7.522600e-03 6.039180e-02 2.959520e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561700 0.9585841 NA NA NA NA NA 1.965649e-01 2.471540e-01 0.0000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.456000e+04 0.000000e+00 8.4560e+04 8.456000e+04 8.456000e+04 8.456000e+04 8.456000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0013076 0.0028139 0.6421493 0.6421487 0.1121560 0.1894970 84560
1 693731 rs12238997 A G 0.0024167 0.0026619 0.3639410 0.3639388 0.1175570 0.1417730 84560
1 707522 rs371890604 G C 0.0024680 0.0029869 0.4086571 0.4086543 0.0985902 0.1293930 84560
1 717587 rs144155419 G A 0.0027291 0.0071657 0.7033087 0.7033078 0.0157686 0.0045926 84560
1 723329 rs189787166 A T -0.0153198 0.0210321 0.4663726 0.4663682 0.0017291 0.0003994 84560
1 730087 rs148120343 T C 0.0003885 0.0037052 0.9164840 0.9164840 0.0572239 0.0127796 84560
1 731718 rs142557973 T C 0.0015867 0.0025283 0.5302846 0.5302821 0.1233210 0.1543530 84560
1 732032 rs61770163 A C 0.0026554 0.0026927 0.3240530 0.3240497 0.1226810 0.1555510 84560
1 734349 rs141242758 T C 0.0016252 0.0025300 0.5206502 0.5206479 0.1225210 0.1525560 84560
1 740284 rs61770167 C T 0.0002943 0.0114042 0.9794120 0.9794120 0.0059528 0.0023962 84560
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0058971 0.0029453 0.0452616 0.0452588 0.0553391 0.0309934 84560
23 154923374 rs111332691 T A -0.0019959 0.0032156 0.5348057 0.5348036 0.0445246 0.0116556 84560
23 154925045 rs509981 C T -0.0004939 0.0015485 0.7497872 0.7497869 0.2439760 0.3634440 84560
23 154925895 rs538470 C T -0.0006445 0.0015830 0.6838975 0.6838975 0.2404630 0.3634440 84560
23 154927581 rs644138 G A -0.0019092 0.0014561 0.1898021 0.1897989 0.2997000 0.4635760 84560
23 154929412 rs557132 C T -0.0004520 0.0015492 0.7704545 0.7704538 0.2437950 0.3568210 84560
23 154929637 rs35185538 CT C -0.0006314 0.0016141 0.6956391 0.6956390 0.2283320 0.3011920 84560
23 154929952 rs4012982 CAA C -0.0003005 0.0016293 0.8536959 0.8536949 0.2379300 0.3165560 84560
23 154930230 rs781880 A G -0.0004339 0.0015488 0.7793508 0.7793482 0.2442420 0.3618540 84560
23 154930487 rs781879 T A -0.0009497 0.0053265 0.8584860 0.8584855 0.0192211 0.1263580 84560

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112156 ES:SE:LP:AF:SS:ID   0.00130761:0.0028139:0.192364:0.112156:84560:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117557 ES:SE:LP:AF:SS:ID   0.0024167:0.0026619:0.438969:0.117557:84560:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0985902    ES:SE:LP:AF:SS:ID   0.00246796:0.00298689:0.388641:0.0985902:84560:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157686    ES:SE:LP:AF:SS:ID   0.00272913:0.00716572:0.152854:0.0157686:84560:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00172909   ES:SE:LP:AF:SS:ID   -0.0153198:0.0210321:0.331267:0.00172909:84560:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0572239    ES:SE:LP:AF:SS:ID   0.000388542:0.00370521:0.0378751:0.0572239:84560:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123321 ES:SE:LP:AF:SS:ID   0.00158668:0.00252827:0.275491:0.123321:84560:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122681 ES:SE:LP:AF:SS:ID   0.00265545:0.00269269:0.489384:0.122681:84560:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122521 ES:SE:LP:AF:SS:ID   0.00162517:0.00253005:0.283454:0.122521:84560:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0059528    ES:SE:LP:AF:SS:ID   0.000294298:0.0114042:0.00903458:0.0059528:84560:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018425    ES:SE:LP:AF:SS:ID   -0.0267375:0.0223094:0.636894:0.0018425:84560:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868238 ES:SE:LP:AF:SS:ID   -0.00167178:0.00249506:0.298575:0.868238:84560:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00164427   ES:SE:LP:AF:SS:ID   0.0289137:0.0216449:0.74086:0.00164427:84560:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124395 ES:SE:LP:AF:SS:ID   0.00203061:0.00247069:0.386002:0.124395:84560:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144    ES:SE:LP:AF:SS:ID   0.0018814:0.00244683:0.354629:0.144:84560:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124533 ES:SE:LP:AF:SS:ID   0.00208612:0.00246689:0.400389:0.124533:84560:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869246 