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-7663/UKB-b-7663_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7663/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7663/UKB-b-7663_data.vcf.gz ...
Read summary statistics for 8164789 SNPs.
Dropped 6432 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, 1283621 SNPs remain.
After merging with regression SNP LD, 1283621 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0227 (0.0014)
Lambda GC: 1.2034
Mean Chi^2: 1.2273
Intercept: 1.0221 (0.0074)
Ratio: 0.0974 (0.0327)
Analysis finished at Thu Oct 17 14:42:19 2019
Total time elapsed: 1.0m:29.15s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9439,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -5.2715e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 6,
    "n_p_sig": 527,
    "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": 76479,
    "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": 1283621,
    "ldsc_nsnp_merge_regression_ld": 1283621,
    "ldsc_observed_scale_h2_beta": 0.0227,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0221,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.2034,
    "ldsc_mean_chisq": 1.2273,
    "ldsc_ratio": 0.0972
}

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 8158386 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 8164789 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 8.658047e+00 5.763244e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.871793e+07 5.639477e+07 828.000000 3.229959e+07 6.920056e+07 1.145352e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.300000e-06 1.700000e-03 -0.017709 -7.989000e-04 -1.900000e-06 7.889000e-04 1.813150e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.383000e-03 8.624000e-04 0.000607 7.063000e-04 9.980000e-04 1.832800e-03 7.476900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.754527e-01 2.953320e-01 0.000000 2.099999e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.754538e-01 2.953084e-01 0.000000 2.135942e-01 4.670394e-01 7.312686e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.410079e-01 2.604943e-01 0.007374 3.241700e-02 1.302040e-01 3.820330e-01 9.926260e-01 ▇▂▂▁▁
numeric AF_reference 76479 0.9906331 NA NA NA NA NA NA NA 2.403993e-01 2.523616e-01 0.000000 3.314700e-02 1.459660e-01 3.773960e-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 0.0000579 0.0011171 0.9599999 0.9586777 0.623782 0.7821490 NA
1 54676 rs2462492 C T 0.0004520 0.0011065 0.6800001 0.6829454 0.400397 NA NA
1 86028 rs114608975 T C -0.0022538 0.0017688 0.2000000 0.2026072 0.103566 0.0277556 NA
1 91536 rs6702460 G T 0.0008150 0.0010895 0.4500005 0.4544659 0.456836 0.4207270 NA
1 234313 rs8179466 C T 0.0022082 0.0021478 0.2999998 0.3038835 0.074517 NA NA
1 534192 rs6680723 C T -0.0002772 0.0012447 0.8200001 0.8237751 0.240936 NA NA
1 546697 rs12025928 A G -0.0010640 0.0015529 0.4899999 0.4932317 0.913502 NA NA
1 693731 rs12238997 A G 0.0008345 0.0010428 0.4199997 0.4236052 0.116349 0.1417730 NA
1 705882 rs72631875 G A -0.0005394 0.0015286 0.7199992 0.7241817 0.067272 0.0315495 NA
1 706368 rs55727773 A G -0.0003502 0.0007726 0.6499995 0.6503723 0.515605 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0008963 0.0009323 0.3400001 0.3363571 0.137938 0.2052720 NA
22 51219387 rs9616832 T C -0.0007654 0.0012101 0.5300002 0.5270409 0.073731 0.0654952 NA
22 51219704 rs147475742 G A -0.0014000 0.0016218 0.3900004 0.3879981 0.041939 0.0473243 NA
22 51221190 rs369304721 G A -0.0008471 0.0016192 0.5999997 0.6008484 0.049715 NA NA
22 51221731 rs115055839 T C -0.0005711 0.0012109 0.6400000 0.6371802 0.073221 0.0625000 NA
22 51222100 rs114553188 G T -0.0010816 0.0014253 0.4500005 0.4479113 0.054465 0.0880591 NA
22 51223637 rs375798137 G A -0.0010966 0.0014322 0.4400003 0.4438371 0.054096 0.0788738 NA
22 51229805 rs9616985 T C -0.0006160 0.0012153 0.6100002 0.6122160 0.073053 0.0730831 NA
22 51232488 rs376461333 A G -0.0011783 0.0028615 0.6800001 0.6804997 0.020051 NA NA
22 51237063 rs3896457 T C 0.0000034 0.0007432 1.0000000 0.9963184 0.297957 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623782 ES:SE:LP:AF:ID  5.78787e-05:0.00111707:0.0177288:0.623782:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400397 ES:SE:LP:AF:ID  0.000451955:0.00110652:0.167491:0.400397:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103566 ES:SE:LP:AF:ID  -0.00225377:0.00176883:0.69897:0.103566:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456836 ES:SE:LP:AF:ID  0.000814973:0.00108955:0.346787:0.456836:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074517 ES:SE:LP:AF:ID  0.00220819:0.00214775:0.522879:0.074517:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240936 ES:SE:LP:AF:ID  -0.000277185:0.0012447:0.0861861:0.240936:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913502 ES:SE:LP:AF:ID  -0.00106404:0.00155294:0.309804:0.913502:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116349 