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-15695/UKB-b-15695_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15695/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15695/UKB-b-15695_data.vcf.gz ...
Read summary statistics for 8565981 SNPs.
Dropped 7254 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, 1285523 SNPs remain.
After merging with regression SNP LD, 1285523 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.032 (0.0027)
Lambda GC: 1.1439
Mean Chi^2: 1.1506
Intercept: 1.0258 (0.0065)
Ratio: 0.1716 (0.0434)
Analysis finished at Thu Oct 17 14:45:50 2019
Total time elapsed: 1.0m:32.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9459,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 214,
    "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": 82092,
    "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": 1285523,
    "ldsc_nsnp_merge_regression_ld": 1285523,
    "ldsc_observed_scale_h2_beta": 0.032,
    "ldsc_observed_scale_h2_se": 0.0027,
    "ldsc_intercept_beta": 1.0258,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.1439,
    "ldsc_mean_chisq": 1.1506,
    "ldsc_ratio": 0.1713
}

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 8558761 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 8565981 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 8.651627e+00 5.761603e+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 7.875973e+07 5.637647e+07 828.0000000 3.237062e+07 6.927086e+07 1.145574e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.000000e-05 4.384500e-03 -0.0482972 -1.918000e-03 -2.090000e-05 1.857500e-03 4.510860e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.507200e-03 2.368700e-03 0.0014094 1.658900e-03 2.432400e-03 4.729500e-03 2.475480e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.814909e-01 2.938025e-01 0.0000000 2.200002e-01 4.700002e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.814912e-01 2.937772e-01 0.0000000 2.226522e-01 4.745357e-01 7.363410e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.305537e-01 2.596338e-01 0.0056010 2.599300e-02 1.158560e-01 3.649110e-01 9.943990e-01 ▇▂▁▁▁
numeric AF_reference 82092 0.9904165 NA NA NA NA NA NA NA 2.302401e-01 2.515912e-01 0.0000000 2.436100e-02 1.323880e-01 3.618210e-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 0.0020591 0.0025928 0.4299995 0.4270916 0.624189 0.7821490 NA
1 54676 rs2462492 C T 0.0002710 0.0025744 0.9199999 0.9161723 0.399687 NA NA
1 86028 rs114608975 T C -0.0026647 0.0040949 0.5199996 0.5152199 0.103749 0.0277556 NA
1 91536 rs6702460 G T -0.0003972 0.0025336 0.8800001 0.8754102 0.456531 0.4207270 NA
1 234313 rs8179466 C T -0.0046343 0.0049893 0.3500000 0.3529712 0.074558 NA NA
1 534192 rs6680723 C T -0.0028347 0.0028921 0.3300000 0.3270141 0.240700 NA NA
1 546697 rs12025928 A G -0.0023420 0.0036098 0.5199996 0.5164651 0.913436 NA NA
1 693731 rs12238997 A G 0.0035451 0.0024277 0.1400000 0.1442095 0.115792 0.1417730 NA
1 705882 rs72631875 G A 0.0002105 0.0035482 0.9500000 0.9526887 0.067531 0.0315495 NA
1 706368 rs55727773 A G -0.0000485 0.0017957 0.9800000 0.9784662 0.516624 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0013773 0.0021620 0.5199996 0.5241039 0.137950 0.2052720 NA
22 51219387 rs9616832 T C 0.0003505 0.0028071 0.9000000 0.9006230 0.073938 0.0654952 NA
22 51219704 rs147475742 G A -0.0024959 0.0037619 0.5099998 0.5070275 0.042108 0.0473243 NA
22 51221190 rs369304721 G A 0.0011005 0.0037545 0.7700005 0.7694276 0.049891 NA NA
22 51221731 rs115055839 T C 0.0005636 0.0028097 0.8400000 0.8410333 0.073384 0.0625000 NA
22 51222100 rs114553188 G T -0.0023013 0.0033155 0.4899999 0.4876159 0.054211 0.0880591 NA
22 51223637 rs375798137 G A -0.0025652 0.0033317 0.4400003 0.4413408 0.053837 0.0788738 NA
22 51229805 rs9616985 T C 0.0001246 0.0028202 0.9599999 0.9647459 0.073177 0.0730831 NA
22 51232488 rs376461333 A G -0.0017197 0.0066559 0.8000000 0.7961196 0.019993 NA NA
22 51237063 rs3896457 T C -0.0017913 0.0017286 0.2999998 0.3000696 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624189 ES:SE:LP:AF:ID  0.00205913:0.00259278:0.366532:0.624189:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399687 ES:SE:LP:AF:ID  0.000270968:0.00257436:0.0362122:0.399687:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103749 ES:SE:LP:AF:ID  -0.00266468:0.0040949:0.283997:0.103749:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456531 ES:SE:LP:AF:ID  -0.000397239:0.00253357:0.0555173:0.456531:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074558 ES:SE:LP:AF:ID  -0.00463426:0.00498929:0.455932:0.074558:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.2407   ES:SE:LP:AF:ID  -0.00283469:0.00289211:0.481486:0.2407:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913436 ES:SE:LP:AF:ID  -0.00234202:0.00360975:0.283997:0.913436:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115792 ES:SE:LP:AF:ID  