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-1350/UKB-b-1350_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1350/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:47 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1350/UKB-b-1350_data.vcf.gz ...
Read summary statistics for 6660518 SNPs.
Dropped 3783 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, 1251070 SNPs remain.
After merging with regression SNP LD, 1251070 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0061 (0.001)
Lambda GC: 1.0907
Mean Chi^2: 1.0916
Intercept: 1.0368 (0.006)
Ratio: 0.4017 (0.0659)
Analysis finished at Thu Oct 17 14:44:06 2019
Total time elapsed: 1.0m:18.91s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9325,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 4.1186e-06,
    "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": 61158,
    "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": 1251070,
    "ldsc_nsnp_merge_regression_ld": 1251070,
    "ldsc_observed_scale_h2_beta": 0.0061,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0368,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0907,
    "ldsc_mean_chisq": 1.0916,
    "ldsc_ratio": 0.4017
}

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 6656757 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 6660518 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 8.664065e+00 5.763882e+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 7.860244e+07 5.648108e+07 828.0000000 3.206788e+07 6.905242e+07 1.145020e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.100000e-06 7.097000e-04 -0.0063091 -3.948000e-04 1.500000e-06 3.993000e-04 6.816900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.338000e-04 2.664000e-04 0.0003732 4.182000e-04 5.246000e-04 7.839000e-04 3.262300e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.874445e-01 2.922025e-01 0.0000001 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.874445e-01 2.921756e-01 0.0000002 2.313612e-01 4.826292e-01 7.407927e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.874126e-01 2.583007e-01 0.0212010 7.082700e-02 1.958250e-01 4.477420e-01 9.787980e-01 ▇▃▂▂▁
numeric AF_reference 61158 0.9908178 NA NA NA NA NA NA NA 2.852107e-01 2.505413e-01 0.0000000 7.987220e-02 2.062700e-01 4.398960e-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 -0.0011005 0.0006867 0.1100001 0.1090253 0.623770 0.7821490 NA
1 54676 rs2462492 C T 0.0009116 0.0006805 0.1800002 0.1803555 0.400399 NA NA
1 86028 rs114608975 T C -0.0017211 0.0010879 0.1100001 0.1136356 0.103553 0.0277556 NA
1 91536 rs6702460 G T 0.0006649 0.0006699 0.3200000 0.3209760 0.456861 0.4207270 NA
1 234313 rs8179466 C T -0.0020384 0.0013209 0.1199999 0.1228023 0.074508 NA NA
1 534192 rs6680723 C T 0.0004620 0.0007653 0.5500004 0.5460504 0.240947 NA NA
1 546697 rs12025928 A G 0.0003345 0.0009547 0.7300002 0.7260799 0.913479 NA NA
1 693731 rs12238997 A G -0.0009074 0.0006413 0.1600000 0.1570905 0.116336 0.1417730 NA
1 705882 rs72631875 G A -0.0000623 0.0009398 0.9500000 0.9471235 0.067300 0.0315495 NA
1 706368 rs55727773 A G -0.0003559 0.0004751 0.4500005 0.4538273 0.515669 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0004918 0.0007423 0.5099998 0.5076815 0.073614 0.0826677 NA
22 51219006 rs28729663 G A 0.0001595 0.0005731 0.7800007 0.7807898 0.137946 0.2052720 NA
22 51219387 rs9616832 T C 0.0004211 0.0007438 0.5700002 0.5713484 0.073738 0.0654952 NA
22 51219704 rs147475742 G A 0.0014422 0.0009967 0.1499999 0.1479088 0.041957 0.0473243 NA
22 51221190 rs369304721 G A 0.0011611 0.0009951 0.2399999 0.2432629 0.049733 NA NA
22 51221731 rs115055839 T C 0.0005008 0.0007443 0.5000000 0.5010540 0.073229 0.0625000 NA
22 51222100 rs114553188 G T -0.0005335 0.0008764 0.5400003 0.5426913 0.054460 0.0880591 NA
22 51223637 rs375798137 G A -0.0005234 0.0008806 0.5500004 0.5522786 0.054089 0.0788738 NA
22 51229805 rs9616985 T C 0.0005768 0.0007470 0.4400003 0.4400012 0.073065 0.0730831 NA
22 51237063 rs3896457 T C 0.0001764 0.0004569 0.6999999 0.6995130 0.297977 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62377  ES:SE:LP:AF:ID  -0.00110054:0.000686726:0.958607:0.62377:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400399 ES:SE:LP:AF:ID  0.000911626:0.00068049:0.744727:0.400399:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103553 ES:SE:LP:AF:ID  -0.00172114:0.00108791:0.958607:0.103553:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456861 ES:SE:LP:AF:ID  0.000664863:0.000669918:0.49485:0.456861:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074508 ES:SE:LP:AF:ID  -0.00203835:0.00132093:0.920819:0.074508:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240947 ES:SE:LP:AF:ID  0.000461993:0.000765283:0.259637:0.240947:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913479 ES:SE:LP:AF:ID  0.000334489:0.000954742:0.136677:0.913479:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116336 