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/public/UKB-b-18436/UKB-b-18436_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18436/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18436/UKB-b-18436_data.vcf.gz ...
Read summary statistics for 6457608 SNPs.
Dropped 3457 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1241414 SNPs remain.
After merging with regression SNP LD, 1241414 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1296 (0.037)
Lambda GC: 1.026
Mean Chi^2: 1.0429
Intercept: 1.0058 (0.0064)
Ratio: 0.1347 (0.1485)
Analysis finished at Thu Oct 17 14:41:31 2019
Total time elapsed: 1.0m:13.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9303,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 238,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 59226,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1241414,
    "ldsc_nsnp_merge_regression_ld": 1241414,
    "ldsc_observed_scale_h2_beta": 0.1296,
    "ldsc_observed_scale_h2_se": 0.037,
    "ldsc_intercept_beta": 1.0058,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.026,
    "ldsc_mean_chisq": 1.0429,
    "ldsc_ratio": 0.1352
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 6454172 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 6457608 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.667283e+00 5.763972e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.856205e+07 5.648331e+07 828.0000000 3.202118e+07 6.899286e+07 1.144559e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.130000e-05 2.037020e-02 -0.2232510 -1.160330e-02 -6.320000e-05 1.154150e-02 1.719280e-01 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.866250e-02 7.348100e-03 0.0113413 1.268630e-02 1.569330e-02 2.283890e-02 9.427280e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.949134e-01 2.910166e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.949148e-01 2.909916e-01 0.0000000 2.413014e-01 4.931343e-01 7.474682e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.946410e-01 2.571469e-01 0.0245050 7.806800e-02 2.058800e-01 4.567150e-01 9.754950e-01 ▇▃▂▂▁
numeric AF_reference 59226 0.9908285 NA NA NA NA NA NA NA 2.920772e-01 2.495702e-01 0.0000000 8.746010e-02 2.154550e-01 4.484820e-01 1.000000e+00 ▇▃▂▂▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C 0.0061481 0.0210885 0.7700005 0.7706406 0.625675 0.7821490 NA
1 54676 rs2462492 C T 0.0228806 0.0206946 0.2700001 0.2688861 0.399123 NA NA
1 86028 rs114608975 T C -0.0384221 0.0332012 0.2500000 0.2471701 0.103932 0.0277556 NA
1 91536 rs6702460 G T 0.0207631 0.0204098 0.3100002 0.3090058 0.459145 0.4207270 NA
1 234313 rs8179466 C T -0.0128327 0.0393693 0.7400005 0.7444569 0.075888 NA NA
1 534192 rs6680723 C T -0.0108219 0.0234930 0.6499995 0.6450543 0.240110 NA NA
1 546697 rs12025928 A G -0.0397209 0.0292812 0.1700000 0.1749298 0.913809 NA NA
1 693731 rs12238997 A G 0.0061390 0.0197122 0.7600007 0.7554726 0.115903 0.1417730 NA
1 705882 rs72631875 G A 0.0209657 0.0287282 0.4700002 0.4655154 0.067030 0.0315495 NA
1 706368 rs55727773 A G -0.0084982 0.0144912 0.5600000 0.5575784 0.514457 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0264287 0.0229393 0.2500000 0.2492740 0.073134 0.0826677 NA
22 51219006 rs28729663 G A 0.0109386 0.0176584 0.5400003 0.5356161 0.136561 0.2052720 NA
22 51219387 rs9616832 T C 0.0284097 0.0229588 0.2200002 0.2159308 0.073344 0.0654952 NA
22 51219704 rs147475742 G A 0.0107346 0.0307452 0.7300002 0.7269788 0.041781 0.0473243 NA
22 51221190 rs369304721 G A 0.0537504 0.0309568 0.0830004 0.0825102 0.049230 NA NA
22 51221731 rs115055839 T C 0.0279378 0.0229831 0.2200002 0.2241449 0.072838 0.0625000 NA
22 51222100 rs114553188 G T -0.0000438 0.0268072 1.0000000 0.9986961 0.053953 0.0880591 NA
22 51223637 rs375798137 G A -0.0014808 0.0269213 0.9599999 0.9561335 0.053712 0.0788738 NA
22 51229805 rs9616985 T C 0.0295436 0.0230926 0.2000000 0.2007726 0.072504 0.0730831 NA
22 51237063 rs3896457 T C -0.0039540 0.0138675 0.7800007 0.7755451 0.296582 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.625675 ES:SE:LP:AF:ID  0.00614808:0.0210885:0.113509:0.625675:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399123 ES:SE:LP:AF:ID  0.0228806:0.0206946:0.568636:0.399123:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103932 ES:SE:LP:AF:ID  -0.0384221:0.0332012:0.60206:0.103932:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.459145 ES:SE:LP:AF:ID  0.0207631:0.0204098:0.508638:0.459145:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.075888 ES:SE:LP:AF:ID  -0.0128327:0.0393693:0.130768:0.075888:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24011  ES:SE:LP:AF:ID  -0.0108219:0.023493:0.187087:0.24011:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913809 ES:SE:LP:AF:ID  -0.0397209:0.0292812:0.769551:0.913809:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115903 ES:SE:LP:AF:ID  