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-20448/ukb-d-20448.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-20448/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 17:13:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20448/ukb-d-20448.vcf.gz ...
Read summary statistics for 13560730 SNPs.
Dropped 12680 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: 0.041 (0.0083)
Lambda GC: 1.0552
Mean Chi^2: 1.0584
Intercept: 1.0048 (0.0069)
Ratio: 0.083 (0.1189)
Analysis finished at Mon Nov 25 17:15:28 2019
Total time elapsed: 2.0m:4.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0389,
    "mean_EFFECT": 0,
    "n": 66302,
    "n_snps": 13560730,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250948,
    "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": 561834,
    "n_est": 66464.0781,
    "ratio_se_n": 1.0012,
    "mean_diff": 0,
    "ratio_diff": 44.3577,
    "sd_y_est1": 0.4766,
    "sd_y_est2": 0.4771,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.041,
    "ldsc_observed_scale_h2_se": 0.0083,
    "ldsc_intercept_beta": 1.0048,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.0552,
    "ldsc_mean_chisq": 1.0584,
    "ldsc_ratio": 0.0822
}

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 1.000000 3 94 0 13548714 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 57035 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33324 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.051411e+00 6.185004e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.902400e+07 5.591580e+07 3.02000e+02 3.292671e+07 7.013658e+07 1.148568e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 2.690000e-05 1.526270e-02 -1.98487e-01 -4.096600e-03 2.880000e-05 4.153500e-03 1.819370e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 1.094240e-02 1.054020e-02 2.22270e-03 3.128300e-03 5.750600e-03 1.570970e-02 5.301080e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.937998e-01 2.903396e-01 1.00000e-07 2.407809e-01 4.917847e-01 7.455264e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.937974e-01 2.903410e-01 1.00000e-07 2.407766e-01 4.917828e-01 7.455259e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 1.911410e-01 2.544817e-01 1.00000e-03 7.523000e-03 6.044980e-02 2.960120e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561834 0.958569 NA NA NA NA NA 1.965752e-01 2.471484e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 6.630200e+04 0.000000e+00 6.63020e+04 6.630200e+04 6.630200e+04 6.630200e+04 6.630200e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0022478 0.0045486 0.6211851 0.6211841 0.1122300 0.1894970 66302
1 693731 rs12238997 A G -0.0022300 0.0043021 0.6042101 0.6042075 0.1172900 0.1417730 66302
1 707522 rs371890604 G C -0.0026541 0.0048192 0.5818151 0.5818137 0.0990393 0.1293930 66302
1 717587 rs144155419 G A 0.0006540 0.0116180 0.9551100 0.9551100 0.0156734 0.0045926 66302
1 723329 rs189787166 A T 0.0021641 0.0329393 0.9476160 0.9476162 0.0018601 0.0003994 66302
1 730087 rs148120343 T C -0.0049422 0.0059820 0.4087107 0.4087076 0.0573208 0.0127796 66302
1 731718 rs142557973 T C -0.0013953 0.0040814 0.7324585 0.7324576 0.1232890 0.1543530 66302
1 732032 rs61770163 A C -0.0036972 0.0043461 0.3949426 0.3949410 0.1228860 0.1555510 66302
1 734349 rs141242758 T C -0.0015974 0.0040828 0.6956135 0.6956123 0.1225770 0.1525560 66302
1 740284 rs61770167 C T 0.0095460 0.0186914 0.6095523 0.6095509 0.0058456 0.0023962 66302
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0038914 0.0049504 0.4318332 0.4318306 0.0555173 0.0309934 66302
23 154923374 rs111332691 T A -0.0000244 0.0054743 0.9964380 0.9964379 0.0434979 0.0116556 66302
23 154925045 rs509981 C T -0.0000352 0.0025920 0.9891600 0.9891601 0.2455060 0.3634440 66302
23 154925895 rs538470 C T 0.0000828 0.0026507 0.9750929 0.9750933 0.2417750 0.3634440 66302
23 154927581 rs644138 G A -0.0009217 0.0024407 0.7056917 0.7056892 0.3014430 0.4635760 66302
23 154929412 rs557132 C T -0.0001007 0.0025926 0.9690041 0.9690039 0.2453970 0.3568210 66302
23 154929637 rs35185538 CT C 0.0033122 0.0027076 0.2212249 0.2212210 0.2290560 0.3011920 66302
23 154929952 rs4012982 CAA C 0.0010072 0.0027313 0.7123034 0.7123037 0.2390590 0.3165560 66302
23 154930230 rs781880 A G 0.0000602 0.0025922 0.9814800 0.9814797 0.2457120 0.3618540 66302
23 154930487 rs781879 T A 0.0080715 0.0088179 0.3600070 0.3600035 0.0195170 0.1263580 66302

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11223  ES:SE:LP:AF:SS:ID   -0.00224777:0.00454855:0.206779:0.11223:66302:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11729  ES:SE:LP:AF:SS:ID   -0.00223005:0.00430213:0.218812:0.11729:66302:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0990393    ES:SE:LP:AF:SS:ID   -0.00265413:0.00481923:0.235215:0.0990393:66302:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156734    ES:SE:LP:AF:SS:ID   0.000653989:0.011618:0.0199466:0.0156734:66302:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00186009   ES:SE:LP:AF:SS:ID   0.00216413:0.0329393:0.0233676:0.00186009:66302:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0573208    ES:SE:LP:AF:SS:ID   -0.00494215:0.005982:0.388584:0.0573208:66302:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123289 ES:SE:LP:AF:SS:ID   -0.00139526:0.0040814:0.135217:0.123289:66302:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122886 ES:SE:LP:AF:SS:ID   -0.00369718:0.00434609:0.403466:0.122886:66302:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122577 ES:SE:LP:AF:SS:ID   -0.0015974:0.00408281:0.157632:0.122577:66302:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00584556   ES:SE:LP:AF:SS:ID   0.00954597:0.0186914:0.214989:0.00584556:66302:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188372   ES:SE:LP:AF:SS:ID   0.0322809:0.0352387:0.444136:0.00188372:66302:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868261 ES:SE:LP:AF:SS:ID   0.00200784:0.00402034:0.209374:0.868261:66302:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00155977   ES:SE:LP:AF:SS:ID   0.0374892:0.036229:0.521761:0.00155977:66302:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124618 ES:SE:LP:AF:SS:ID   -0.00222204:0.00398067:0.239046:0.124618:66302:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143985 ES:SE:LP:AF:SS:ID   -0.00025184:0.00394129:0.02271:0.143985:66302:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12472  ES:SE:LP:AF:SS:ID   -0.00228218:0.00397534:0.247251:0.12472:66302:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869053 ES:SE:LP:AF:SS:ID   0.00060439:0.00387501:0.0574681:0.869053:66302:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873655 ES:SE:LP:AF:SS:ID   0.00114775:0.00393737:0.113132:0.873655:66302:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130347 ES:SE:LP:AF:SS:ID   -0.000849591:0.00388615:0.0825223:0.130347:66302:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0364997    ES:SE:LP:AF:SS:ID   0.00950539:0.00708156:0.745907:0.0364997:66302:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868665 ES:SE:LP:AF:SS:ID   0.00053187:0.00387111:0.0502593:0.868665:66302:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868748 ES:SE:LP:AF:SS:ID   0.000381125:0.00387261:0.0354561:0.868748:66302:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868668 ES:SE:LP:AF:SS:ID   0.00054296:0.00387099:0.051366:0.868668:66302:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00502046   ES:SE:LP:AF:SS:ID   0.0167328:0.0201073:0.392209:0.00502046:66302:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00498835   ES:SE:LP:AF:SS:ID   0.0161708:0.0201526:0.374365:0.00498835:66302:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00577021   ES:SE:LP:AF:SS:ID   -0.0161707:0.0190018:0.403659:0.00577021:66302:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868697 ES:SE:LP:AF:SS:ID   0.000325616:0.00386396:0.0301919:0.868697:66302:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127712 ES:SE:LP:AF:SS:ID   -0.00072461:0.00394363:0.0684323:0.127712:66302:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868217 ES:SE:LP:AF:SS:ID   0.000383575:0.00385369:0.0358753:0.868217:66302:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867698 ES:SE:LP:AF:SS:ID   0.000225961:0.00385234:0.0208037:0.867698:66302:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868419 ES:SE:LP:AF:SS:ID   0.000236912:0.00385759:0.0218062:0.868419:66302:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868425 ES:SE:LP:AF:SS:ID   0.000241863:0.00385786:0.0222714:0.868425:66302:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868428 ES:SE:LP:AF:SS:ID   0.000245713:0.00385788:0.0226349:0.868428:66302:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868824 ES:SE:LP:AF:SS:ID   0.000242823:0.00386746:0.0223052:0.868824:66302:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100535 ES:SE:LP:AF:SS:ID   -0.00205445:0.00448565:0.189129:0.100535:66302:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00664878   ES:SE:LP:AF:SS:ID   -0.0157928:0.0172424:0.444049:0.00664878:66302:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872819 ES:SE:LP:AF:SS:ID   0.00087891:0.00392614:0.0846709:0.872819:66302:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.8623   ES:SE:LP:AF:SS:ID   0.00101698:0.00385109:0.101427:0.8623:66302:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867549 ES:SE:LP:AF:SS:ID   0.000959878:0.00388903:0.0941766:0.867549:66302:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864726 ES:SE:LP:AF:SS:ID   0.00142312:0.00389246:0.145902:0.864726:66302:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100682 ES:SE:LP:AF:SS:ID   -0.00184276:0.00464205:0.160277:0.100682:66302:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869759 ES:SE:LP:AF:SS:ID   0.00157506:0.00393476:0.161818:0.869759:66302:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869759 ES:SE:LP:AF:SS:ID   0.00157505:0.00393476:0.161817:0.869759:66302:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869756 ES:SE:LP:AF:SS:ID   0.00157406:0.00393477:0.161699:0.869756:66302:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870088 ES:SE:LP:AF:SS:ID   0.00117052:0.00393626:0.115666:0.870088:66302:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127341 ES:SE:LP:AF:SS:ID   -0.00122055:0.00393934:0.121084:0.127341:66302:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107089 ES:SE:LP:AF:SS:ID   -0.00224387:0.00428077:0.221734:0.107089:66302:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85356  ES:SE:LP:AF:SS:ID   -0.000924812:0.0038502:0.0914201:0.85356:66302:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00176829   ES:SE:LP:AF:SS:ID   0.00302788:0.0331687:0.0327966:0.00176829:66302:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838032 ES:SE:LP:AF:SS:ID   -0.000435642:0.0038223:0.0413124:0.838032:66302:rs376645387