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-16019/UKB-b-16019_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16019/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16019/UKB-b-16019_data.vcf.gz ...
Read summary statistics for 7896939 SNPs.
Dropped 5930 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, 1281341 SNPs remain.
After merging with regression SNP LD, 1281341 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0073 (0.0011)
Lambda GC: 1.1139
Mean Chi^2: 1.1297
Intercept: 1.0651 (0.0065)
Ratio: 0.5019 (0.0504)
Analysis finished at Thu Oct 17 14:46:07 2019
Total time elapsed: 1.0m:27.77s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9424,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 2.5806e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 2808,
    "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": 73665,
    "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": 1281341,
    "ldsc_nsnp_merge_regression_ld": 1281341,
    "ldsc_observed_scale_h2_beta": 0.0073,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0651,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.1139,
    "ldsc_mean_chisq": 1.1297,
    "ldsc_ratio": 0.5019
}

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 TRUE
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 7891036 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 7896939 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 8.660762e+00 5.763614e+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 7.870372e+07 5.642330e+07 828.0000000 3.224686e+07 6.917357e+07 1.145574e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.600000e-06 1.442100e-03 -0.0250335 -6.809000e-04 -1.100000e-06 6.862000e-04 1.425810e-02 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.192700e-03 7.014000e-04 0.0005541 6.400000e-04 8.835000e-04 1.562800e-03 6.832900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.829290e-01 2.935744e-01 0.0000000 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.829304e-01 2.935484e-01 0.0000000 2.247171e-01 4.771506e-01 7.366340e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.484035e-01 2.607899e-01 0.0089110 3.737500e-02 1.405670e-01 3.932205e-01 9.910890e-01 ▇▂▂▁▁
numeric AF_reference 73665 0.9906717 NA NA NA NA NA NA NA 2.475952e-01 2.526287e-01 0.0000000 3.993610e-02 1.557510e-01 3.881790e-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 -0.0003067 0.0010196 0.7600007 0.7635241 0.623776 0.7821490 NA
1 54676 rs2462492 C T -0.0009735 0.0010102 0.3400001 0.3352271 0.400404 NA NA
1 86028 rs114608975 T C 0.0009229 0.0016151 0.5700002 0.5677075 0.103556 0.0277556 NA
1 91536 rs6702460 G T -0.0009087 0.0009946 0.3599996 0.3608778 0.456861 0.4207270 NA
1 234313 rs8179466 C T 0.0005764 0.0019611 0.7700005 0.7688072 0.074508 NA NA
1 534192 rs6680723 C T -0.0002711 0.0011361 0.8100000 0.8114216 0.240948 NA NA
1 546697 rs12025928 A G 0.0005504 0.0014173 0.6999999 0.6977790 0.913472 NA NA
1 693731 rs12238997 A G 0.0007787 0.0009522 0.4100001 0.4134882 0.116323 0.1417730 NA
1 705882 rs72631875 G A -0.0013854 0.0013951 0.3200000 0.3206870 0.067305 0.0315495 NA
1 706368 rs55727773 A G 0.0000820 0.0007053 0.9100000 0.9074240 0.515671 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0004278 0.0008508 0.6200004 0.6150754 0.137960 0.2052720 NA
22 51219387 rs9616832 T C 0.0014295 0.0011044 0.2000000 0.1955271 0.073739 0.0654952 NA
22 51219704 rs147475742 G A 0.0008658 0.0014799 0.5600000 0.5585331 0.041957 0.0473243 NA
22 51221190 rs369304721 G A 0.0012689 0.0014775 0.3900004 0.3904524 0.049727 NA NA
22 51221731 rs115055839 T C 0.0013476 0.0011051 0.2200002 0.2226707 0.073229 0.0625000 NA
22 51222100 rs114553188 G T -0.0013794 0.0013010 0.2900000 0.2890157 0.054469 0.0880591 NA
22 51223637 rs375798137 G A -0.0014068 0.0013073 0.2800000 0.2818747 0.054098 0.0788738 NA
22 51229805 rs9616985 T C 0.0012486 0.0011091 0.2599998 0.2602439 0.073064 0.0730831 NA
22 51232488 rs376461333 A G -0.0022559 0.0026131 0.3900004 0.3879627 0.020044 NA NA
22 51237063 rs3896457 T C 0.0017371 0.0006784 0.0100000 0.0104509 0.297967 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623776 ES:SE:LP:AF:ID  -0.000306741:0.00101956:0.119186:0.623776:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400404 ES:SE:LP:AF:ID  -0.000973516:0.00101025:0.468521:0.400404:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  0.000922901:0.00161507:0.244125:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456861 ES:SE:LP:AF:ID  -0.000908747:0.000994586:0.443698:0.456861:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074508 ES:SE:LP:AF:ID  0.000576434:0.00196109:0.113509:0.074508:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240948 ES:SE:LP:AF:ID  -0.000271072:0.00113613:0.091515:0.240948:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913472 ES:SE:LP:AF:ID  0.000550382:0.00141734:0.154902:0.913472:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116323 