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-4056_irnt/ukb-d-4056_irnt.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-4056_irnt/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 14:52:32 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4056_irnt/ukb-d-4056_irnt.vcf.gz ...
Read summary statistics for 13424742 SNPs.
Dropped 12474 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, 1283468 SNPs remain.
After merging with regression SNP LD, 1283468 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.1055 (0.0754)
Lambda GC: 0.9883
Mean Chi^2: 0.9908
Intercept: 1.002 (0.0058)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 14:54:51 2019
Total time elapsed: 2.0m:18.94s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9517,
    "inflation_factor": 0.9906,
    "mean_EFFECT": -0.0001,
    "n": 5339,
    "n_snps": 13424742,
    "n_clumped_hits": 0,
    "n_p_sig": 2,
    "n_mono": 0,
    "n_ns": 1245449,
    "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": 532508,
    "n_est": 5397.8021,
    "ratio_se_n": 1.0055,
    "mean_diff": -0,
    "ratio_diff": 12.6898,
    "sd_y_est1": 0.7334,
    "sd_y_est2": 0.7374,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283468,
    "ldsc_nsnp_merge_regression_ld": 1283468,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.002,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 0.9883,
    "ldsc_mean_chisq": 0.9908,
    "ldsc_ratio": -0.2174
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 13412926 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56720 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33233 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051428e+00 6.183349e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.901490e+07 5.591812e+07 302.0000000 3.291390e+07 7.011418e+07 1.148457e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.120000e-05 8.023880e-02 -1.2524700 -2.103800e-02 1.831000e-04 2.179630e-02 9.137210e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.785880e-02 5.557250e-02 0.0110776 1.691000e-02 3.065350e-02 8.248530e-02 3.641430e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.013167e-01 2.882003e-01 0.0000000 2.519852e-01 5.020281e-01 7.507235e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.012868e-01 2.882183e-01 0.0000000 2.519331e-01 5.019984e-01 7.507107e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.929688e-01 2.549366e-01 0.0010000 7.984500e-03 6.272530e-02 2.998310e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 532508 0.9603338 NA NA NA NA NA 1.980086e-01 2.474753e-01 0.0000000 5.990400e-03 8.646170e-02 3.113020e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.339000e+03 0.000000e+00 5339.0000000 5.339000e+03 5.339000e+03 5.339000e+03 5.339000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0282483 0.0253158 0.2645410 0.2644920 0.1074130 0.1894970 5339
1 693731 rs12238997 A G -0.0393566 0.0240479 0.1017759 0.1017158 0.1132790 0.1417730 5339
1 707522 rs371890604 G C -0.0487604 0.0272952 0.0740901 0.0740330 0.0935047 0.1293930 5339
1 717587 rs144155419 G A 0.0241439 0.0659415 0.7142743 0.7142597 0.0142136 0.0045926 5339
1 723329 rs189787166 A T -0.1281140 0.1783050 0.4724752 0.4724426 0.0017786 0.0003994 5339
1 730087 rs148120343 T C -0.0450169 0.0327863 0.1697970 0.1697399 0.0568113 0.0127796 5339
1 731718 rs142557973 T C -0.0402849 0.0227582 0.0767627 0.0767060 0.1187170 0.1543530 5339
1 732032 rs61770163 A C -0.0357702 0.0245004 0.1443531 0.1442944 0.1168390 0.1555510 5339
1 734349 rs141242758 T C -0.0392911 0.0227588 0.0843315 0.0842730 0.1181120 0.1525560 5339
1 740284 rs61770167 C T -0.1438610 0.1118680 0.1985048 0.1984470 0.0050762 0.0023962 5339
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0040447 0.0242509 0.8675470 0.8675401 0.0573618 0.0309934 5339
23 154923374 rs111332691 T A 0.0063623 0.0282584 0.8218739 0.8218648 0.0400824 0.0116556 5339
23 154925045 rs509981 C T 0.0233504 0.0129469 0.0713592 0.0713017 0.2491400 0.3634440 5339
23 154925895 rs538470 C T 0.0228721 0.0132639 0.0846954 0.0846380 0.2451920 0.3634440 5339
23 154927581 rs644138 G A 0.0216019 0.0121686 0.0759189 0.0758621 0.3073100 0.4635760 5339
23 154929412 rs557132 C T 0.0229099 0.0129580 0.0771170 0.0770589 0.2486900 0.3568210 5339
23 154929637 rs35185538 CT C 0.0306553 0.0135008 0.0232097 0.0231695 0.2306310 0.3011920 5339
23 154929952 rs4012982 CAA C 0.0226264 0.0135751 0.0956225 0.0955626 0.2430550 0.3165560 5339
23 154930230 rs781880 A G 0.0231359 0.0129507 0.0740832 0.0740249 0.2494030 0.3618540 5339
23 154930487 rs781879 T A 0.1330810 0.0475809 0.0051776 0.0051589 0.0180415 0.1263580 5339

