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-217/UKB-b-217_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-217/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-217/UKB-b-217_data.vcf.gz ...
Read summary statistics for 7701637 SNPs.
Dropped 5545 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, 1279507 SNPs remain.
After merging with regression SNP LD, 1279507 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0021 (0.0128)
Lambda GC: 1.0088
Mean Chi^2: 1.0105
Intercept: 1.0091 (0.006)
Ratio: 0.8644 (0.5677)
Analysis finished at Thu Oct 17 14:43:50 2019
Total time elapsed: 1.0m:31.15s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9415,
    "inflation_factor": 1,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "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": 71683,
    "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": 1279507,
    "ldsc_nsnp_merge_regression_ld": 1279507,
    "ldsc_observed_scale_h2_beta": 0.0021,
    "ldsc_observed_scale_h2_se": 0.0128,
    "ldsc_intercept_beta": 1.0091,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0088,
    "ldsc_mean_chisq": 1.0105,
    "ldsc_ratio": 0.8667
}

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 7696116 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 7701637 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 8.661946e+00 5.763940e+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 7.868414e+07 5.643546e+07 828.0000000 3.220261e+07 6.914208e+07 1.145647e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.450000e-05 2.850320e-02 -0.2606800 -1.383200e-02 -1.058000e-04 1.354260e-02 3.704720e-01 ▁▅▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.474500e-02 1.389960e-02 0.0119669 1.375910e-02 1.868670e-02 3.213750e-02 1.433180e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.985255e-01 2.894187e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.985241e-01 2.893913e-01 0.0000000 2.478807e-01 4.975513e-01 7.492758e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.540657e-01 2.607899e-01 0.0102590 4.154100e-02 1.487270e-01 4.015800e-01 9.897410e-01 ▇▂▂▁▁
numeric AF_reference 71683 0.9906925 NA NA NA NA NA NA NA 2.531307e-01 2.526662e-01 0.0000000 4.552720e-02 1.631390e-01 3.961660e-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 -0.0321445 0.0220761 0.1499999 0.1453714 0.623431 0.7821490 NA
1 54676 rs2462492 C T -0.0103795 0.0218724 0.6400000 0.6351093 0.398406 NA NA
1 86028 rs114608975 T C 0.0105943 0.0347040 0.7600007 0.7601559 0.104061 0.0277556 NA
1 91536 rs6702460 G T -0.0252995 0.0215278 0.2399999 0.2399142 0.455565 0.4207270 NA
1 234313 rs8179466 C T -0.0109918 0.0425557 0.8000000 0.7961815 0.074689 NA NA
1 534192 rs6680723 C T 0.0280263 0.0246834 0.2599998 0.2561947 0.240665 NA NA
1 546697 rs12025928 A G -0.0070041 0.0302002 0.8200001 0.8165994 0.911591 NA NA
1 693731 rs12238997 A G 0.0114013 0.0203360 0.5800000 0.5750388 0.118210 0.1417730 NA
1 705882 rs72631875 G A 0.0061438 0.0299859 0.8400000 0.8376591 0.068211 0.0315495 NA
1 706368 rs55727773 A G 0.0358971 0.0151621 0.0179999 0.0179061 0.514209 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0151027 0.0185110 0.4100001 0.4145705 0.137030 0.2052720 NA
22 51219387 rs9616832 T C 0.0307694 0.0239817 0.2000000 0.1994792 0.073396 0.0654952 NA
22 51219704 rs147475742 G A -0.0035020 0.0319574 0.9100000 0.9127400 0.042117 0.0473243 NA
22 51221190 rs369304721 G A 0.0423048 0.0320827 0.1900002 0.1872971 0.049669 NA NA
22 51221731 rs115055839 T C 0.0329163 0.0239852 0.1700000 0.1699518 0.073001 0.0625000 NA
22 51222100 rs114553188 G T -0.0190287 0.0284552 0.5000000 0.5036710 0.053380 0.0880591 NA
22 51223637 rs375798137 G A -0.0206285 0.0286177 0.4700002 0.4710140 0.052976 0.0788738 NA
22 51229805 rs9616985 T C 0.0288906 0.0240777 0.2300001 0.2301819 0.072843 0.0730831 NA
22 51232488 rs376461333 A G -0.0378219 0.0585095 0.5199996 0.5180053 0.019236 NA NA
22 51237063 rs3896457 T C -0.0205108 0.0146919 0.1600000 0.1626959 0.298661 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623431 ES:SE:LP:AF:ID  -0.0321445:0.0220761:0.823909:0.623431:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398406 ES:SE:LP:AF:ID  -0.0103795:0.0218724:0.19382:0.398406:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104061 ES:SE:LP:AF:ID  0.0105943:0.034704:0.119186:0.104061:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455565 ES:SE:LP:AF:ID  -0.0252995:0.0215278:0.619789:0.455565:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074689 ES:SE:LP:AF:ID  -0.0109918:0.0425557:0.09691:0.074689:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240665 ES:SE:LP:AF:ID  0.0280263:0.0246834:0.585027:0.240665:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.911591 ES:SE:LP:AF:ID  -0.00700406:0.0302002:0.0861861:0.911591:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11821  ES:SE:LP:AF:ID  