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-22660_106/ukb-d-22660_106.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-22660_106/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 14:58:21 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22660_106/ukb-d-22660_106.vcf.gz ...
Read summary statistics for 10474308 SNPs.
Dropped 8348 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, 1280633 SNPs remain.
After merging with regression SNP LD, 1280633 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0174 (0.0066)
Lambda GC: 1.0281
Mean Chi^2: 1.0195
Intercept: 0.9964 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 15:00:05 2019
Total time elapsed: 1.0m:44.3s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9439,
    "inflation_factor": 1.0216,
    "mean_EFFECT": 3.6887e-06,
    "n": 67655,
    "n_snps": 10474308,
    "n_clumped_hits": 1,
    "n_p_sig": 8,
    "n_mono": 0,
    "n_ns": 1110384,
    "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": 206059,
    "n_est": 67704.2932,
    "ratio_se_n": 1.0004,
    "mean_diff": 0,
    "ratio_diff": 60.7155,
    "sd_y_est1": 0.1604,
    "sd_y_est2": 0.1605,
    "r2_sum1": 0,
    "r2_sum2": 0.0005,
    "r2_sum3": 0.0005,
    "r2_sum4": 0.0005,
    "ldsc_nsnp_merge_refpanel_ld": 1280633,
    "ldsc_nsnp_merge_regression_ld": 1280633,
    "ldsc_observed_scale_h2_beta": 0.0174,
    "ldsc_observed_scale_h2_se": 0.0066,
    "ldsc_intercept_beta": 0.9964,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0281,
    "ldsc_mean_chisq": 1.0195,
    "ldsc_ratio": -0.1846
}

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 10466526 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 49630 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30718 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.076391e+00 6.178361e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.30000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.878957e+07 5.605373e+07 3.02000e+02 3.255462e+07 6.973202e+07 1.147358e+08 2.49230e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.700000e-06 2.355800e-03 -2.17488e-02 -1.030400e-03 -1.030000e-05 1.011300e-03 2.99275e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.961000e-03 1.301300e-03 7.27900e-04 9.701000e-04 1.363900e-03 2.576400e-03 7.25500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.970132e-01 2.891572e-01 0.00000e+00 2.458618e-01 4.954046e-01 7.470196e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.970109e-01 2.891586e-01 0.00000e+00 2.458580e-01 4.954030e-01 7.470178e-01 1.00000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.439846e-01 2.626490e-01 6.16370e-03 3.113230e-02 1.340790e-01 3.903590e-01 9.93836e-01 ▇▂▂▁▁
numeric AF_reference 206059 0.9803272 NA NA NA NA NA 2.438741e-01 2.535822e-01 0.00000e+00 3.254790e-02 1.507590e-01 3.873800e-01 1.00000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.765500e+04 0.000000e+00 6.76550e+04 6.765500e+04 6.765500e+04 6.765500e+04 6.76550e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0012438 0.0015248 0.4146436 0.4146436 0.1113330 0.1894970 67655
1 693731 rs12238997 A G -0.0008058 0.0014444 0.5769498 0.5769475 0.1164250 0.1417730 67655
1 707522 rs371890604 G C -0.0016866 0.0016240 0.2990322 0.2990269 0.0978617 0.1293930 67655
1 717587 rs144155419 G A 0.0043240 0.0038671 0.2635008 0.2634972 0.0157910 0.0045926 67655
1 730087 rs148120343 T C -0.0007322 0.0020034 0.7147613 0.7147590 0.0569430 0.0127796 67655
1 731718 rs142557973 T C -0.0005943 0.0013709 0.6646316 0.6646312 0.1223980 0.1543530 67655
1 732032 rs61770163 A C -0.0013461 0.0014621 0.3572120 0.3572102 0.1220450 0.1555510 67655
1 734349 rs141242758 T C -0.0006011 0.0013719 0.6612825 0.6612814 0.1216050 0.1525560 67655
1 749963 rs529266287 T TAA 0.0015963 0.0013490 0.2367119 0.2367081 0.8688800 0.7641770 67655
1 751343 rs28544273 T A -0.0014778 0.0013380 0.2694027 0.2694003 0.1236460 0.2426120 67655
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0007204 0.0016352 0.6595610 0.6595596 0.0547784 0.0309934 67655
23 154923374 rs111332691 T A -0.0032296 0.0017794 0.0695264 0.0695214 0.0442687 0.0116556 67655
23 154925045 rs509981 C T -0.0000527 0.0008495 0.9505610 0.9505613 0.2448950 0.3634440 67655
23 154925895 rs538470 C T -0.0001230 0.0008686 0.8873830 0.8873829 0.2412550 0.3634440 67655
23 154927581 rs644138 G A -0.0001912 0.0008001 0.8111280 0.8111270 0.3000720 0.4635760 67655
23 154929412 rs557132 C T -0.0000690 0.0008497 0.9352799 0.9352797 0.2447530 0.3568210 67655
23 154929637 rs35185538 CT C -0.0002789 0.0008876 0.7533295 0.7533280 0.2291340 0.3011920 67655
23 154929952 rs4012982 CAA C -0.0001119 0.0008945 0.9004801 0.9004794 0.2385660 0.3165560 67655
23 154930230 rs781880 A G -0.0000636 0.0008495 0.9403599 0.9403595 0.2451600 0.3618540 67655
23 154930487 rs781879 T A -0.0031126 0.0029076 0.2843957 0.2843922 0.0193551 0.1263580 67655

