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-17868/UKB-b-17868_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17868/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:28 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17868/UKB-b-17868_data.vcf.gz ...
Read summary statistics for 6941343 SNPs.
Dropped 4211 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, 1261722 SNPs remain.
After merging with regression SNP LD, 1261722 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0205 (0.0022)
Lambda GC: 1.0947
Mean Chi^2: 1.1131
Intercept: 1.011 (0.0074)
Ratio: 0.0974 (0.0654)
Analysis finished at Thu Oct 17 14:41:55 2019
Total time elapsed: 1.0m:26.71s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9353,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -3.0127e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 6,
    "n_p_sig": 143,
    "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": 63858,
    "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": 1261722,
    "ldsc_nsnp_merge_regression_ld": 1261722,
    "ldsc_observed_scale_h2_beta": 0.0205,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.011,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.0947,
    "ldsc_mean_chisq": 1.1131,
    "ldsc_ratio": 0.0973
}

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 6937154 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 6941343 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 8.664206e+00 5.763992e+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 7.862828e+07 5.645245e+07 828.0000000 3.213043e+07 6.907252e+07 1.145155e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.000000e-06 1.513600e-03 -0.0156103 -8.286000e-04 -2.000000e-06 8.225000e-04 1.311560e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.337700e-03 6.128000e-04 0.0007484 8.451000e-04 1.081800e-03 1.676200e-03 7.415500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.870871e-01 2.922813e-01 0.0000000 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 4.870874e-01 2.922568e-01 0.0000000 2.302315e-01 4.833950e-01 7.398627e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.778642e-01 2.595865e-01 0.0173960 6.161200e-02 1.822420e-01 4.354870e-01 9.826030e-01 ▇▃▂▁▁
numeric AF_reference 63858 0.9908003 NA NA NA NA NA NA NA 2.760640e-01 2.516238e-01 0.0000000 6.968850e-02 1.940890e-01 4.279150e-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 -0.0016614 0.0013799 0.2300001 0.2285648 0.623401 0.7821490 NA
1 54676 rs2462492 C T 0.0029813 0.0013642 0.0290001 0.0288565 0.401018 NA NA
1 86028 rs114608975 T C -0.0004917 0.0021882 0.8200001 0.8222161 0.103479 0.0277556 NA
1 91536 rs6702460 G T 0.0023148 0.0013439 0.0850002 0.0849835 0.457119 0.4207270 NA
1 234313 rs8179466 C T -0.0006543 0.0026550 0.8100000 0.8053529 0.074433 NA NA
1 534192 rs6680723 C T -0.0000150 0.0015357 0.9900000 0.9922127 0.241303 NA NA
1 546697 rs12025928 A G 0.0020059 0.0019165 0.2999998 0.2952617 0.913550 NA NA
1 693731 rs12238997 A G -0.0008748 0.0012856 0.5000000 0.4961745 0.116712 0.1417730 NA
1 705882 rs72631875 G A -0.0002835 0.0018876 0.8800001 0.8806309 0.067085 0.0315495 NA
1 706368 rs55727773 A G -0.0004396 0.0009534 0.6400000 0.6447249 0.515095 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0002388 0.0011524 0.8400000 0.8358206 0.137893 0.2052720 NA
22 51219387 rs9616832 T C 0.0003349 0.0014950 0.8200001 0.8227317 0.073629 0.0654952 NA
22 51219704 rs147475742 G A 0.0008426 0.0020037 0.6700003 0.6741081 0.041840 0.0473243 NA
22 51221190 rs369304721 G A 0.0012688 0.0020016 0.5300002 0.5261522 0.049595 NA NA
22 51221731 rs115055839 T C 0.0003766 0.0014956 0.8000000 0.8012125 0.073159 0.0625000 NA
22 51222100 rs114553188 G T -0.0015991 0.0017580 0.3599996 0.3630178 0.054619 0.0880591 NA
22 51223637 rs375798137 G A -0.0016467 0.0017664 0.3500000 0.3512293 0.054253 0.0788738 NA
22 51229805 rs9616985 T C 0.0002389 0.0015009 0.8700001 0.8735219 0.073027 0.0730831 NA
22 51232488 rs376461333 A G -0.0065216 0.0035308 0.0649995 0.0647366 0.020062 NA NA
22 51237063 rs3896457 T C 0.0020566 0.0009168 0.0250000 0.0248747 0.297965 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623401 ES:SE:LP:AF:ID  -0.00166144:0.00137986:0.638272:0.623401:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.401018 ES:SE:LP:AF:ID  0.00298127:0.00136415:1.5376:0.401018:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103479 ES:SE:LP:AF:ID  -0.000491679:0.0021882:0.0861861:0.103479:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457119 ES:SE:LP:AF:ID  0.0023148:0.00134388:1.07058:0.457119:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074433 ES:SE:LP:AF:ID  -0.000654262:0.00265501:0.091515:0.074433:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241303 ES:SE:LP:AF:ID  -1.49884e-05:0.00153569:0.00436481:0.241303:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91355  ES:SE:LP:AF:ID  0.00200586:0.00191646:0.522879:0.91355:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116712 