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-20533/ukb-d-20533.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-20533/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 17:09:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20533/ukb-d-20533.vcf.gz ...
Read summary statistics for 13550919 SNPs.
Dropped 12663 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, 1283498 SNPs remain.
After merging with regression SNP LD, 1283498 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0414 (0.0094)
Lambda GC: 1.0311
Mean Chi^2: 1.0344
Intercept: 0.9973 (0.0063)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:11:28 2019
Total time elapsed: 2.0m:14.54s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0199,
    "mean_EFFECT": -7.7897e-06,
    "n": 45540,
    "n_snps": 13550919,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "n_mono": 0,
    "n_ns": 1250594,
    "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": 559710,
    "n_est": 45660.7289,
    "ratio_se_n": 1.0013,
    "mean_diff": -6.9459e-06,
    "ratio_diff": 2.0804,
    "sd_y_est1": 0.4304,
    "sd_y_est2": 0.431,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0007,
    "ldsc_nsnp_merge_refpanel_ld": 1283498,
    "ldsc_nsnp_merge_regression_ld": 1283498,
    "ldsc_observed_scale_h2_beta": 0.0414,
    "ldsc_observed_scale_h2_se": 0.0094,
    "ldsc_intercept_beta": 0.9973,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0311,
    "ldsc_mean_chisq": 1.0344,
    "ldsc_ratio": -0.0785
}

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 13538919 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57019 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33323 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051614e+00 6.185017e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902395e+07 5.591775e+07 3.02000e+02 3.292543e+07 7.013602e+07 1.148575e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -7.800000e-06 1.653520e-02 -2.20137e-01 -4.378500e-03 2.740000e-05 4.459200e-03 1.880570e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.190560e-02 1.146400e-02 2.44430e-03 3.408400e-03 6.260300e-03 1.708280e-02 6.324230e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.972019e-01 2.898027e-01 0.00000e+00 2.452652e-01 4.957594e-01 7.487296e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.971984e-01 2.898048e-01 0.00000e+00 2.452585e-01 4.957567e-01 7.487273e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.912683e-01 2.545124e-01 1.00000e-03 7.554000e-03 6.059090e-02 2.962890e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 559710 0.9586958 NA NA NA NA NA 1.966727e-01 2.471679e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.087060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 4.554000e+04 0.000000e+00 4.55400e+04 4.554000e+04 4.554000e+04 4.554000e+04 4.554000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0021775 0.0049722 0.6614439 0.6614412 0.1119100 0.1894970 45540
1 693731 rs12238997 A G 0.0020697 0.0046911 0.6590752 0.6590732 0.1172340 0.1417730 45540
1 707522 rs371890604 G C 0.0012473 0.0052587 0.8125171 0.8125162 0.0989953 0.1293930 45540
1 717587 rs144155419 G A -0.0006819 0.0126786 0.9571110 0.9571105 0.0156843 0.0045926 45540
1 723329 rs189787166 A T -0.0128175 0.0368136 0.7277128 0.7277103 0.0017920 0.0003994 45540
1 730087 rs148120343 T C 0.0066428 0.0065513 0.3106061 0.3106008 0.0568549 0.0127796 45540
1 731718 rs142557973 T C 0.0010837 0.0044499 0.8075970 0.8075955 0.1231910 0.1543530 45540
1 732032 rs61770163 A C 0.0001356 0.0047416 0.9771821 0.9771819 0.1226120 0.1555510 45540
1 734349 rs141242758 T C 0.0009920 0.0044508 0.8236240 0.8236227 0.1225270 0.1525560 45540
1 740284 rs61770167 C T -0.0043281 0.0200496 0.8290891 0.8290878 0.0060200 0.0023962 45540
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0019487 0.0053968 0.7180456 0.7180439 0.0559848 0.0309934 45540
23 154923374 rs111332691 T A -0.0006443 0.0059986 0.9144680 0.9144679 0.0435881 0.0116556 45540
23 154925045 rs509981 C T -0.0040353 0.0028492 0.1566910 0.1566840 0.2457860 0.3634440 45540
23 154925895 rs538470 C T -0.0043557 0.0029138 0.1349631 0.1349557 0.2422210 0.3634440 45540
23 154927581 rs644138 G A -0.0040524 0.0026793 0.1304121 0.1304044 0.3022470 0.4635760 45540
23 154929412 rs557132 C T -0.0040461 0.0028499 0.1556840 0.1556773 0.2456640 0.3568210 45540
23 154929637 rs35185538 CT C -0.0039463 0.0029782 0.1851561 0.1851505 0.2296840 0.3011920 45540
23 154929952 rs4012982 CAA C -0.0028237 0.0030036 0.3471778 0.3471735 0.2394930 0.3165560 45540
23 154930230 rs781880 A G -0.0040186 0.0028492 0.1584211 0.1584142 0.2460210 0.3618540 45540
23 154930487 rs781879 T A -0.0106014 0.0097468 0.2767400 0.2767354 0.0193766 0.1263580 45540

