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-20176/UKB-b-20176_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20176/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20176/UKB-b-20176_data.vcf.gz ...
Read summary statistics for 6746734 SNPs.
Dropped 3916 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, 1254482 SNPs remain.
After merging with regression SNP LD, 1254482 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0045 (0.0014)
Lambda GC: 1.1085
Mean Chi^2: 1.1085
Intercept: 1.0712 (0.0073)
Ratio: 0.656 (0.0674)
Analysis finished at Thu Oct 17 14:43:21 2019
Total time elapsed: 1.0m:14.35s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9334,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -2.7329e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 160,
    "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": 61960,
    "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": 1254482,
    "ldsc_nsnp_merge_regression_ld": 1254482,
    "ldsc_observed_scale_h2_beta": 0.0045,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0712,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.1085,
    "ldsc_mean_chisq": 1.1085,
    "ldsc_ratio": 0.6562
}

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 TRUE
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 6742840 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 6746734 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 8.663616e+00 5.764261e+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 7.861319e+07 5.647486e+07 828.0000000 3.209022e+07 6.906233e+07 1.145128e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.000000e-07 8.191000e-04 -0.0066673 -4.529000e-04 -2.300000e-06 4.511000e-04 9.894900e-03 ▁▇▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.208000e-04 3.113000e-04 0.0004180 4.694000e-04 5.923000e-04 8.951000e-04 3.660000e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.841598e-01 2.925649e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.841607e-01 2.925396e-01 0.0000000 2.267957e-01 4.785078e-01 7.372317e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.843867e-01 2.587122e-01 0.0199250 6.783900e-02 1.915660e-01 4.438458e-01 9.800750e-01 ▇▃▂▂▁
numeric AF_reference 61960 0.9908163 NA NA NA NA NA NA NA 2.822989e-01 2.508908e-01 0.0000000 7.667730e-02 2.024760e-01 4.361020e-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 0.0009009 0.0007697 0.2399999 0.2418135 0.623810 0.7821490 NA
1 54676 rs2462492 C T 0.0005746 0.0007619 0.4500005 0.4507519 0.400463 NA NA
1 86028 rs114608975 T C -0.0008200 0.0012180 0.5000000 0.5007921 0.103584 0.0277556 NA
1 91536 rs6702460 G T 0.0002892 0.0007504 0.6999999 0.6999138 0.456945 0.4207270 NA
1 234313 rs8179466 C T -0.0015338 0.0014806 0.2999998 0.3002473 0.074502 NA NA
1 534192 rs6680723 C T -0.0012238 0.0008574 0.1499999 0.1534819 0.240991 NA NA
1 546697 rs12025928 A G -0.0017768 0.0010686 0.0959997 0.0963684 0.913369 NA NA
1 693731 rs12238997 A G -0.0013783 0.0007186 0.0549997 0.0550860 0.116273 0.1417730 NA
1 705882 rs72631875 G A -0.0001070 0.0010523 0.9199999 0.9190211 0.067376 0.0315495 NA
1 706368 rs55727773 A G 0.0003254 0.0005324 0.5400003 0.5410613 0.515844 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0003885 0.0006422 0.5500004 0.5452142 0.137918 0.2052720 NA
22 51219387 rs9616832 T C -0.0006364 0.0008334 0.4500005 0.4451080 0.073758 0.0654952 NA
22 51219704 rs147475742 G A -0.0004013 0.0011168 0.7199992 0.7193652 0.041966 0.0473243 NA
22 51221190 rs369304721 G A -0.0010432 0.0011145 0.3500000 0.3492605 0.049753 NA NA
22 51221731 rs115055839 T C -0.0006655 0.0008339 0.4199997 0.4248452 0.073253 0.0625000 NA
22 51222100 rs114553188 G T 0.0001066 0.0009820 0.9100000 0.9135553 0.054411 0.0880591 NA
22 51223637 rs375798137 G A 0.0001111 0.0009867 0.9100000 0.9103163 0.054042 0.0788738 NA
22 51229805 rs9616985 T C -0.0006195 0.0008369 0.4600002 0.4591226 0.073087 0.0730831 NA
22 51232488 rs376461333 A G 0.0006910 0.0019708 0.7300002 0.7258707 0.020026 NA NA
22 51237063 rs3896457 T C 0.0000220 0.0005119 0.9699999 0.9657436 0.298147 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62381  ES:SE:LP:AF:ID  0.000900931:0.00076972:0.619789:0.62381:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400463 ES:SE:LP:AF:ID  0.00057459:0.000761892:0.346787:0.400463:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103584 ES:SE:LP:AF:ID  -0.000820038:0.00121804:0.30103:0.103584:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456945 ES:SE:LP:AF:ID  0.000289221:0.000750372:0.154902:0.456945:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074502 ES:SE:LP:AF:ID  -0.00153381:0.00148065:0.522879:0.074502:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240991 ES:SE:LP:AF:ID  -0.00122381:0.000857406:0.823909:0.240991:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913369 ES:SE:LP:AF:ID  -0.00177675:0.00106858:1.01773:0.913369:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116273 