ES:SE:LP:AF:ID  -0.000874844:0.00128555:0.30103:0.116712:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067085 ES:SE:LP:AF:ID  -0.000283466:0.00188764:0.0555173:0.067085:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515095 ES:SE:LP:AF:ID  -0.00043962:0.00095341:0.19382:0.515095:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032861 ES:SE:LP:AF:ID  -0.00446889:0.00240869:1.19382:0.032861:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036427 ES:SE:LP:AF:ID  -0.00431871:0.00218999:1.3098:0.036427:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036535 ES:SE:LP:AF:ID  -0.00426187:0.0021821:1.29243:0.036535:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036226 ES:SE:LP:AF:ID  -0.00436993:0.0021982:1.3279:0.036226:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036755 ES:SE:LP:AF:ID  -0.00409712:0.00217409:1.22915:0.036755:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036848 ES:SE:LP:AF:ID  -0.00447714:0.00216678:1.40894:0.036848:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101008 ES:SE:LP:AF:ID  0.00280202:0.00157476:1.12494:0.101008:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959342 ES:SE:LP:AF:ID  0.004007:0.0020896:1.25964:0.959342:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031378 ES:SE:LP:AF:ID  0.000116261:0.00377749:0.00877392:0.031378:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053413 ES:SE:LP:AF:ID  0.000396698:0.00299955:0.05061:0.053413:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036398 ES:SE:LP:AF:ID  -0.00388908:0.00217924:1.13077:0.036398:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036722 ES:SE:LP:AF:ID  -0.00409221:0.00215953:1.23657:0.036722:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843037 ES:SE:LP:AF:ID  0.00184141:0.00111554:1.00436:0.843037:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056083 ES:SE:LP:AF:ID  -0.000698244:0.00180425:0.154902:0.056083:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122718 ES:SE:LP:AF:ID  -0.000884019:0.00121922:0.327902:0.122718:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025572 ES:SE:LP:AF:ID  0.00157681:0.00301149:0.221849:0.025572:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121939 ES:SE:LP:AF:ID  -0.000882358:0.00121975:0.327902:0.121939:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13258  ES:SE:LP:AF:ID  -0.00182696:0.00120308:0.886057:0.13258:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036626 ES:SE:LP:AF:ID  -0.00431928:0.00213815:1.36653:0.036626:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838737 ES:SE:LP:AF:ID  0.00146498:0.00107987:0.769551:0.838737:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838362 ES:SE:LP:AF:ID  0.00133312:0.0010788:0.657577:0.838362:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86939  ES:SE:LP:AF:ID  0.000548683:0.00115643:0.19382:0.86939:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130261 ES:SE:LP:AF:ID  -0.000430498:0.00115903:0.148742:0.130261:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037104 ES:SE:LP:AF:ID  -0.00420762:0.00210249:1.34679:0.037104:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037365 ES:SE:LP:AF:ID  -0.00418891:0.00208856:1.34679:0.037365:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868723 ES:SE:LP:AF:ID  0.000439162:0.00115432:0.154902:0.868723:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868797 ES:SE:LP:AF:ID  0.000401093:0.00115473:0.136677:0.868797:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037312 ES:SE:LP:AF:ID  -0.00426109:0.00209786:1.37675:0.037312:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868724 ES:SE:LP:AF:ID  0.000438279:0.00115428:0.154902:0.868724:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83781  ES:SE:LP:AF:ID  0.00138938:0.00107576:0.69897:0.83781:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037325 ES:SE:LP:AF:ID  -0.00426579:0.00210102:1.37675:0.037325:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838442 ES:SE:LP:AF:ID  0.00136049:0.00107878:0.677781:0.838442:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839577 ES:SE:LP:AF:ID  0.00143808:0.00109322:0.721246:0.839577:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869015 ES:SE:LP:AF:ID  0.000483595:0.0011528:0.173925:0.869015:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868557 ES:SE:LP:AF:ID  0.000453619:0.00114992:0.161151:0.868557:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867537 ES:SE:LP:AF:ID  0.000368236:0.00114806:0.124939:0.867537:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868704 ES:SE:LP:AF:ID  0.000477512:0.00115089:0.167491:0.868704:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868713 ES:SE:LP:AF:ID  0.000479366:0.00115098:0.167491:0.868713:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868721 ES:SE:LP:AF:ID  0.000477389:0.001151:0.167491:0.868721:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86919  ES:SE:LP:AF:ID  0.000523088:0.0011541:0.187087:0.86919:rs3131954