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-19060/UKB-b-19060_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19060/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19060/UKB-b-19060_data.vcf.gz ...
Read summary statistics for 6433337 SNPs.
Dropped 3419 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, 1240310 SNPs remain.
After merging with regression SNP LD, 1240310 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0162 (0.002)
Lambda GC: 1.0907
Mean Chi^2: 1.1071
Intercept: 1.0166 (0.0071)
Ratio: 0.1548 (0.0665)
Analysis finished at Thu Oct 17 14:42:08 2019
Total time elapsed: 1.0m:13.34s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9301,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -1.1126e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 9,
    "n_p_sig": 204,
    "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": 58990,
    "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": 1240310,
    "ldsc_nsnp_merge_regression_ld": 1240310,
    "ldsc_observed_scale_h2_beta": 0.0162,
    "ldsc_observed_scale_h2_se": 0.002,
    "ldsc_intercept_beta": 1.0166,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.0907,
    "ldsc_mean_chisq": 1.1071,
    "ldsc_ratio": 0.155
}

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 6429939 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 6433337 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 8.666834e+00 5.763367e+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 7.857147e+07 5.648636e+07 828.0000000 3.202414e+07 6.901507e+07 1.144776e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.100000e-06 1.019900e-03 -0.0083596 -5.880000e-04 -5.800000e-06 5.793000e-04 9.640000e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.179000e-04 3.583000e-04 0.0005614 6.262000e-04 7.733000e-04 1.122000e-03 4.867500e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.873248e-01 2.925005e-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 4.873275e-01 2.924729e-01 0.0000000 2.310656e-01 4.829193e-01 7.406212e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.955228e-01 2.569468e-01 0.0249150 7.916700e-02 2.071260e-01 4.576810e-01 9.750850e-01 ▇▃▂▂▁
numeric AF_reference 58990 0.9908306 NA NA NA NA NA NA NA 2.929278e-01 2.494336e-01 0.0000000 8.845850e-02 2.164540e-01 4.494810e-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 -0.0017393 0.0010336 0.0920005 0.0924243 0.623622 0.7821490 NA
1 54676 rs2462492 C T -0.0014555 0.0010260 0.1600000 0.1560110 0.400004 NA NA
1 86028 rs114608975 T C 0.0004763 0.0016384 0.7700005 0.7712712 0.103588 0.0277556 NA
1 91536 rs6702460 G T -0.0004694 0.0010096 0.6400000 0.6419343 0.456393 0.4207270 NA
1 234313 rs8179466 C T -0.0004095 0.0019899 0.8400000 0.8369698 0.074453 NA NA
1 534192 rs6680723 C T -0.0002011 0.0011540 0.8600001 0.8616745 0.240991 NA NA
1 546697 rs12025928 A G 0.0012085 0.0014331 0.4000000 0.3990685 0.913077 NA NA
1 693731 rs12238997 A G 0.0009068 0.0009651 0.3500000 0.3474516 0.116614 0.1417730 NA
1 705882 rs72631875 G A -0.0010629 0.0014121 0.4500005 0.4516143 0.067608 0.0315495 NA
1 706368 rs55727773 A G 0.0001148 0.0007152 0.8700001 0.8725115 0.515273 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0024085 0.0011175 0.0309999 0.0311477 0.073485 0.0826677 NA
22 51219006 rs28729663 G A 0.0012633 0.0008617 0.1400000 0.1426479 0.138022 0.2052720 NA
22 51219387 rs9616832 T C 0.0023053 0.0011200 0.0400000 0.0395663 0.073589 0.0654952 NA
22 51219704 rs147475742 G A 0.0022716 0.0015025 0.1299999 0.1305652 0.041769 0.0473243 NA
22 51221190 rs369304721 G A 0.0032953 0.0014980 0.0280001 0.0278246 0.049669 NA NA
22 51221731 rs115055839 T C 0.0024499 0.0011206 0.0290001 0.0288025 0.073076 0.0625000 NA
22 51222100 rs114553188 G T -0.0007720 0.0013191 0.5600000 0.5583808 0.054560 0.0880591 NA
22 51223637 rs375798137 G A -0.0007472 0.0013256 0.5700002 0.5729694 0.054187 0.0788738 NA
22 51229805 rs9616985 T C 0.0024045 0.0011246 0.0329997 0.0325038 0.072934 0.0730831 NA
22 51237063 rs3896457 T C -0.0001412 0.0006878 0.8400000 0.8373154 0.297752 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623622 ES:SE:LP:AF:ID  -0.00173932:0.00103362:1.03621:0.623622:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400004 ES:SE:LP:AF:ID  -0.0014555:0.001026:0.79588:0.400004:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103588 ES:SE:LP:AF:ID  0.000476312:0.00163843:0.113509:0.103588:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456393 ES:SE:LP:AF:ID  -0.000469446:0.00100957:0.19382:0.456393:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074453 ES:SE:LP:AF:ID  -0.000409472:0.00198994:0.0757207:0.074453:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240991 ES:SE:LP:AF:ID  -0.000201073:0.00115398:0.0655015:0.240991:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913077 ES:SE:LP:AF:ID  0.00120853:0.00143312:0.39794:0.913077:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116614 