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/public/UKB-b-15787/UKB-b-15787_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15787/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15787/UKB-b-15787_data.vcf.gz ...
Read summary statistics for 6873285 SNPs.
Dropped 4115 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, 1259344 SNPs remain.
After merging with regression SNP LD, 1259344 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0345 (0.0025)
Lambda GC: 1.1859
Mean Chi^2: 1.2024
Intercept: 1.0369 (0.007)
Ratio: 0.1821 (0.0344)
Analysis finished at Thu Oct 17 14:45:49 2019
Total time elapsed: 1.0m:23.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9347,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -7.6728e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 7,
    "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": 63214,
    "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": 1259344,
    "ldsc_nsnp_merge_regression_ld": 1259344,
    "ldsc_observed_scale_h2_beta": 0.0345,
    "ldsc_observed_scale_h2_se": 0.0025,
    "ldsc_intercept_beta": 1.0369,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.1859,
    "ldsc_mean_chisq": 1.2024,
    "ldsc_ratio": 0.1823
}

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 6869192 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 6873285 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 8.664060e+00 5.764479e+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 7.862528e+07 5.646412e+07 828.0000000 3.211747e+07 6.906584e+07 1.145195e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -7.700000e-06 1.515100e-03 -0.0131793 -8.406000e-04 -1.120000e-05 8.268000e-04 1.324720e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.295700e-03 5.816000e-04 0.0007353 8.274000e-04 1.053900e-03 1.617900e-03 7.321200e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.740650e-01 2.952702e-01 0.0000000 2.099999e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.740656e-01 2.952457e-01 0.0000000 2.112399e-01 4.656376e-01 7.295188e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.800796e-01 2.592547e-01 0.0182500 6.370900e-02 1.854520e-01 4.383960e-01 9.817500e-01 ▇▃▂▁▁
numeric AF_reference 63214 0.9908029 NA NA NA NA NA NA NA 2.781899e-01 2.513455e-01 0.0000000 7.208470e-02 1.970850e-01 4.307110e-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 0.0006252 0.0013533 0.6400000 0.6440796 0.623695 0.7821490 NA
1 54676 rs2462492 C T 0.0006274 0.0013397 0.6400000 0.6395478 0.400681 NA NA
1 86028 rs114608975 T C -0.0029771 0.0021414 0.1600000 0.1644391 0.103516 0.0277556 NA
1 91536 rs6702460 G T 0.0021209 0.0013206 0.1100001 0.1082555 0.456668 0.4207270 NA
1 234313 rs8179466 C T 0.0016413 0.0025915 0.5300002 0.5265118 0.074802 NA NA
1 534192 rs6680723 C T -0.0014525 0.0015081 0.3400001 0.3355073 0.240941 NA NA
1 546697 rs12025928 A G -0.0007167 0.0018830 0.6999999 0.7034974 0.913746 NA NA
1 693731 rs12238997 A G -0.0000196 0.0012603 0.9900000 0.9875931 0.116422 0.1417730 NA
1 705882 rs72631875 G A -0.0015375 0.0018557 0.4100001 0.4073906 0.066929 0.0315495 NA
1 706368 rs55727773 A G -0.0002382 0.0009349 0.8000000 0.7988828 0.515436 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0019179 0.0011264 0.0890000 0.0886436 0.138606 0.2052720 NA
22 51219387 rs9616832 T C -0.0010100 0.0014615 0.4899999 0.4895154 0.074194 0.0654952 NA
22 51219704 rs147475742 G A -0.0012573 0.0019556 0.5199996 0.5202872 0.042309 0.0473243 NA
22 51221190 rs369304721 G A -0.0011041 0.0019534 0.5700002 0.5719364 0.050099 NA NA
22 51221731 rs115055839 T C -0.0010919 0.0014624 0.4600002 0.4552618 0.073696 0.0625000 NA
22 51222100 rs114553188 G T -0.0024921 0.0017263 0.1499999 0.1488580 0.054577 0.0880591 NA
22 51223637 rs375798137 G A -0.0024430 0.0017347 0.1600000 0.1590388 0.054212 0.0788738 NA
22 51229805 rs9616985 T C -0.0011610 0.0014679 0.4299995 0.4289785 0.073513 0.0730831 NA
22 51232488 rs376461333 A G -0.0027728 0.0034661 0.4199997 0.4237212 0.020032 NA NA
22 51237063 rs3896457 T C 0.0000788 0.0009005 0.9299999 0.9302963 0.297423 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623695 ES:SE:LP:AF:ID  0.000625214:0.00135327:0.19382:0.623695:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400681 ES:SE:LP:AF:ID  0.000627442:0.00133974:0.19382:0.400681:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103516 ES:SE:LP:AF:ID  -0.00297711:0.00214135:0.79588:0.103516:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456668 ES:SE:LP:AF:ID  0.00212093:0.00132056:0.958607:0.456668:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074802 ES:SE:LP:AF:ID  0.0016413:0.0025915:0.275724:0.074802:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240941 ES:SE:LP:AF:ID  -0.00145245:0.00150813:0.468521:0.240941:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913746 ES:SE:LP:AF:ID  -0.000716669:0.00188298:0.154902:0.913746:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116422 