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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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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-100920_2102/ukb-d-100920_2102.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-100920_2102/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 14:53:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-100920_2102/ukb-d-100920_2102.vcf.gz ...
Read summary statistics for 13550213 SNPs.
Dropped 12661 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, 1283501 SNPs remain.
After merging with regression SNP LD, 1283501 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0207 (0.0091)
Lambda GC: 1.0139
Mean Chi^2: 1.018
Intercept: 0.9974 (0.0061)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 14:56:14 2019
Total time elapsed: 2.0m:43.77s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0076,
    "mean_EFFECT": -0,
    "n": 51427,
    "n_snps": 13550213,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250634,
    "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": 558023,
    "n_est": 51639.4465,
    "ratio_se_n": 1.0021,
    "mean_diff": -0,
    "ratio_diff": 11.3911,
    "sd_y_est1": 0.4854,
    "sd_y_est2": 0.4864,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283501,
    "ldsc_nsnp_merge_regression_ld": 1283501,
    "ldsc_observed_scale_h2_beta": 0.0207,
    "ldsc_observed_scale_h2_se": 0.0091,
    "ldsc_intercept_beta": 0.9974,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0139,
    "ldsc_mean_chisq": 1.018,
    "ldsc_ratio": -0.1444
}

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 13538215 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57023 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33319 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051468e+00 6.184826e+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 7.902490e+07 5.591852e+07 3.02000e+02 3.292677e+07 7.013539e+07 1.148604e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.920000e-05 1.755030e-02 -2.14149e-01 -4.663000e-03 -7.400000e-06 4.667200e-03 2.160100e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.262380e-02 1.215670e-02 2.49040e-03 3.616200e-03 6.638500e-03 1.810840e-02 6.320740e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.986535e-01 2.896742e-01 2.00000e-07 2.471980e-01 4.983839e-01 7.499598e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.986504e-01 2.896761e-01 2.00000e-07 2.471928e-01 4.983813e-01 7.499590e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.912999e-01 2.545267e-01 1.00000e-03 7.571900e-03 6.060870e-02 2.962430e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 558023 0.9588181 NA NA NA NA NA 1.966848e-01 2.471857e-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 5.142700e+04 0.000000e+00 5.14270e+04 5.142700e+04 5.142700e+04 5.142700e+04 5.142700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0006108 0.0052664 0.9076751 0.9076744 0.1121000 0.1894970 51427
1 693731 rs12238997 A G 0.0031131 0.0050046 0.5339136 0.5339113 0.1168090 0.1417730 51427
1 707522 rs371890604 G C 0.0059140 0.0056130 0.2920573 0.2920518 0.0982930 0.1293930 51427
1 717587 rs144155419 G A -0.0081222 0.0135695 0.5494688 0.5494658 0.0154808 0.0045926 51427
1 723329 rs189787166 A T -0.0189395 0.0385665 0.6233687 0.6233650 0.0017973 0.0003994 51427
1 730087 rs148120343 T C 0.0067298 0.0069694 0.3342358 0.3342317 0.0570822 0.0127796 51427
1 731718 rs142557973 T C 0.0010781 0.0047558 0.8206729 0.8206721 0.1225210 0.1543530 51427
1 732032 rs61770163 A C 0.0000449 0.0050697 0.9929410 0.9929410 0.1216510 0.1555510 51427
1 734349 rs141242758 T C 0.0011506 0.0047584 0.8089281 0.8089280 0.1217650 0.1525560 51427
1 740284 rs61770167 C T -0.0024550 0.0207953 0.9060261 0.9060256 0.0062329 0.0023962 51427
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0038876 0.0055951 0.4871705 0.4871663 0.0542488 0.0309934 51427
23 154923374 rs111332691 T A -0.0022856 0.0060608 0.7060915 0.7060891 0.0445389 0.0116556 51427
23 154925045 rs509981 C T 0.0022952 0.0029136 0.4308380 0.4308342 0.2434190 0.3634440 51427
23 154925895 rs538470 C T 0.0024228 0.0029763 0.4156368 0.4156331 0.2401390 0.3634440 51427
23 154927581 rs644138 G A 0.0031574 0.0027406 0.2492832 0.2492773 0.2981050 0.4635760 51427
23 154929412 rs557132 C T 0.0022062 0.0029146 0.4490813 0.4490787 0.2432580 0.3568210 51427
23 154929637 rs35185538 CT C 0.0022517 0.0030369 0.4584268 0.4584230 0.2278210 0.3011920 51427
23 154929952 rs4012982 CAA C 0.0018241 0.0030666 0.5519681 0.5519658 0.2374290 0.3165560 51427
23 154930230 rs781880 A G 0.0023689 0.0029134 0.4161597 0.4161570 0.2438260 0.3618540 51427
23 154930487 rs781879 T A -0.0076547 0.0101307 0.4498959 0.4498924 0.0189843 0.1263580 51427