0.006139:0.0197122:0.119186:0.115903:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06703  ES:SE:LP:AF:ID  0.0209657:0.0287282:0.327902:0.06703:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514457 ES:SE:LP:AF:ID  -0.00849825:0.0144912:0.251812:0.514457:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032147 ES:SE:LP:AF:ID  -0.0411469:0.0368556:0.585027:0.032147:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.035329 ES:SE:LP:AF:ID  -0.0340089:0.0337384:0.508638:0.035329:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.035499 ES:SE:LP:AF:ID  -0.0341657:0.0335606:0.508638:0.035499:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035157 ES:SE:LP:AF:ID  -0.0315842:0.033829:0.455932:0.035157:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.035719 ES:SE:LP:AF:ID  -0.0277868:0.0334465:0.387216:0.035719:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.035896 ES:SE:LP:AF:ID  -0.0300695:0.0332749:0.431798:0.035896:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101563 ES:SE:LP:AF:ID  0.0200231:0.0238578:0.39794:0.101563:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.960634 ES:SE:LP:AF:ID  0.0320294:0.0321944:0.49485:0.960634:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03168  ES:SE:LP:AF:ID  -0.0517773:0.0570734:0.443698:0.03168:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052511 ES:SE:LP:AF:ID  -0.00801766:0.0456615:0.0655015:0.052511:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.035519 ES:SE:LP:AF:ID  -0.0315093:0.0334009:0.455932:0.035519:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.035898 ES:SE:LP:AF:ID  -0.0237625:0.0331016:0.327902:0.035898:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.844642 ES:SE:LP:AF:ID  0.0010418:0.017105:0.0222764:0.844642:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055444 ES:SE:LP:AF:ID  0.0157806:0.02756:0.244125:0.055444:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121753 ES:SE:LP:AF:ID  0.0100123:0.018671:0.229148:0.121753:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.024539 ES:SE:LP:AF:ID  -0.0176396:0.0467784:0.148742:0.024539:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121047 ES:SE:LP:AF:ID  0.00946676:0.0186698:0.21467:0.121047:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.131135 ES:SE:LP:AF:ID  0.0059902:0.0185085:0.124939:0.131135:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.035444 ES:SE:LP:AF:ID  -0.0224945:0.0329181:0.309804:0.035444:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839829 ES:SE:LP:AF:ID  0.00272621:0.0165264:0.0604807:0.839829:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.839367 ES:SE:LP:AF:ID  0.00406253:0.0165068:0.091515:0.839367:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869547 ES:SE:LP:AF:ID  -0.00481433:0.0176056:0.107905:0.869547:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130237 ES:SE:LP:AF:ID  0.00494265:0.0176721:0.107905:0.130237:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036024 ES:SE:LP:AF:ID  -0.0224676:0.0323364:0.309804:0.036024:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.036307 ES:SE:LP:AF:ID  -0.0227189:0.0321039:0.318759:0.036307:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868845 ES:SE:LP:AF:ID  -0.00368601:0.0175771:0.0809219:0.868845:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868929 ES:SE:LP:AF:ID  -0.0033285:0.0175825:0.0705811:0.868929:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.036166 ES:SE:LP:AF:ID  -0.0226996:0.0322973:0.318759:0.036166:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868833 ES:SE:LP:AF:ID  -0.00371647:0.017576:0.0809219:0.868833:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838719 ES:SE:LP:AF:ID  0.00400955:0.0164524:0.091515:0.838719:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03622  ES:SE:LP:AF:ID  -0.0228265:0.0323207:0.318759:0.03622:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839193 ES:SE:LP:AF:ID  0.00393927:0.0164921:0.091515:0.839193:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.84034  ES:SE:LP:AF:ID  0.00327093:0.0166902:0.0757207:0.84034:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869186 ES:SE:LP:AF:ID  -0.00569197:0.0175542:0.124939:0.869186:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868742 ES:SE:LP:AF:ID  -0.00707921:0.0175109:0.161151:0.868742:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867683 ES:SE:LP:AF:ID  -0.00699811:0.0174758:0.161151:0.867683:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868823 ES:SE:LP:AF:ID  -0.00720933:0.0175262:0.167491:0.868823:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868832 ES:SE:LP:AF:ID  -0.00726089:0.0175282:0.167491:0.868832:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868829 ES:SE:LP:AF:ID  -0.00719957:0.0175276:0.167491:0.868829:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869295 ES:SE:LP:AF:ID  -0.00577924:0.0175641:0.130768:0.869295:rs3131954