ES:SE:LP:AF:ID  0.00083447:0.00104285:0.376751:0.116349:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067272 ES:SE:LP:AF:ID  -0.000539388:0.00152855:0.142668:0.067272:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515605 ES:SE:LP:AF:ID  -0.000350169:0.000772582:0.187087:0.515605:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032986 ES:SE:LP:AF:ID  -0.000940558:0.00194841:0.200659:0.032986:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036602 ES:SE:LP:AF:ID  -0.000627394:0.00176975:0.142668:0.036602:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036718 ES:SE:LP:AF:ID  -0.000708551:0.00176304:0.161151:0.036718:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036419 ES:SE:LP:AF:ID  -0.000618271:0.00177569:0.136677:0.036419:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016401 ES:SE:LP:AF:ID  -1.68926e-05:0.00273413:-0:0.016401:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036957 ES:SE:LP:AF:ID  -0.000653488:0.00175606:0.148742:0.036957:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037053 ES:SE:LP:AF:ID  -0.000641578:0.00175007:0.148742:0.037053:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101242 ES:SE:LP:AF:ID  0.000214736:0.00127443:0.0604807:0.101242:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959112 ES:SE:LP:AF:ID  0.000629064:0.00168778:0.148742:0.959112:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  0.00165726:0.00306338:0.229148:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053275 ES:SE:LP:AF:ID  9.05812e-05:0.00243606:0.0132283:0.053275:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036574 ES:SE:LP:AF:ID  -0.000644526:0.0017613:0.148742:0.036574:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036886 ES:SE:LP:AF:ID  -0.000547151:0.00174537:0.124939:0.036886:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843211 ES:SE:LP:AF:ID  -0.000250322:0.000903884:0.107905:0.843211:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055936 ES:SE:LP:AF:ID  -0.000215811:0.00146318:0.0555173:0.055936:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122327 ES:SE:LP:AF:ID  0.000409685:0.00098926:0.167491:0.122327:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025679 ES:SE:LP:AF:ID  -0.00386232:0.00243515:0.958607:0.025679:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12157  ES:SE:LP:AF:ID  0.000390568:0.000989677:0.161151:0.12157:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132338 ES:SE:LP:AF:ID  0.000263383:0.000975538:0.102373:0.132338:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011143 ES:SE:LP:AF:ID  0.00210944:0.0035448:0.259637:0.011143:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036802 ES:SE:LP:AF:ID  -0.000269053:0.0017277:0.0555173:0.036802:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83895  ES:SE:LP:AF:ID  -0.000726238:0.000875334:0.387216:0.83895:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838577 ES:SE:LP:AF:ID  -0.000715937:0.000874385:0.387216:0.838577:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869761 ES:SE:LP:AF:ID  -0.000911923:0.000938209:0.481486:0.869761:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129886 ES:SE:LP:AF:ID  0.000867176:0.000940116:0.443698:0.129886:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037312 ES:SE:LP:AF:ID  -0.000581439:0.00169842:0.136677:0.037312:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037556 ES:SE:LP:AF:ID  -0.000593178:0.00168768:0.136677:0.037556:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  -0.000887739:0.00093637:0.468521:0.869103:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869201 ES:SE:LP:AF:ID  -0.000939176:0.00093674:0.49485:0.869201:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  -0.000564344:0.001695:0.130768:0.037514:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  -0.00090182:0.000936351:0.468521:0.869106:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838032 ES:SE:LP:AF:ID  -0.000760249:0.000871962:0.420216:0.838032:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  -0.000575695:0.00169739:0.136677:0.037527:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838663 ES:SE:LP:AF:ID  -0.000720696:0.000874417:0.387216:0.838663:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013783 ES:SE:LP:AF:ID  0.00323742:0.00305099:0.537602:0.013783:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  -0.000707028:0.000886248:0.366532:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869387 ES:SE:LP:AF:ID  -0.0010003:0.000935271:0.552842:0.869387:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868933 ES:SE:LP:AF:ID  -0.00104524:0.000932914:0.585027:0.868933:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867885 ES:SE:LP:AF:ID  -0.000922972:0.000931125:0.49485:0.867885:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869077 ES:SE:LP:AF:ID  -0.00102388:0.000933681:0.568636:0.869077:rs4951929