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.1121   ES:SE:LP:AF:SS:ID   0.000610762:0.00526644:0.0420696:0.1121:51427:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116809 ES:SE:LP:AF:SS:ID   0.0031131:0.00500461:0.272529:0.116809:51427:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098293 ES:SE:LP:AF:SS:ID   0.00591399:0.00561296:0.534532:0.098293:51427:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154808    ES:SE:LP:AF:SS:ID   -0.00812217:0.0135695:0.260057:0.0154808:51427:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00179726   ES:SE:LP:AF:SS:ID   -0.0189395:0.0385665:0.205255:0.00179726:51427:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570822    ES:SE:LP:AF:SS:ID   0.00672982:0.00696939:0.475947:0.0570822:51427:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122521 ES:SE:LP:AF:SS:ID   0.00107805:0.00475581:0.0858299:0.122521:51427:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121651 ES:SE:LP:AF:SS:ID   4.48528e-05:0.00506969:0.00307656:0.121651:51427:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121765 ES:SE:LP:AF:SS:ID   0.00115062:0.00475838:0.0920901:0.121765:51427:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0062329    ES:SE:LP:AF:SS:ID   -0.00245495:0.0207953:0.0428593:0.0062329:51427:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00176649   ES:SE:LP:AF:SS:ID   -0.0741502:0.0432115:1.06464:0.00176649:51427:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868613 ES:SE:LP:AF:SS:ID   -0.00221156:0.00468419:0.195973:0.868613:51427:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00158492   ES:SE:LP:AF:SS:ID   0.00562207:0.04203:0.0488617:0.00158492:51427:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123957 ES:SE:LP:AF:SS:ID   0.00152422:0.00464036:0.12927:0.123957:51427:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143385 ES:SE:LP:AF:SS:ID   0.000945399:0.00460394:0.0771174:0.143385:51427:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124126 ES:SE:LP:AF:SS:ID   0.00154185:0.00463265:0.131198:0.124126:51427:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869933 ES:SE:LP:AF:SS:ID   2.85631e-05:0.00451496:0.00219787:0.869933:51427:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874426 ES:SE:LP:AF:SS:ID   -0.0013985:0.00458673:0.118933:0.874426:51427:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129659 ES:SE:LP:AF:SS:ID   0.00112161:0.00452608:0.0945911:0.129659:51427:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0369164    ES:SE:LP:AF:SS:ID   -0.0206743:0.00815156:1.95047:0.0369164:51427:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869554 ES:SE:LP:AF:SS:ID   -0.000379213:0.00451074:0.0301174:0.869554:51427:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869648 ES:SE:LP:AF:SS:ID   -0.000523156:0.00451309:0.0420495:0.869648:51427:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   -0.000397561:0.00451074:0.0316254:0.86957:51427:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00531261   ES:SE:LP:AF:SS:ID   0.0167995:0.0226079:0.33967:0.00531261:51427:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00527727   ES:SE:LP:AF:SS:ID   0.0172281:0.0226673:0.349467:0.00527727:51427:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0057746    ES:SE:LP:AF:SS:ID   0.0336898:0.0221074:0.894367:0.0057746:51427:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869706 ES:SE:LP:AF:SS:ID   -0.000481263:0.00450393:0.038624:0.869706:51427:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12702  ES:SE:LP:AF:SS:ID   0.00259114:0.0045935:0.242075:0.12702:51427:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   -0.000483358:0.00449209:0.0389056:0.869213:51427:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868449 ES:SE:LP:AF:SS:ID   -0.000867303:0.00448774:0.0722417:0.868449:51427:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   -0.000421756:0.00449705:0.0337268:0.869419:51427:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869426 ES:SE:LP:AF:SS:ID   -0.000419004:0.00449734:0.0334964:0.869426:51427:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   -0.000439315:0.00449755:0.0351805:0.869437:51427:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869848 ES:SE:LP:AF:SS:ID   -0.000528562:0.00450805:0.0425536:0.869848:51427:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0999077    ES:SE:LP:AF:SS:ID   0.00315684:0.00522778:0.262855:0.0999077:51427:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00659027   ES:SE:LP:AF:SS:ID   0.0303005:0.0200798:0.881722:0.00659027:51427:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87358  ES:SE:LP:AF:SS:ID   -0.00182123:0.00457317:0.160866:0.87358:51427:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86295  ES:SE:LP:AF:SS:ID   -0.000984706:0.00448653:0.0828743:0.86295:51427:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868667 ES:SE:LP:AF:SS:ID   -0.000646406:0.00453053:0.0522992:0.868667:51427:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.8652   ES:SE:LP:AF:SS:ID   -0.00100046:0.00452853:0.0834655:0.8652:51427:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0992889    ES:SE:LP:AF:SS:ID   0.000237179:0.005435:0.0153863:0.0992889:51427:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   -0.00182062:0.00457942:0.160552:0.870459:51427:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   -0.00182107:0.00457942:0.160597:0.870459:51427:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870456 ES:SE:LP:AF:SS:ID   -0.00181992:0.00457944:0.16048:0.870456:51427:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870829 ES:SE:LP:AF:SS:ID   -0.0018006:0.00458205:0.158425:0.870829:51427:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126636 ES:SE:LP:AF:SS:ID   0.00219225:0.00458716:0.198791:0.126636:51427:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106247 ES:SE:LP:AF:SS:ID   0.00282155:0.00499549:0.242453:0.106247:51427:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854084 ES:SE:LP:AF:SS:ID   -0.00265141:0.00448604:0.256099:0.854084:51427:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00168817   ES:SE:LP:AF:SS:ID   -0.0260233:0.0389066:0.297928:0.00168817:51427:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836377 ES:SE:LP:AF:SS:ID   -0.00583524:0.00439329:0.734918:0.836377:51427:rs376645387