ES:SE:LP:AF:ID  -1.95982e-05:0.0012603:0.00436481:0.116422:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066929 ES:SE:LP:AF:ID  -0.00153747:0.00185574:0.387216:0.066929:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515436 ES:SE:LP:AF:ID  -0.000238211:0.000934919:0.09691:0.515436:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033237 ES:SE:LP:AF:ID  0.00178551:0.00234991:0.346787:0.033237:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036836 ES:SE:LP:AF:ID  0.0010965:0.00213609:0.21467:0.036836:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036942 ES:SE:LP:AF:ID  0.00130291:0.00212872:0.267606:0.036942:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036658 ES:SE:LP:AF:ID  0.00107572:0.00214324:0.207608:0.036658:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.037204 ES:SE:LP:AF:ID  0.000930427:0.00211945:0.180456:0.037204:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037301 ES:SE:LP:AF:ID  0.00108117:0.00211238:0.21467:0.037301:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101051 ES:SE:LP:AF:ID  -0.000959864:0.00154544:0.275724:0.101051:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958793 ES:SE:LP:AF:ID  -0.00088228:0.00203475:0.180456:0.958793:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031537 ES:SE:LP:AF:ID  0.0029611:0.00369427:0.376751:0.031537:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053306 ES:SE:LP:AF:ID  0.000875451:0.00294173:0.113509:0.053306:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  0.00106635:0.00212646:0.207608:0.036808:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037114 ES:SE:LP:AF:ID  0.00124226:0.00210726:0.251812:0.037114:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842785 ES:SE:LP:AF:ID  -0.000321674:0.00109134:0.113509:0.842785:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055996 ES:SE:LP:AF:ID  -0.00103222:0.0017705:0.251812:0.055996:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122437 ES:SE:LP:AF:ID  0.000197005:0.00119506:0.0604807:0.122437:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025762 ES:SE:LP:AF:ID  -8.63806e-05:0.0029436:0.00877392:0.025762:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121649 ES:SE:LP:AF:ID  0.000181514:0.00119562:0.0555173:0.121649:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132632 ES:SE:LP:AF:ID  -0.000277045:0.00117859:0.091515:0.132632:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.037053 ES:SE:LP:AF:ID  0.000871591:0.00208541:0.167491:0.037053:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838548 ES:SE:LP:AF:ID  -0.000607809:0.00105717:0.244125:0.838548:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838134 ES:SE:LP:AF:ID  -0.000483369:0.00105586:0.187087:0.838134:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869551 ES:SE:LP:AF:ID  -0.000512601:0.00113313:0.187087:0.869551:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130136 ES:SE:LP:AF:ID  0.000393694:0.00113517:0.136677:0.130136:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037551 ES:SE:LP:AF:ID  0.00128646:0.00205001:0.275724:0.037551:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037804 ES:SE:LP:AF:ID  0.00119824:0.00203688:0.251812:0.037804:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868852 ES:SE:LP:AF:ID  -0.000444393:0.00113072:0.161151:0.868852:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86895  ES:SE:LP:AF:ID  -0.000386339:0.00113118:0.136677:0.86895:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037757 ES:SE:LP:AF:ID  0.00144414:0.00204593:0.318759:0.037757:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868857 ES:SE:LP:AF:ID  -0.00044655:0.00113073:0.161151:0.868857:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837569 ES:SE:LP:AF:ID  -0.000696528:0.00105293:0.29243:0.837569:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037772 ES:SE:LP:AF:ID  0.00153026:0.00204876:0.337242:0.037772:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838224 ES:SE:LP:AF:ID  -0.000718746:0.00105592:0.30103:0.838224:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839351 ES:SE:LP:AF:ID  -0.000916938:0.00107027:0.408935:0.839351:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  -0.000578414:0.00112951:0.21467:0.869154:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868702 ES:SE:LP:AF:ID  -0.000526497:0.00112665:0.19382:0.868702:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867609 ES:SE:LP:AF:ID  -0.000427482:0.00112428:0.154902:0.867609:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868849 ES:SE:LP:AF:ID  -0.000568153:0.00112763:0.21467:0.868849:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868858 ES:SE:LP:AF:ID  -0.000559166:0.00112771:0.207608:0.868858:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868868 ES:SE:LP:AF:ID  -0.000564748:0.00112774:0.207608:0.868868:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869344 ES:SE:LP:AF:ID  -0.000572359:0.00113085:0.21467:0.869344:rs3131954