ES:SE:LP:AF:ID  -0.00137834:0.00071856:1.25964:0.116273:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067376 ES:SE:LP:AF:ID  -0.000106983:0.00105229:0.0362122:0.067376:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515844 ES:SE:LP:AF:ID  0.000325385:0.000532363:0.267606:0.515844:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032992 ES:SE:LP:AF:ID  -0.000455199:0.00134184:0.136677:0.032992:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036625 ES:SE:LP:AF:ID  -0.000346788:0.00121839:0.107905:0.036625:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036734 ES:SE:LP:AF:ID  -0.000290027:0.00121395:0.091515:0.036734:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036436 ES:SE:LP:AF:ID  -0.000331647:0.0012227:0.102373:0.036436:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036974 ES:SE:LP:AF:ID  -0.000485058:0.00120912:0.161151:0.036974:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03707  ES:SE:LP:AF:ID  -0.000237348:0.00120501:0.0757207:0.03707:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101244 ES:SE:LP:AF:ID  -0.000630701:0.000877907:0.327902:0.101244:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959105 ES:SE:LP:AF:ID  0.000799196:0.00116234:0.309804:0.959105:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03148  ES:SE:LP:AF:ID  0.000825568:0.00210784:0.154902:0.03148:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053283 ES:SE:LP:AF:ID  -0.000675971:0.001677:0.161151:0.053283:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036586 ES:SE:LP:AF:ID  -0.000250239:0.00121285:0.0757207:0.036586:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036901 ES:SE:LP:AF:ID  -0.000361947:0.00120186:0.119186:0.036901:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843234 ES:SE:LP:AF:ID  0.00105486:0.000622585:1.04576:0.843234:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055902 ES:SE:LP:AF:ID  -0.000960298:0.00100823:0.468521:0.055902:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122269 ES:SE:LP:AF:ID  -0.00133201:0.000681572:1.29243:0.122269:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025722 ES:SE:LP:AF:ID  0.000862605:0.00167496:0.21467:0.025722:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121517 ES:SE:LP:AF:ID  -0.00126858:0.000681852:1.20066:0.121517:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132305 ES:SE:LP:AF:ID  -0.000771727:0.000672014:0.60206:0.132305:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036826 ES:SE:LP:AF:ID  -0.000253493:0.00118951:0.0809219:0.036826:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838962 ES:SE:LP:AF:ID  0.00133769:0.000602996:1.56864:0.838962:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838586 ES:SE:LP:AF:ID  0.00129434:0.000602313:1.49485:0.838586:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869828 ES:SE:LP:AF:ID  0.00175897:0.00064644:2.18709:0.869828:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129826 ES:SE:LP:AF:ID  -0.001611:0.00064775:1.88606:0.129826:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037327 ES:SE:LP:AF:ID  -0.000272709:0.00116956:0.0861861:0.037327:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037569 ES:SE:LP:AF:ID  -0.000258094:0.0011622:0.0861861:0.037569:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869168 ES:SE:LP:AF:ID  0.00170739:0.000645148:2.09152:0.869168:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869265 ES:SE:LP:AF:ID  0.00171529:0.000645398:2.10237:0.869265:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037528 ES:SE:LP:AF:ID  -0.000268268:0.00116718:0.0861861:0.037528:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86917  ES:SE:LP:AF:ID  0.00170439:0.000645135:2.08619:0.86917:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838037 ES:SE:LP:AF:ID  0.00125786:0.000600635:1.4437:0.838037:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037538 ES:SE:LP:AF:ID  -0.000321321:0.00116887:0.107905:0.037538:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838671 ES:SE:LP:AF:ID  0.00127913:0.000602334:1.46852:0.838671:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839778 ES:SE:LP:AF:ID  0.00128728:0.000610468:1.45593:0.839778:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869454 ES:SE:LP:AF:ID  0.00175606:0.000644428:2.19382:0.869454:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869001 ES:SE:LP:AF:ID  0.00169569:0.000642806:2.08092:0.869001:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867947 ES:SE:LP:AF:ID  0.00164321:0.000641534:2:0.867947:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869145 ES:SE:LP:AF:ID  0.00172512:0.000643333:2.13668:0.869145:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  0.00172561:0.000643383:2.13668:0.869154:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869162 ES:SE:LP:AF:ID  0.001723:0.000643398:2.13077:0.869162:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869638 ES:SE:LP:AF:ID  0.00173374:0.000645166:2.14267:0.869638:rs3131954