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-352/UKB-b-352_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-352/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:43 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-352/UKB-b-352_data.vcf.gz ...
Read summary statistics for 7944648 SNPs.
Dropped 6033 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, 1281837 SNPs remain.
After merging with regression SNP LD, 1281837 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0281 (0.0118)
Lambda GC: 1.024
Mean Chi^2: 1.0234
Intercept: 1.0007 (0.0068)
Ratio: 0.0294 (0.2924)
Analysis finished at Thu Oct 17 14:45:15 2019
Total time elapsed: 1.0m:31.51s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9426,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 74160,
    "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": 1281837,
    "ldsc_nsnp_merge_regression_ld": 1281837,
    "ldsc_observed_scale_h2_beta": 0.0281,
    "ldsc_observed_scale_h2_se": 0.0118,
    "ldsc_intercept_beta": 1.0007,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.024,
    "ldsc_mean_chisq": 1.0234,
    "ldsc_ratio": 0.0299
}

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 7938642 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 7944648 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 8.661006e+00 5.763952e+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 7.870124e+07 5.641473e+07 828.0000000 3.225715e+07 6.917200e+07 1.145400e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.530000e-05 1.500260e-02 -0.1468330 -6.972800e-03 1.900000e-06 6.972800e-03 1.668290e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.279420e-02 7.605400e-03 0.0058770 6.806300e-03 9.435500e-03 1.679490e-02 7.363190e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.963548e-01 2.895715e-01 0.0000002 2.500000e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.963538e-01 2.895462e-01 0.0000002 2.452420e-01 4.949820e-01 7.468835e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.470778e-01 2.607733e-01 0.0086200 3.644800e-02 1.387220e-01 3.912410e-01 9.913800e-01 ▇▂▂▁▁
numeric AF_reference 74160 0.9906654 NA NA NA NA NA NA NA 2.463102e-01 2.526092e-01 0.0000000 3.873800e-02 1.539540e-01 3.863820e-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 0.0114769 0.0107651 0.2900000 0.2863689 0.622554 0.7821490 NA
1 54676 rs2462492 C T 0.0048338 0.0107216 0.6499995 0.6520999 0.399309 NA NA
1 86028 rs114608975 T C -0.0300091 0.0172194 0.0810009 0.0813774 0.102916 0.0277556 NA
1 91536 rs6702460 G T -0.0006065 0.0105438 0.9500000 0.9541327 0.455293 0.4207270 NA
1 234313 rs8179466 C T -0.0045445 0.0213716 0.8300000 0.8316051 0.073001 NA NA
1 534192 rs6680723 C T -0.0270060 0.0120403 0.0250000 0.0248989 0.240740 NA NA
1 546697 rs12025928 A G -0.0215447 0.0148995 0.1499999 0.1481768 0.911856 NA NA
1 693731 rs12238997 A G 0.0060323 0.0100721 0.5500004 0.5492303 0.117259 0.1417730 NA
1 705882 rs72631875 G A 0.0098944 0.0146405 0.5000000 0.4991542 0.068108 0.0315495 NA
1 706368 rs55727773 A G 0.0054454 0.0074749 0.4700002 0.4663110 0.516451 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0047900 0.0090366 0.5999997 0.5960615 0.137511 0.2052720 NA
22 51219387 rs9616832 T C -0.0005190 0.0117623 0.9599999 0.9648025 0.072867 0.0654952 NA
22 51219704 rs147475742 G A -0.0096174 0.0158927 0.5500004 0.5450842 0.041076 0.0473243 NA
22 51221190 rs369304721 G A -0.0100563 0.0157827 0.5199996 0.5240126 0.049068 NA NA
22 51221731 rs115055839 T C 0.0006377 0.0117714 0.9599999 0.9567935 0.072363 0.0625000 NA
22 51222100 rs114553188 G T -0.0013432 0.0137320 0.9199999 0.9220760 0.055155 0.0880591 NA
22 51223637 rs375798137 G A -0.0020866 0.0138002 0.8800001 0.8798174 0.054764 0.0788738 NA
22 51229805 rs9616985 T C 0.0007688 0.0118141 0.9500000 0.9481131 0.072231 0.0730831 NA
22 51232488 rs376461333 A G -0.0086093 0.0279576 0.7600007 0.7581270 0.019917 NA NA
22 51237063 rs3896457 T C 0.0004651 0.0071687 0.9500000 0.9482659 0.297591 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.622554 ES:SE:LP:AF:ID  0.0114769:0.0107651:0.537602:0.622554:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399309 ES:SE:LP:AF:ID  0.0048338:0.0107216:0.187087:0.399309:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.102916 ES:SE:LP:AF:ID  -0.0300091:0.0172194:1.09151:0.102916:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455293 ES:SE:LP:AF:ID  -0.000606457:0.0105438:0.0222764:0.455293:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.073001 ES:SE:LP:AF:ID  -0.00454453:0.0213716:0.0809219:0.073001:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24074  ES:SE:LP:AF:ID  -0.027006:0.0120403:1.60206:0.24074:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.911856 ES:SE:LP:AF:ID  -0.0215447:0.0148995:0.823909:0.911856:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117259 ES:SE:LP:AF:ID  