ES:SE:LP:AF:ID  0.000778664:0.000952179:0.387216:0.116323:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067305 ES:SE:LP:AF:ID  -0.00138541:0.00139511:0.49485:0.067305:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515671 ES:SE:LP:AF:ID  8.2023e-05:0.000705341:0.0409586:0.515671:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03301  ES:SE:LP:AF:ID  0.000464222:0.00177792:0.102373:0.03301:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036625 ES:SE:LP:AF:ID  0.000150629:0.00161499:0.0315171:0.036625:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036742 ES:SE:LP:AF:ID  -1.90284e-06:0.00160887:-0:0.036742:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03644  ES:SE:LP:AF:ID  4.72305e-05:0.00162049:0.00877392:0.03644:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016414 ES:SE:LP:AF:ID  0.00233716:0.00249466:0.455932:0.016414:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036979 ES:SE:LP:AF:ID  -4.58424e-05:0.00160255:0.00877392:0.036979:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037076 ES:SE:LP:AF:ID  -0.000120228:0.00159702:0.0268721:0.037076:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101207 ES:SE:LP:AF:ID  0.00108883:0.00116363:0.455932:0.101207:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959088 ES:SE:LP:AF:ID  0.000252786:0.00154021:0.0604807:0.959088:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031438 ES:SE:LP:AF:ID  -0.00119112:0.002798:0.173925:0.031438:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053262 ES:SE:LP:AF:ID  -0.000520773:0.00222403:0.091515:0.053262:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036593 ES:SE:LP:AF:ID  4.08799e-05:0.00160739:0.00877392:0.036593:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036909 ES:SE:LP:AF:ID  0.000111273:0.00159277:0.0268721:0.036909:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843196 ES:SE:LP:AF:ID  -0.000277763:0.000825145:0.130768:0.843196:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055919 ES:SE:LP:AF:ID  -0.00107472:0.00133604:0.376751:0.055919:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122312 ES:SE:LP:AF:ID  0.000450616:0.000903218:0.207608:0.122312:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025715 ES:SE:LP:AF:ID  -0.00189403:0.00222146:0.408935:0.025715:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121555 ES:SE:LP:AF:ID  0.00050429:0.000903597:0.236572:0.121555:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132335 ES:SE:LP:AF:ID  1.19695e-06:0.000890614:-0:0.132335:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011126 ES:SE:LP:AF:ID  -0.00139557:0.00323929:0.173925:0.011126:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036823 ES:SE:LP:AF:ID  0.00010891:0.00157666:0.0268721:0.036823:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83894  ES:SE:LP:AF:ID  -7.91406e-05:0.000799099:0.0362122:0.83894:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838567 ES:SE:LP:AF:ID  -7.84251e-05:0.000798236:0.0362122:0.838567:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869775 ES:SE:LP:AF:ID  -2.20561e-05:0.000856544:0.00877392:0.869775:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  5.92984e-05:0.000858298:0.0268721:0.129876:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  0.000110168:0.0015499:0.0268721:0.037336:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037579 ES:SE:LP:AF:ID  0.000216478:0.00154011:0.05061:0.037579:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  8.81909e-06:0.00085486:0.00436481:0.869116:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -3.32067e-05:0.000855196:0.0132283:0.869214:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037538 ES:SE:LP:AF:ID  0.000115653:0.00154676:0.0268721:0.037538:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86912  ES:SE:LP:AF:ID  -1.32141e-06:0.000854845:-0:0.86912:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83802  ES:SE:LP:AF:ID  -6.38282e-06:0.000796021:0.00436481:0.83802:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037551 ES:SE:LP:AF:ID  0.000150969:0.00154895:0.0362122:0.037551:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838651 ES:SE:LP:AF:ID  -2.22615e-05:0.000798257:0.00877392:0.838651:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013774 ES:SE:LP:AF:ID  9.21434e-05:0.00278643:0.0132283:0.013774:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839765 ES:SE:LP:AF:ID  -0.000198375:0.00080906:0.091515:0.839765:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.8694   ES:SE:LP:AF:ID  -4.21404e-05:0.000853863:0.0177288:0.8694:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86895  ES:SE:LP:AF:ID  -0.000102673:0.000851722:0.0457575:0.86895:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8679   ES:SE:LP:AF:ID  -6.0106e-05:0.000850079:0.0268721:0.8679:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869092 ES:SE:LP:AF:ID  -7.27252e-05:0.000852416:0.0315171:0.869092:rs4951929