ES:SE:LP:AF:SS:ID   -0.00150943:0.0024029:0.27581:0.869246:84560:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873942 ES:SE:LP:AF:SS:ID   -0.00170544:0.00244277:0.314187:0.873942:84560:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130314 ES:SE:LP:AF:SS:ID   0.00211806:0.00240843:0.421168:0.130314:84560:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0369737    ES:SE:LP:AF:SS:ID   0.000499579:0.00433577:0.0417855:0.0369737:84560:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868843 ES:SE:LP:AF:SS:ID   -0.00167501:0.00240047:0.313976:0.868843:84560:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868982 ES:SE:LP:AF:SS:ID   -0.00157918:0.00240183:0.291691:0.868982:84560:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868843 ES:SE:LP:AF:SS:ID   -0.0016785:0.00240034:0.314812:0.868843:84560:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00518321   ES:SE:LP:AF:SS:ID   0.0186504:0.0121682:0.901883:0.00518321:84560:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00514894   ES:SE:LP:AF:SS:ID   0.0183387:0.0122019:0.876616:0.00514894:84560:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0053731    ES:SE:LP:AF:SS:ID   0.00280916:0.0122065:0.0872541:0.0053731:84560:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868963 ES:SE:LP:AF:SS:ID   -0.00158367:0.00239655:0.293508:0.868963:84560:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127547 ES:SE:LP:AF:SS:ID   0.00221394:0.00244579:0.43728:0.127547:84560:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868537 ES:SE:LP:AF:SS:ID   -0.00169757:0.00239094:0.320839:0.868537:84560:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867698 ES:SE:LP:AF:SS:ID   -0.00192014:0.00238768:0.375418:0.867698:84560:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868689 ES:SE:LP:AF:SS:ID   -0.00162274:0.00239291:0.303048:0.868689:84560:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868696 ES:SE:LP:AF:SS:ID   -0.0016256:0.00239309:0.303681:0.868696:84560:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868706 ES:SE:LP:AF:SS:ID   -0.00165464:0.00239318:0.31041:0.868706:84560:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869131 ES:SE:LP:AF:SS:ID   -0.00156734:0.00239929:0.289377:0.869131:84560:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100096 ES:SE:LP:AF:SS:ID   0.00218572:0.0027837:0.364168:0.100096:84560:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00617499   ES:SE:LP:AF:SS:ID   0.00342158:0.0110722:0.12073:0.00617499:84560:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873113 ES:SE:LP:AF:SS:ID   -0.0016021:0.00243546:0.291872:0.873113:84560:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862393 ES:SE:LP:AF:SS:ID   -0.00168177:0.00238884:0.317468:0.862393:84560:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867919 ES:SE:LP:AF:SS:ID   -0.00167542:0.00241128:0.312323:0.867919:84560:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864685 ES:SE:LP:AF:SS:ID   -0.00119316:0.00241116:0.207113:0.864685:84560:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997324    ES:SE:LP:AF:SS:ID   0.00132163:0.00289192:0.18865:0.0997324:84560:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870023 ES:SE:LP:AF:SS:ID   -0.00145882:0.00243906:0.259819:0.870023:84560:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870022 ES:SE:LP:AF:SS:ID   -0.00145892:0.00243905:0.259843:0.870022:84560:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870025 ES:SE:LP:AF:SS:ID   -0.00145031:0.00243922:0.25796:0.870025:84560:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870385 ES:SE:LP:AF:SS:ID   -0.00145639:0.00244051:0.259108:0.870385:84560:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127086 ES:SE:LP:AF:SS:ID   0.00209017:0.00244281:0.406492:0.127086:84560:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106665 ES:SE:LP:AF:SS:ID   0.00125976:0.00265521:0.197103:0.106665:84560:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85369  ES:SE:LP:AF:SS:ID   -0.00187098:0.00238712:0.363342:0.85369:84560:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00162574   ES:SE:LP:AF:SS:ID   -0.0199926:0.0212058:0.461188:0.00162574:84560:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837496 ES:SE:LP:AF:SS:ID   0.00149859:0.00234886:0.281107:0.837496:84560:rs376645387