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-1553/UKB-b-1553_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1553/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1553/UKB-b-1553_data.vcf.gz ...
Read summary statistics for 7664965 SNPs.
Dropped 5459 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, 1278604 SNPs remain.
After merging with regression SNP LD, 1278604 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0173 (0.0014)
Lambda GC: 1.1532
Mean Chi^2: 1.1741
Intercept: 1.0125 (0.0077)
Ratio: 0.0721 (0.0441)
Analysis finished at Thu Oct 17 14:45:40 2019
Total time elapsed: 1.0m:30.3s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9409,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -2.8741e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 364,
    "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": 71281,
    "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": 1278604,
    "ldsc_nsnp_merge_regression_ld": 1278604,
    "ldsc_observed_scale_h2_beta": 0.0173,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0125,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.1532,
    "ldsc_mean_chisq": 1.1741,
    "ldsc_ratio": 0.0718
}

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 7659530 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 7664965 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 8.662168e+00 5.764475e+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 7.867845e+07 5.644275e+07 828.0000000 3.219791e+07 6.912366e+07 1.145703e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.900000e-06 1.272700e-03 -0.0122113 -6.311000e-04 -5.200000e-06 6.260000e-04 1.452330e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.062900e-03 5.922000e-04 0.0005178 5.945000e-04 8.052000e-04 1.378200e-03 6.221000e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.797550e-01 2.944966e-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 4.797569e-01 2.944714e-01 0.0000000 2.192258e-01 4.729519e-01 7.351989e-01 9.999999e-01 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.551034e-01 2.608539e-01 0.0104800 4.232600e-02 1.501310e-01 4.031790e-01 9.895200e-01 ▇▂▂▁▁
numeric AF_reference 71281 0.9907004 NA NA NA NA NA NA NA 2.540969e-01 2.526969e-01 0.0000000 4.632590e-02 1.645370e-01 3.975640e-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 0.0012461 0.0009530 0.1900002 0.1910236 0.623739 0.7821490 NA
1 54676 rs2462492 C T -0.0010891 0.0009439 0.2500000 0.2485751 0.400447 NA NA
1 86028 rs114608975 T C 0.0009709 0.0015094 0.5199996 0.5200670 0.103563 0.0277556 NA
1 91536 rs6702460 G T -0.0001387 0.0009296 0.8800001 0.8813996 0.456854 0.4207270 NA
1 234313 rs8179466 C T -0.0018034 0.0018326 0.3300000 0.3250935 0.074518 NA NA
1 534192 rs6680723 C T 0.0006163 0.0010617 0.5600000 0.5616221 0.240965 NA NA
1 546697 rs12025928 A G -0.0022279 0.0013246 0.0929994 0.0925684 0.913474 NA NA
1 693731 rs12238997 A G 0.0012102 0.0008897 0.1700000 0.1737550 0.116340 0.1417730 NA
1 705882 rs72631875 G A 0.0034091 0.0013040 0.0089000 0.0089403 0.067265 0.0315495 NA
1 706368 rs55727773 A G -0.0004418 0.0006591 0.5000000 0.5026277 0.515686 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0001678 0.0007952 0.8300000 0.8328388 0.137953 0.2052720 NA
22 51219387 rs9616832 T C -0.0002179 0.0010322 0.8300000 0.8328248 0.073751 0.0654952 NA
22 51219704 rs147475742 G A -0.0001330 0.0013833 0.9199999 0.9233872 0.041948 0.0473243 NA
22 51221190 rs369304721 G A 0.0005404 0.0013811 0.6999999 0.6955742 0.049729 NA NA
22 51221731 rs115055839 T C -0.0000886 0.0010328 0.9299999 0.9316463 0.073243 0.0625000 NA
22 51222100 rs114553188 G T 0.0005187 0.0012160 0.6700003 0.6696868 0.054458 0.0880591 NA
22 51223637 rs375798137 G A 0.0005456 0.0012218 0.6600001 0.6551812 0.054088 0.0788738 NA
22 51229805 rs9616985 T C -0.0001847 0.0010366 0.8600001 0.8585615 0.073077 0.0730831 NA
22 51232488 rs376461333 A G 0.0007080 0.0024419 0.7700005 0.7718613 0.020040 NA NA
22 51237063 rs3896457 T C 0.0003136 0.0006340 0.6200004 0.6209156 0.297987 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623739 ES:SE:LP:AF:ID  0.00124606:0.000952968:0.721246:0.623739:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400447 ES:SE:LP:AF:ID  -0.00108914:0.000943945:0.60206:0.400447:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103563 ES:SE:LP:AF:ID  0.000970916:0.00150941:0.283997:0.103563:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456854 ES:SE:LP:AF:ID  -0.000138691:0.000929594:0.0555173:0.456854:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074518 ES:SE:LP:AF:ID  -0.00180339:0.00183263:0.481486:0.074518:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  0.000616264:0.00106173:0.251812:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913474 ES:SE:LP:AF:ID  -0.00222793:0.00132457:1.03152:0.913474:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11634  ES:SE:LP:AF:ID  0.00121023:0.00088972:0.769551:0.11634:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067265 ES:SE:LP:AF:ID  0.00340911:0.00130401:2.05061:0.067265:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515686 ES:SE:LP:AF:ID  -0.000441843:0.000659112:0.30103:0.515686:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032994 ES:SE:LP:AF:ID  -0.00216243:0.00166194:0.721246:0.032994:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036606 ES:SE:LP:AF:ID  -0.00181002:0.00150964:0.638272:0.036606:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  -0.00171771:0.00150393:0.60206:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036422 ES:SE:LP:AF:ID  -0.00173869:0.00151476:0.60206:0.036422:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016422 ES:SE:LP:AF:ID  0.00161979:0.00233073:0.309804:0.016422:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036962 ES:SE:LP:AF:ID  -0.00174416:0.00149795:0.619789:0.036962:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037058 ES:SE:LP:AF:ID  -0.00162576:0.00149285:0.552842:0.037058:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10117  ES:SE:LP:AF:ID  6.69548e-05:0.0010876:0.0222764:0.10117:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959116 ES:SE:LP:AF:ID  0.00181678:0.00143992:0.677781:0.959116:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031456 ES:SE:LP:AF:ID  -0.00430377:0.00261298:1:0.031456:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053258 ES:SE:LP:AF:ID  -0.000827719:0.00207886:0.161151:0.053258:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036575 ES:SE:LP:AF:ID  -0.00151279:0.00150254:0.508638:0.036575:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  -0.0016438:0.00148886:0.568636:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843218 ES:SE:LP:AF:ID  -0.000283808:0.000771163:0.148742:0.843218:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055922 ES:SE:LP:AF:ID  0.00169871:0.00124851:0.769551:0.055922:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122325 ES:SE:LP:AF:ID  0.000949393:0.000844017:0.585027:0.122325:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  -0.00515722:0.00207611:1.88606:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121567 ES:SE:LP:AF:ID  0.000936158:0.000844373:0.568636:0.121567:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132324 ES:SE:LP:AF:ID  0.000154298:0.000832285:0.0705811:0.132324:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  -0.00334661:0.00302629:0.568636:0.01113:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  -0.00175859:0.00147376:0.638272:0.036808:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838956 ES:SE:LP:AF:ID  -0.000577426:0.000746816:0.356547:0.838956:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838586 ES:SE:LP:AF:ID  -0.000575479:0.000746017:0.356547:0.838586:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86977  ES:SE:LP:AF:ID  -0.00110708:0.000800472:0.769551:0.86977:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129879 ES:SE:LP:AF:ID  0.0010544:0.000802111:0.721246:0.129879:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037318 ES:SE:LP:AF:ID  -0.00173342:0.00144882:0.638272:0.037318:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  -0.00171695:0.00143968:0.638272:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  -0.00109066:0.000798914:0.769551:0.869116:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -0.00109708:0.000799232:0.769551:0.869214:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037519 ES:SE:LP:AF:ID  -0.00184319:0.00144591:0.69897:0.037519:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  -0.00108129:0.0007989:0.744727:0.869119:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83804  ES:SE:LP:AF:ID  -0.000532001:0.000743952:0.327902:0.83804:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  -0.001834:0.00144796:0.677781:0.03753:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838671 ES:SE:LP:AF:ID  -0.000506709:0.000746043:0.30103:0.838671:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013766 ES:SE:LP:AF:ID  -0.00439247:0.00260485:1.03621:0.013766:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839782 ES:SE:LP:AF:ID  -0.000638183:0.000756124:0.39794:0.839782:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869394 ES:SE:LP:AF:ID  -0.00105789:0.000797962:0.744727:0.869394:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86894  ES:SE:LP:AF:ID  -0.00106649:0.00079595:0.744727:0.86894:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867895 ES:SE:LP:AF:ID  -0.00100697:0.000794435:0.69897:0.867895:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869084 ES:SE:LP:AF:ID  -0.00109845:0.000796604:0.769551:0.869084:rs4951929