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111333 ES:SE:LP:AF:SS:ID   -0.00124383:0.00152477:0.382325:0.111333:67655:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116425 ES:SE:LP:AF:SS:ID   -0.000805785:0.00144445:0.238862:0.116425:67655:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978617    ES:SE:LP:AF:SS:ID   -0.00168655:0.00162399:0.524282:0.0978617:67655:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015791 ES:SE:LP:AF:SS:ID   0.00432405:0.0038671:0.579218:0.015791:67655:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.056943 ES:SE:LP:AF:SS:ID   -0.000732176:0.00200337:0.145839:0.056943:67655:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122398 ES:SE:LP:AF:SS:ID   -0.000594315:0.00137088:0.177419:0.122398:67655:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122045 ES:SE:LP:AF:SS:ID   -0.00134611:0.00146206:0.447074:0.122045:67655:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121605 ES:SE:LP:AF:SS:ID   -0.000601095:0.00137191:0.179613:0.121605:67655:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.86888  ES:SE:LP:AF:SS:ID   0.00159627:0.00134905:0.62578:0.86888:67655:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123646 ES:SE:LP:AF:SS:ID   -0.00147778:0.00133803:0.569598:0.123646:67655:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143073 ES:SE:LP:AF:SS:ID   -0.00150466:0.0013243:0.591967:0.143073:67655:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123779 ES:SE:LP:AF:SS:ID   -0.00146452:0.00133607:0.563802:0.123779:67655:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869863 ES:SE:LP:AF:SS:ID   0.00155029:0.00130167:0.631416:0.869863:67655:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874632 ES:SE:LP:AF:SS:ID   0.00154585:0.00132337:0.614818:0.874632:67655:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129534 ES:SE:LP:AF:SS:ID   -0.00137132:0.00130559:0.532302:0.129534:67655:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358436    ES:SE:LP:AF:SS:ID   -0.00231084:0.00238321:0.478559:0.0358436:67655:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869516 ES:SE:LP:AF:SS:ID   0.00149037:0.00130052:0.598929:0.869516:67655:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869601 ES:SE:LP:AF:SS:ID   0.00147808:0.00130118:0.591791:0.869601:67655:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86951  ES:SE:LP:AF:SS:ID   0.00149256:0.00130046:0.600176:0.86951:67655:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869521 ES:SE:LP:AF:SS:ID   0.00156179:0.00129798:0.640381:0.869521:67655:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126879 ES:SE:LP:AF:SS:ID   -0.00139388:0.00132485:0.533494:0.126879:67655:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869086 ES:SE:LP:AF:SS:ID   0.00158599:0.00129469:0.656432:0.869086:67655:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86843  ES:SE:LP:AF:SS:ID   0.00160789:0.00129332:0.670015:0.86843:67655:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   0.00158787:0.00129574:0.656773:0.869213:67655:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869219 ES:SE:LP:AF:SS:ID   0.00158542:0.00129583:0.655305:0.869219:67655:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:SS:ID   0.00158894:0.00129584:0.657317:0.869221:67655:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869661 ES:SE:LP:AF:SS:ID   0.00161558:0.00129921:0.670226:0.869661:67655:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991549    ES:SE:LP:AF:SS:ID   -0.00160617:0.00151249:0.540204:0.0991549:67655:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00672466   ES:SE:LP:AF:SS:ID   -0.000947426:0.00570419:0.0614382:0.00672466:67655:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873693 ES:SE:LP:AF:SS:ID   0.00163307:0.00131836:0.666637:0.873693:67655:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86311  ES:SE:LP:AF:SS:ID   0.00119673:0.00129308:0.450123:0.86311:67655:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868459 ES:SE:LP:AF:SS:ID   0.00136478:0.00130614:0.528601:0.868459:67655:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865449 ES:SE:LP:AF:SS:ID   0.00167664:0.00130622:0.700506:0.865449:67655:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0996966    ES:SE:LP:AF:SS:ID   -0.00155078:0.00156188:0.493812:0.0996966:67655:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   0.00153122:0.00132116:0.608254:0.870704:67655:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   0.0015312:0.00132116:0.608243:0.870704:67655:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870702 ES:SE:LP:AF:SS:ID   0.00153134:0.00132116:0.608317:0.870702:67655:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871042 ES:SE:LP:AF:SS:ID   0.00164374:0.00132179:0.670271:0.871042:67655:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126524 ES:SE:LP:AF:SS:ID   -0.00144219:0.00132313:0.559527:0.126524:67655:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105925 ES:SE:LP:AF:SS:ID   -0.00135108:0.00143996:0.45829:0.105925:67655:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854403 ES:SE:LP:AF:SS:ID   0.00162405:0.0012925:0.679999:0.854403:67655:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839355 ES:SE:LP:AF:SS:ID   -0.000851849:0.00127666:0.297039:0.839355:67655:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763322 ES:SE:LP:AF:SS:ID   0.000677514:0.00102633:0.293135:0.763322:67655:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.104959 ES:SE:LP:AF:SS:ID   0.000367969:0.00141565:0.0996771:0.104959:67655:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00786948   ES:SE:LP:AF:SS:ID   -0.000405933:0.00519305:0.0279389:0.00786948:67655:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129874 ES:SE:LP:AF:SS:ID   -0.00115467:0.00130491:0.424542:0.129874:67655:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129612 ES:SE:LP:AF:SS:ID   -0.00122136:0.00130319:0.457603:0.129612:67655:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104244 ES:SE:LP:AF:SS:ID   0.000522066:0.0014265:0.146068:0.104244:67655:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00881952   ES:SE:LP:AF:SS:ID   0.0043189:0.00509258:0.401869:0.00881952:67655:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00789757   ES:SE:LP:AF:SS:ID   -0.000243917:0.00521122:0.0165235:0.00789757:67655:rs112563271