ES:SE:LP:AF:ID  0.00090675:0.000965096:0.455932:0.116614:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067608 ES:SE:LP:AF:ID  -0.00106291:0.00141208:0.346787:0.067608:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515273 ES:SE:LP:AF:ID  0.000114764:0.000715178:0.0604807:0.515273:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033038 ES:SE:LP:AF:ID  0.00125859:0.00180114:0.318759:0.033038:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03668  ES:SE:LP:AF:ID  0.00140009:0.00163512:0.408935:0.03668:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036796 ES:SE:LP:AF:ID  0.00150592:0.00162898:0.443698:0.036796:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036497 ES:SE:LP:AF:ID  0.00128831:0.00164058:0.366532:0.036497:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.037045 ES:SE:LP:AF:ID  0.00142646:0.00162234:0.420216:0.037045:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037129 ES:SE:LP:AF:ID  0.00126253:0.00161718:0.366532:0.037129:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101271 ES:SE:LP:AF:ID  0.000277326:0.00117863:0.091515:0.101271:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959044 ES:SE:LP:AF:ID  -0.00130022:0.00156089:0.39794:0.959044:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031467 ES:SE:LP:AF:ID  0.000952225:0.00284024:0.130768:0.031467:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053035 ES:SE:LP:AF:ID  -0.0018697:0.00226561:0.387216:0.053035:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036638 ES:SE:LP:AF:ID  0.00157831:0.00162792:0.481486:0.036638:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036976 ES:SE:LP:AF:ID  0.00177044:0.00161273:0.568636:0.036976:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842792 ES:SE:LP:AF:ID  -0.0010723:0.000835942:0.69897:0.842792:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055882 ES:SE:LP:AF:ID  5.1272e-05:0.00135662:0.0132283:0.055882:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122665 ES:SE:LP:AF:ID  0.000696315:0.000915257:0.346787:0.122665:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025852 ES:SE:LP:AF:ID  0.000623147:0.00224375:0.107905:0.025852:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121907 ES:SE:LP:AF:ID  0.000703152:0.000915669:0.356547:0.121907:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132632 ES:SE:LP:AF:ID  0.00151471:0.000902398:1.03152:0.132632:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.03686  ES:SE:LP:AF:ID  0.00164843:0.00159718:0.522879:0.03686:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838633 ES:SE:LP:AF:ID  -0.00112795:0.000810081:0.79588:0.838633:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838265 ES:SE:LP:AF:ID  -0.00108302:0.000809194:0.744727:0.838265:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869481 ES:SE:LP:AF:ID  -0.000696418:0.00086827:0.376751:0.869481:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130187 ES:SE:LP:AF:ID  0.000696558:0.000870099:0.376751:0.130187:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03737  ES:SE:LP:AF:ID  0.00186033:0.00157049:0.619789:0.03737:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037625 ES:SE:LP:AF:ID  0.00190772:0.00156028:0.657577:0.037625:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868834 ES:SE:LP:AF:ID  -0.000648789:0.000866604:0.346787:0.868834:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868928 ES:SE:LP:AF:ID  -0.000676304:0.000866898:0.356547:0.868928:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037567 ES:SE:LP:AF:ID  0.00174709:0.00156718:0.585027:0.037567:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868835 ES:SE:LP:AF:ID  -0.000652679:0.00086657:0.346787:0.868835:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837735 ES:SE:LP:AF:ID  -0.00107216:0.000806999:0.744727:0.837735:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037589 ES:SE:LP:AF:ID  0.00170084:0.0015691:0.552842:0.037589:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838358 ES:SE:LP:AF:ID  -0.00102625:0.000809238:0.69897:0.838358:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83949  ES:SE:LP:AF:ID  -0.0010094:0.000820129:0.657577:0.83949:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.000723213:0.000865563:0.39794:0.869104:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868654 ES:SE:LP:AF:ID  -0.00073928:0.000863385:0.408935:0.868654:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867577 ES:SE:LP:AF:ID  -0.000566801:0.000861676:0.29243:0.867577:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868787 ES:SE:LP:AF:ID  -0.000710603:0.000864056:0.387216:0.868787:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868796 ES:SE:LP:AF:ID  -0.000710917:0.000864119:0.387216:0.868796:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868803 ES:SE:LP:AF:ID  -0.000711596:0.00086414:0.387216:0.868803:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869285 ES:SE:LP:AF:ID  -0.000699744:0.000866555:0.376751:0.869285:rs3131954