ES:SE:LP:AF:ID  -0.000907431:0.000641328:0.79588:0.116336:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0673   ES:SE:LP:AF:ID  -6.23248e-05:0.000939766:0.0222764:0.0673:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515669 ES:SE:LP:AF:ID  -0.000355878:0.000475106:0.346787:0.515669:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033017 ES:SE:LP:AF:ID  -0.00201227:0.00119744:1.03152:0.033017:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036633 ES:SE:LP:AF:ID  -0.00186095:0.00108771:1.06048:0.036633:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03675  ES:SE:LP:AF:ID  -0.00196467:0.00108359:1.1549:0.03675:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036448 ES:SE:LP:AF:ID  -0.00181622:0.00109143:1.01773:0.036448:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036987 ES:SE:LP:AF:ID  -0.00183442:0.00107934:1.05061:0.036987:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037084 ES:SE:LP:AF:ID  -0.00188287:0.00107564:1.09691:0.037084:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  0.000991727:0.000783842:0.677781:0.101206:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959082 ES:SE:LP:AF:ID  0.00150621:0.0010374:0.823909:0.959082:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031433 ES:SE:LP:AF:ID  0.00138229:0.00188482:0.337242:0.031433:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053267 ES:SE:LP:AF:ID  0.00278837:0.00149794:1.20066:0.053267:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036601 ES:SE:LP:AF:ID  -0.00188243:0.00108261:1.08619:0.036601:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036917 ES:SE:LP:AF:ID  -0.00190698:0.00107275:1.12494:0.036917:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843178 ES:SE:LP:AF:ID  0.00103395:0.000555774:1.20066:0.843178:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05592  ES:SE:LP:AF:ID  0.0004448:0.000899915:0.207608:0.05592:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122326 ES:SE:LP:AF:ID  -0.000790049:0.000608352:0.721246:0.122326:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02572  ES:SE:LP:AF:ID  0.00181062:0.0014962:0.638272:0.02572:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121569 ES:SE:LP:AF:ID  -0.000720028:0.000608606:0.619789:0.121569:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132349 ES:SE:LP:AF:ID  -0.000826139:0.000599864:0.769551:0.132349:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036832 ES:SE:LP:AF:ID  -0.00189215:0.0010619:1.12494:0.036832:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838917 ES:SE:LP:AF:ID  0.0010462:0.00053823:1.284:0.838917:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838544 ES:SE:LP:AF:ID  0.00100555:0.000537649:1.21467:0.838544:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869759 ES:SE:LP:AF:ID  0.000742019:0.000576927:0.69897:0.869759:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129895 ES:SE:LP:AF:ID  -0.000786416:0.000578096:0.769551:0.129895:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037345 ES:SE:LP:AF:ID  -0.00182959:0.00104387:1.09691:0.037345:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037589 ES:SE:LP:AF:ID  -0.00177018:0.00103728:1.05552:0.037589:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869099 ES:SE:LP:AF:ID  0.000710825:0.000575793:0.657577:0.869099:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869197 ES:SE:LP:AF:ID  0.000720327:0.00057602:0.677781:0.869197:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037547 ES:SE:LP:AF:ID  -0.001771:0.00104176:1.05061:0.037547:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  0.000707229:0.000575783:0.657577:0.869103:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837997 ES:SE:LP:AF:ID  0.00102853:0.000536156:1.25964:0.837997:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03756  ES:SE:LP:AF:ID  -0.00172677:0.00104323:1.00877:0.03756:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838627 ES:SE:LP:AF:ID  0.000999574:0.000537662:1.20066:0.838627:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839743 ES:SE:LP:AF:ID  0.00109112:0.00054494:1.34679:0.839743:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869384 ES:SE:LP:AF:ID  0.000748898:0.000575121:0.721246:0.869384:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868933 ES:SE:LP:AF:ID  0.000734276:0.000573676:0.69897:0.868933:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867884 ES:SE:LP:AF:ID  0.000684685:0.000572572:0.638272:0.867884:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869076 ES:SE:LP:AF:ID  0.000736371:0.000574146:0.69897:0.869076:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869084 ES:SE:LP:AF:ID  0.000735247:0.00057419:0.69897:0.869084:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869092 ES:SE:LP:AF:ID  0.000738672:0.000574203:0.69897:0.869092:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869568 ES:SE:LP:AF:ID  0.000745894:0.000575776:0.69897:0.869568:rs3131954