0.00354511:0.00242767:0.853872:0.115792:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067531 ES:SE:LP:AF:ID  0.000210515:0.00354816:0.0222764:0.067531:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516624 ES:SE:LP:AF:ID  -4.84697e-05:0.00179571:0.00877392:0.516624:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033113 ES:SE:LP:AF:ID  -0.00696364:0.00452028:0.920819:0.033113:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036785 ES:SE:LP:AF:ID  -0.00594175:0.00410063:0.823909:0.036785:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036917 ES:SE:LP:AF:ID  -0.00603486:0.00408376:0.853872:0.036917:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036621 ES:SE:LP:AF:ID  -0.00533826:0.00411264:0.721246:0.036621:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016436 ES:SE:LP:AF:ID  0.00514604:0.00635127:0.376751:0.016436:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037167 ES:SE:LP:AF:ID  -0.00540802:0.00406679:0.744727:0.037167:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037269 ES:SE:LP:AF:ID  -0.00513641:0.00405236:0.69897:0.037269:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101315 ES:SE:LP:AF:ID  0.00632166:0.00296135:1.48149:0.101315:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958845 ES:SE:LP:AF:ID  0.00488987:0.00390806:0.677781:0.958845:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031451 ES:SE:LP:AF:ID  0.0103449:0.00715154:0.823909:0.031451:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053112 ES:SE:LP:AF:ID  -0.00213588:0.00567817:0.148742:0.053112:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036764 ES:SE:LP:AF:ID  -0.00475162:0.00408119:0.619789:0.036764:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  -0.00482175:0.0040444:0.638272:0.037066:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843463 ES:SE:LP:AF:ID  -0.00103975:0.00210015:0.207608:0.843463:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055783 ES:SE:LP:AF:ID  -8.14459e-05:0.0034042:0.00877392:0.055783:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12177  ES:SE:LP:AF:ID  0.00349322:0.00230355:0.886057:0.12177:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025889 ES:SE:LP:AF:ID  0.000351535:0.00563257:0.0222764:0.025889:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121035 ES:SE:LP:AF:ID  0.00328161:0.0023045:0.823909:0.121035:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132005 ES:SE:LP:AF:ID  0.000515427:0.0022692:0.0861861:0.132005:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011079 ES:SE:LP:AF:ID  -0.000390456:0.00825806:0.0177288:0.011079:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036985 ES:SE:LP:AF:ID  -0.0048826:0.00400298:0.657577:0.036985:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839261 ES:SE:LP:AF:ID  -0.00100805:0.0020351:0.207608:0.839261:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838885 ES:SE:LP:AF:ID  -0.000990329:0.00203263:0.200659:0.838885:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.87026  ES:SE:LP:AF:ID  -0.00292688:0.00218381:0.744727:0.87026:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129392 ES:SE:LP:AF:ID  0.00313286:0.00218772:0.823909:0.129392:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037556 ES:SE:LP:AF:ID  -0.00472934:0.00393237:0.638272:0.037556:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037778 ES:SE:LP:AF:ID  -0.00457727:0.00390917:0.619789:0.037778:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869602 ES:SE:LP:AF:ID  -0.00297371:0.00217909:0.769551:0.869602:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869732 ES:SE:LP:AF:ID  -0.00300802:0.00218005:0.769551:0.869732:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037746 ES:SE:LP:AF:ID  -0.00466558:0.00392533:0.638272:0.037746:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869608 ES:SE:LP:AF:ID  -0.00294263:0.00217908:0.744727:0.869608:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838339 ES:SE:LP:AF:ID  -0.00103188:0.00202699:0.21467:0.838339:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037758 ES:SE:LP:AF:ID  -0.00482021:0.00393054:0.657577:0.037758:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838961 ES:SE:LP:AF:ID  -0.00111601:0.00203268:0.236572:0.838961:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013781 ES:SE:LP:AF:ID  0.0057517:0.00708786:0.376751:0.013781:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.840065 ES:SE:LP:AF:ID  -0.00124364:0.00206052:0.259637:0.840065:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869885 ES:SE:LP:AF:ID  -0.00295597:0.00217706:0.769551:0.869885:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869438 ES:SE:LP:AF:ID  -0.00303773:0.00217159:0.79588:0.869438:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868355 ES:SE:LP:AF:ID  -0.00267149:0.00216655:0.657577:0.868355:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869579 ES:SE:LP:AF:ID  -0.00295224:0.0021733:0.769551:0.869579:rs4951929