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11191  ES:SE:LP:AF:SS:ID   0.00217746:0.00497223:0.179507:0.11191:45540:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117234 ES:SE:LP:AF:SS:ID   0.00206969:0.00469112:0.181065:0.117234:45540:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0989953    ES:SE:LP:AF:SS:ID   0.00124726:0.00525868:0.0901675:0.0989953:45540:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156843    ES:SE:LP:AF:SS:ID   -0.000681855:0.0126786:0.0190377:0.0156843:45540:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00179196   ES:SE:LP:AF:SS:ID   -0.0128175:0.0368136:0.13804:0.00179196:45540:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568549    ES:SE:LP:AF:SS:ID   0.00664275:0.00655128:0.50779:0.0568549:45540:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123191 ES:SE:LP:AF:SS:ID   0.00108369:0.00444994:0.0928053:0.123191:45540:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122612 ES:SE:LP:AF:SS:ID   0.00013562:0.00474161:0.0100245:0.122612:45540:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122527 ES:SE:LP:AF:SS:ID   0.000992032:0.00445081:0.084271:0.122527:45540:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00602  ES:SE:LP:AF:SS:ID   -0.00432814:0.0200496:0.0813988:0.00602:45540:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018522    ES:SE:LP:AF:SS:ID   0.0402372:0.0389239:0.521053:0.0018522:45540:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868242 ES:SE:LP:AF:SS:ID   -0.00361638:0.00438092:0.388168:0.868242:45540:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00162197   ES:SE:LP:AF:SS:ID   0.046851:0.0388377:0.642641:0.00162197:45540:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124643 ES:SE:LP:AF:SS:ID   0.00357105:0.00433734:0.386871:0.124643:45540:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144077 ES:SE:LP:AF:SS:ID   0.0026071:0.0042964:0.264417:0.144077:45540:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124737 ES:SE:LP:AF:SS:ID   0.00355107:0.00433156:0.384758:0.124737:45540:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868906 ES:SE:LP:AF:SS:ID   -0.00305134:0.00422208:0.32803:0.868906:45540:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873626 ES:SE:LP:AF:SS:ID   -0.00381621:0.00429051:0.427404:0.873626:45540:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130541 ES:SE:LP:AF:SS:ID   0.00298503:0.00423276:0.318147:0.130541:45540:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0370334    ES:SE:LP:AF:SS:ID   -0.00559805:0.00766755:0.332234:0.0370334:45540:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868516 ES:SE:LP:AF:SS:ID   -0.00305272:0.00421768:0.328645:0.868516:45540:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868563 ES:SE:LP:AF:SS:ID   -0.00314365:0.00421839:0.340902:0.868563:45540:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868519 ES:SE:LP:AF:SS:ID   -0.00301273:0.00421757:0.323281:0.868519:45540:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00523349   ES:SE:LP:AF:SS:ID   0.0147932:0.0214002:0.310334:0.00523349:45540:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00520469   ES:SE:LP:AF:SS:ID   0.0147401:0.021448:0.308098:0.00520469:45540:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00579021   ES:SE:LP:AF:SS:ID   -0.000497981:0.0206656:0.00843061:0.00579021:45540:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868542 ES:SE:LP:AF:SS:ID   -0.00331512:0.00420966:0.365531:0.868542:45540:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127831 ES:SE:LP:AF:SS:ID   0.00364025:0.00429583:0.401448:0.127831:45540:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868061 ES:SE:LP:AF:SS:ID   -0.00329859:0.00419905:0.364385:0.868061:45540:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867535 ES:SE:LP:AF:SS:ID   -0.00337647:0.00419724:0.375571:0.867535:45540:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868251 ES:SE:LP:AF:SS:ID   -0.00321392:0.00420272:0.352187:0.868251:45540:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868258 ES:SE:LP:AF:SS:ID   -0.00321097:0.00420302:0.351746:0.868258:45540:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868261 ES:SE:LP:AF:SS:ID   -0.00319965:0.00420305:0.350178:0.868261:45540:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868695 ES:SE:LP:AF:SS:ID   -0.00309622:0.0042141:0.33488:0.868695:45540:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100503 ES:SE:LP:AF:SS:ID   0.00394365:0.00489314:0.376467:0.100503:45540:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00682163   ES:SE:LP:AF:SS:ID   0.000637472:0.0185614:0.0120644:0.00682163:45540:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872853 ES:SE:LP:AF:SS:ID   -0.00358502:0.00427965:0.395547:0.872853:45540:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862109 ES:SE:LP:AF:SS:ID   -0.00317471:0.00419601:0.34747:0.862109:45540:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867419 ES:SE:LP:AF:SS:ID   -0.00343722:0.00423793:0.379516:0.867419:45540:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864621 ES:SE:LP:AF:SS:ID   -0.00424362:0.00424283:0.498631:0.864621:45540:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100688 ES:SE:LP:AF:SS:ID   0.00174561:0.00505833:0.136663:0.100688:45540:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869686 ES:SE:LP:AF:SS:ID   -0.00371494:0.00428807:0.413067:0.869686:45540:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869686 ES:SE:LP:AF:SS:ID   -0.00371542:0.00428807:0.413136:0.869686:45540:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869682 ES:SE:LP:AF:SS:ID   -0.00371166:0.00428808:0.412596:0.869682:45540:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870001 ES:SE:LP:AF:SS:ID   -0.00372012:0.00428984:0.413592:0.870001:45540:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127405 ES:SE:LP:AF:SS:ID   0.00316919:0.00429302:0.336879:0.127405:45540:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107055 ES:SE:LP:AF:SS:ID   0.00203234:0.00466904:0.178249:0.107055:45540:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853126 ES:SE:LP:AF:SS:ID   -0.00252814:0.0041916:0.262477:0.853126:45540:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00171256   ES:SE:LP:AF:SS:ID   -0.0239883:0.0369149:0.287513:0.00171256:45540:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837478 ES:SE:LP:AF:SS:ID   0.00222988:0.00416967:0.227091:0.837478:45540:rs376645387