0.00603232:0.0100721:0.259637:0.117259:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.068108 ES:SE:LP:AF:ID  0.00989436:0.0146405:0.30103:0.068108:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516451 ES:SE:LP:AF:ID  0.00544543:0.00747491:0.327902:0.516451:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032307 ES:SE:LP:AF:ID  0.00565317:0.0191063:0.113509:0.032307:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.035866 ES:SE:LP:AF:ID  0.00579521:0.0173349:0.130768:0.035866:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.035941 ES:SE:LP:AF:ID  0.00601657:0.0172826:0.136677:0.035941:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035757 ES:SE:LP:AF:ID  0.00466176:0.0173746:0.102373:0.035757:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016371 ES:SE:LP:AF:ID  -0.00836659:0.0265264:0.124939:0.016371:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036161 ES:SE:LP:AF:ID  0.00347454:0.0172182:0.0757207:0.036161:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036377 ES:SE:LP:AF:ID  0.00303261:0.0171223:0.0655015:0.036377:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102238 ES:SE:LP:AF:ID  -0.0254484:0.0122413:1.42022:0.102238:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.960051 ES:SE:LP:AF:ID  -0.00639499:0.0165435:0.154902:0.960051:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031671 ES:SE:LP:AF:ID  -0.00501759:0.0296235:0.0604807:0.031671:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05325  ES:SE:LP:AF:ID  -0.0075807:0.0237189:0.124939:0.05325:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.035909 ES:SE:LP:AF:ID  0.00561787:0.0172221:0.130768:0.035909:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036119 ES:SE:LP:AF:ID  0.00240428:0.0171004:0.05061:0.036119:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843185 ES:SE:LP:AF:ID  -0.00357439:0.0087704:0.167491:0.843185:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056793 ES:SE:LP:AF:ID  0.00244371:0.0140693:0.0655015:0.056793:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123327 ES:SE:LP:AF:ID  0.00668742:0.00957023:0.318759:0.123327:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.024664 ES:SE:LP:AF:ID  -0.0142223:0.0240482:0.259637:0.024664:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.1226   ES:SE:LP:AF:ID  0.00666504:0.00957094:0.309804:0.1226:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132766 ES:SE:LP:AF:ID  0.00417742:0.00943502:0.180456:0.132766:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.0114   ES:SE:LP:AF:ID  0.0693328:0.0338843:1.38722:0.0114:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036008 ES:SE:LP:AF:ID  0.00214495:0.0169304:0.0457575:0.036008:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838936 ES:SE:LP:AF:ID  -0.00416479:0.0084904:0.207608:0.838936:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838608 ES:SE:LP:AF:ID  -0.0043744:0.00848103:0.21467:0.838608:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  -0.00680557:0.00907715:0.346787:0.868952:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130726 ES:SE:LP:AF:ID  0.00685741:0.00909154:0.346787:0.130726:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036625 ES:SE:LP:AF:ID  0.00371026:0.0166041:0.0861861:0.036625:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.036854 ES:SE:LP:AF:ID  0.00563176:0.0165035:0.136677:0.036854:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868313 ES:SE:LP:AF:ID  -0.00705451:0.00905877:0.356547:0.868313:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868431 ES:SE:LP:AF:ID  -0.00700916:0.00906278:0.356547:0.868431:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.036855 ES:SE:LP:AF:ID  0.00288519:0.0165666:0.0655015:0.036855:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868323 ES:SE:LP:AF:ID  -0.00696793:0.00905843:0.356547:0.868323:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837971 ES:SE:LP:AF:ID  -0.00343145:0.00845577:0.167491:0.837971:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.036873 ES:SE:LP:AF:ID  0.00209153:0.0165931:0.0457575:0.036873:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838538 ES:SE:LP:AF:ID  -0.0038937:0.00847793:0.187087:0.838538:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013752 ES:SE:LP:AF:ID  -0.0426909:0.0296404:0.823909:0.013752:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839622 ES:SE:LP:AF:ID  -0.00468043:0.00859282:0.229148:0.839622:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868571 ES:SE:LP:AF:ID  -0.00709921:0.00904912:0.366532:0.868571:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868135 ES:SE:LP:AF:ID  -0.00626067:0.00902991:0.309804:0.868135:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867249 ES:SE:LP:AF:ID  -0.0074726:0.00901487:0.387216:0.867249:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868301 ES:SE:LP:AF:ID  -0.00734176:0.0090363:0.376751:0.868301:rs4951929