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.107413 ES:SE:LP:AF:SS:ID   -0.0282483:0.0253158:0.577507:0.107413:5339:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.113279 ES:SE:LP:AF:SS:ID   -0.0393566:0.0240479:0.992355:0.113279:5339:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0935047    ES:SE:LP:AF:SS:ID   -0.0487604:0.0272952:1.13024:0.0935047:5339:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0142136    ES:SE:LP:AF:SS:ID   0.0241439:0.0659415:0.146135:0.0142136:5339:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00177862   ES:SE:LP:AF:SS:ID   -0.128114:0.178305:0.325621:0.00177862:5339:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568113    ES:SE:LP:AF:SS:ID   -0.0450169:0.0327863:0.77007:0.0568113:5339:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.118717 ES:SE:LP:AF:SS:ID   -0.0402849:0.0227582:1.11485:0.118717:5339:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.116839 ES:SE:LP:AF:SS:ID   -0.0357702:0.0245004:0.840574:0.116839:5339:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.118112 ES:SE:LP:AF:SS:ID   -0.0392911:0.0227588:1.07401:0.118112:5339:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00507622   ES:SE:LP:AF:SS:ID   -0.143861:0.111868:0.702229:0.00507622:5339:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00151016   ES:SE:LP:AF:SS:ID   0.103352:0.232299:0.182829:0.00151016:5339:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.873263 ES:SE:LP:AF:SS:ID   0.0241256:0.0225739:0.544794:0.873263:5339:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00175843   ES:SE:LP:AF:SS:ID   -0.578795:0.177575:2.94948:0.00175843:5339:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.119425 ES:SE:LP:AF:SS:ID   -0.018949:0.0223488:0.401706:0.119425:5339:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.138761 ES:SE:LP:AF:SS:ID   -0.0140126:0.0220003:0.280504:0.138761:5339:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.11939  ES:SE:LP:AF:SS:ID   -0.0177208:0.0223351:0.368986:0.11939:5339:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.874527 ES:SE:LP:AF:SS:ID   0.0164283:0.0217044:0.347621:0.874527:5339:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.879636 ES:SE:LP:AF:SS:ID   0.0175385:0.0221169:0.36874:0.879636:5339:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12543  ES:SE:LP:AF:SS:ID   -0.0182637:0.0217606:0.396488:0.12543:5339:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0360554    ES:SE:LP:AF:SS:ID   -0.0466026:0.0387206:0.640521:0.0360554:5339:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.873809 ES:SE:LP:AF:SS:ID   0.0172376:0.0216754:0.370082:0.873809:5339:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.873859 ES:SE:LP:AF:SS:ID   0.0175233:0.0216763:0.377898:0.873859:5339:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.873856 ES:SE:LP:AF:SS:ID   0.0174802:0.0216744:0.376754:0.873856:5339:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0047512    ES:SE:LP:AF:SS:ID   0.232286:0.113116:1.39718:0.0047512:5339:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00469758   ES:SE:LP:AF:SS:ID   0.231297:0.113351:1.38356:0.00469758:5339:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00569689   ES:SE:LP:AF:SS:ID   0.0133051:0.104177:0.0465409:0.00569689:5339:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.874191 ES:SE:LP:AF:SS:ID   0.0160958:0.0216356:0.34014:0.874191:5339:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12245  ES:SE:LP:AF:SS:ID   -0.0162312:0.0221117:0.334469:0.12245:5339:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.873665 ES:SE:LP:AF:SS:ID   0.0146975:0.0215839:0.304575:0.873665:5339:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.872702 ES:SE:LP:AF:SS:ID   0.0153146:0.0215572:0.321046:0.872702:5339:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.873759 ES:SE:LP:AF:SS:ID   0.0150511:0.0215988:0.313428:0.873759:5339:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.873765 ES:SE:LP:AF:SS:ID   0.0150729:0.021601:0.313954:0.873765:5339:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.873771 ES:SE:LP:AF:SS:ID   0.015061:0.0216011:0.313642:0.873771:5339:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.874487 ES:SE:LP:AF:SS:ID   0.0148917:0.02167:0.308048:0.874487:5339:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0959117    ES:SE:LP:AF:SS:ID   -0.0333266:0.0252151:0.729722:0.0959117:5339:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00660805   ES:SE:LP:AF:SS:ID   0.000291774:0.0942316:0.00107403:0.00660805:5339:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.879044 ES:SE:LP:AF:SS:ID   0.0194532:0.0220683:0.422408:0.879044:5339:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.867772 ES:SE:LP:AF:SS:ID   0.0213808:0.0215274:0.493953:0.867772:5339:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.872854 ES:SE:LP:AF:SS:ID   0.0163584:0.0217684:0.344477:0.872854:5339:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.869571 ES:SE:LP:AF:SS:ID   0.0138583:0.0217611:0.280455:0.869571:5339:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0954897    ES:SE:LP:AF:SS:ID   -0.0154197:0.0260779:0.256216:0.0954897:5339:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.875173 ES:SE:LP:AF:SS:ID   0.0202122:0.0220672:0.444011:0.875173:5339:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.875172 ES:SE:LP:AF:SS:ID   0.0202131:0.0220672:0.444035:0.875172:5339:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87517  ES:SE:LP:AF:SS:ID   0.0202038:0.0220673:0.443766:0.87517:5339:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.875767 ES:SE:LP:AF:SS:ID   0.0196979:0.0221171:0.428087:0.875767:5339:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.121675 ES:SE:LP:AF:SS:ID   -0.0194989:0.0221459:0.421772:0.121675:5339:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.104186 ES:SE:LP:AF:SS:ID   -0.0319347:0.0238769:0.742024:0.104186:5339:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.860639 ES:SE:LP:AF:SS:ID   0.0187932:0.0215925:0.415506:0.860639:5339:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00167836   ES:SE:LP:AF:SS:ID   -0.132555:0.178661:0.338986:0.00167836:5339:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839474 ES:SE:LP:AF:SS:ID   -0.0122212:0.0207785:0.254576:0.839474:5339:rs376645387