0.0114013:0.020336:0.236572:0.11821:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.068211 ES:SE:LP:AF:ID  0.00614377:0.0299859:0.0757207:0.068211:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514209 ES:SE:LP:AF:ID  0.0358971:0.0151621:1.74473:0.514209:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033797 ES:SE:LP:AF:ID  -0.0263206:0.0379735:0.309804:0.033797:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037597 ES:SE:LP:AF:ID  -0.027251:0.0344398:0.366532:0.037597:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037781 ES:SE:LP:AF:ID  -0.0278922:0.0342737:0.376751:0.037781:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03743  ES:SE:LP:AF:ID  -0.0269602:0.0345573:0.356547:0.03743:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016543 ES:SE:LP:AF:ID  0.1036:0.0538378:1.26761:0.016543:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.038042 ES:SE:LP:AF:ID  -0.0260708:0.0341404:0.346787:0.038042:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.038093 ES:SE:LP:AF:ID  -0.0281114:0.0340574:0.387216:0.038093:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10125  ES:SE:LP:AF:ID  -0.0156422:0.0250703:0.275724:0.10125:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.957915 ES:SE:LP:AF:ID  0.0214252:0.0328714:0.29243:0.957915:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031329 ES:SE:LP:AF:ID  -0.0149896:0.0609152:0.091515:0.031329:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052492 ES:SE:LP:AF:ID  -0.00996301:0.0485506:0.0757207:0.052492:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037466 ES:SE:LP:AF:ID  -0.0277122:0.034336:0.376751:0.037466:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037799 ES:SE:LP:AF:ID  -0.0284258:0.0340182:0.39794:0.037799:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840551 ES:SE:LP:AF:ID  -0.0105017:0.0177006:0.259637:0.840551:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056074 ES:SE:LP:AF:ID  0.0247882:0.0288669:0.408935:0.056074:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123839 ES:SE:LP:AF:ID  0.00946885:0.0193467:0.207608:0.123839:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.024903 ES:SE:LP:AF:ID  0.0151539:0.0491833:0.119186:0.024903:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.123075 ES:SE:LP:AF:ID  0.0102063:0.0193609:0.221849:0.123075:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134059 ES:SE:LP:AF:ID  -0.000764778:0.0191293:0.0132283:0.134059:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011403 ES:SE:LP:AF:ID  0.0327792:0.0686449:0.200659:0.011403:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.037856 ES:SE:LP:AF:ID  -0.021617:0.0336316:0.283997:0.037856:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836548 ES:SE:LP:AF:ID  -0.0142586:0.0171667:0.387216:0.836548:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836128 ES:SE:LP:AF:ID  -0.0134886:0.0171455:0.366532:0.836128:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868274 ES:SE:LP:AF:ID  -0.0153298:0.018365:0.39794:0.868274:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131343 ES:SE:LP:AF:ID  0.0135745:0.0184058:0.337242:0.131343:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038259 ES:SE:LP:AF:ID  -0.0206031:0.0331246:0.275724:0.038259:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038543 ES:SE:LP:AF:ID  -0.0243971:0.0329043:0.337242:0.038543:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867608 ES:SE:LP:AF:ID  -0.0149966:0.0183322:0.387216:0.867608:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867748 ES:SE:LP:AF:ID  -0.0155685:0.0183434:0.39794:0.867748:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.0385   ES:SE:LP:AF:ID  -0.0225793:0.0330151:0.309804:0.0385:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867622 ES:SE:LP:AF:ID  -0.0146982:0.0183316:0.376751:0.867622:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.835679 ES:SE:LP:AF:ID  -0.0134169:0.0171061:0.366532:0.835679:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038444 ES:SE:LP:AF:ID  -0.023274:0.0330923:0.318759:0.038444:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836363 ES:SE:LP:AF:ID  -0.0132387:0.0171577:0.356547:0.836363:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013055 ES:SE:LP:AF:ID  0.0269125:0.0622484:0.173925:0.013055:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.837769 ES:SE:LP:AF:ID  -0.0139748:0.0173865:0.376751:0.837769:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.867852 ES:SE:LP:AF:ID  -0.0141882:0.0183105:0.356547:0.867852:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867431 ES:SE:LP:AF:ID  -0.0141943:0.0182667:0.356547:0.867431:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866206 ES:SE:LP:AF:ID  -0.0125446:0.0182277:0.309804:0.866206:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867513 ES:SE:LP:AF:ID  -0.0142426:0.0182785:0.356547:0.867513:rs4951929