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-15005/UKB-b-15005_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15005/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:51 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15005/UKB-b-15005_data.vcf.gz ...
Read summary statistics for 7891225 SNPs.
Dropped 5924 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, 1281350 SNPs remain.
After merging with regression SNP LD, 1281350 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.016 (0.0022)
Lambda GC: 1.0999
Mean Chi^2: 1.1005
Intercept: 1.0232 (0.0061)
Ratio: 0.2306 (0.061)
Analysis finished at Thu Oct 17 14:45:21 2019
Total time elapsed: 1.0m:30.21s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9424,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -2.0274e-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": 73610,
    "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": 1281350,
    "ldsc_nsnp_merge_regression_ld": 1281350,
    "ldsc_observed_scale_h2_beta": 0.016,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0232,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0999,
    "ldsc_mean_chisq": 1.1005,
    "ldsc_ratio": 0.2308
}

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 7885328 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 7891225 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 8.660912e+00 5.763694e+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 7.870581e+07 5.642455e+07 828.0000000 3.224704e+07 6.917696e+07 1.145601e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.000000e-06 2.562000e-03 -0.0234580 -1.221700e-03 -5.500000e-06 1.213800e-03 2.733680e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.157500e-03 1.267100e-03 0.0010041 1.159000e-03 1.599100e-03 2.826100e-03 1.226650e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.879650e-01 2.923160e-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 4.879672e-01 2.922897e-01 0.0000001 2.314795e-01 4.837838e-01 7.415342e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.485804e-01 2.607968e-01 0.0089510 3.750500e-02 1.407970e-01 3.934750e-01 9.910490e-01 ▇▂▂▁▁
numeric AF_reference 73610 0.9906719 NA NA NA NA NA NA NA 2.477734e-01 2.526323e-01 0.0000000 4.013580e-02 1.559500e-01 3.885780e-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 -0.0023867 0.0018482 0.2000000 0.1965913 0.623695 0.7821490 NA
1 54676 rs2462492 C T 0.0031172 0.0018298 0.0879995 0.0884506 0.400681 NA NA
1 86028 rs114608975 T C 0.0015939 0.0029246 0.5900000 0.5857550 0.103516 0.0277556 NA
1 91536 rs6702460 G T 0.0006126 0.0018036 0.7300002 0.7340953 0.456668 0.4207270 NA
1 234313 rs8179466 C T 0.0068487 0.0035394 0.0530005 0.0529893 0.074802 NA NA
1 534192 rs6680723 C T -0.0000465 0.0020597 0.9800000 0.9819774 0.240941 NA NA
1 546697 rs12025928 A G -0.0019114 0.0025717 0.4600002 0.4573365 0.913746 NA NA
1 693731 rs12238997 A G -0.0028342 0.0017213 0.1000000 0.0996514 0.116422 0.1417730 NA
1 705882 rs72631875 G A 0.0045141 0.0025345 0.0749998 0.0748999 0.066929 0.0315495 NA
1 706368 rs55727773 A G 0.0002616 0.0012769 0.8400000 0.8376513 0.515436 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0009434 0.0015380 0.5400003 0.5396177 0.138606 0.2052720 NA
22 51219387 rs9616832 T C 0.0017039 0.0019955 0.3900004 0.3931759 0.074194 0.0654952 NA
22 51219704 rs147475742 G A -0.0000262 0.0026702 0.9900000 0.9921742 0.042309 0.0473243 NA
22 51221190 rs369304721 G A 0.0024343 0.0026671 0.3599996 0.3613906 0.050099 NA NA
22 51221731 rs115055839 T C 0.0016647 0.0019967 0.4000000 0.4044422 0.073696 0.0625000 NA
22 51222100 rs114553188 G T -0.0013371 0.0023571 0.5700002 0.5705227 0.054577 0.0880591 NA
22 51223637 rs375798137 G A -0.0014514 0.0023685 0.5400003 0.5400077 0.054212 0.0788738 NA
22 51229805 rs9616985 T C 0.0018357 0.0020042 0.3599996 0.3597148 0.073513 0.0730831 NA
22 51232488 rs376461333 A G 0.0028349 0.0047325 0.5500004 0.5491559 0.020032 NA NA
22 51237063 rs3896457 T C -0.0015280 0.0012295 0.2099999 0.2139543 0.297423 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623695 ES:SE:LP:AF:ID  -0.00238669:0.00184825:0.69897:0.623695:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400681 ES:SE:LP:AF:ID  0.00311723:0.00182976:1.05552:0.400681:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103516 ES:SE:LP:AF:ID  0.00159389:0.00292458:0.229148:0.103516:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456668 ES:SE:LP:AF:ID  0.000612642:0.00180357:0.136677:0.456668:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074802 ES:SE:LP:AF:ID  0.00684871:0.00353937:1.27572:0.074802:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240941 ES:SE:LP:AF:ID  -4.65293e-05:0.00205974:0.00877392:0.240941:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913746 ES:SE:LP:AF:ID  -0.00191139:0.0025717:0.337242:0.913746:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116422 ES:SE:LP:AF:ID  -0.00283415:0.00172127:1:0.116422:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066929 ES:SE:LP:AF:ID  0.00451414:0.0025345:1.12494:0.066929:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515436 ES:SE:LP:AF:ID  0.000261631:0.00127688:0.0757207:0.515436:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033237 ES:SE:LP:AF:ID  0.000519379:0.00320942:0.0604807:0.033237:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036836 ES:SE:LP:AF:ID  0.000117857:0.00291739:0.0132283:0.036836:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036942 ES:SE:LP:AF:ID  -3.22609e-05:0.00290733:0.00436481:0.036942:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036658 ES:SE:LP:AF:ID  0.00034001:0.00292715:0.0409586:0.036658:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016434 ES:SE:LP:AF:ID  0.000588978:0.00451603:0.0457575:0.016434:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037204 ES:SE:LP:AF:ID  9.82947e-05:0.00289467:0.0132283:0.037204:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037301 ES:SE:LP:AF:ID  0.00011696:0.00288501:0.0132283:0.037301:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101051 ES:SE:LP:AF:ID  0.00123667:0.0021107:0.251812:0.101051:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958793 ES:SE:LP:AF:ID  -0.00141157:0.00277899:0.21467:0.958793:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031537 ES:SE:LP:AF:ID  -0.00969415:0.00504549:1.25964:0.031537:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053306 ES:SE:LP:AF:ID  0.00357906:0.0040177:0.431798:0.053306:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  -0.000264385:0.00290424:0.0315171:0.036808:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037114 ES:SE:LP:AF:ID  -0.000336813:0.00287802:0.0409586:0.037114:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842785 ES:SE:LP:AF:ID  0.00137525:0.00149051:0.443698:0.842785:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055996 ES:SE:LP:AF:ID  -0.0021717:0.00241809:0.431798:0.055996:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122437 ES:SE:LP:AF:ID  -0.00203011:0.00163216:0.677781:0.122437:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025762 ES:SE:LP:AF:ID  -0.000416078:0.00402026:0.0362122:0.025762:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121649 ES:SE:LP:AF:ID  -0.00199662:0.00163294:0.657577:0.121649:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132632 ES:SE:LP:AF:ID  -0.00237069:0.00160967:0.853872:0.132632:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011235 ES:SE:LP:AF:ID  0.00360618:0.00584863:0.267606:0.011235:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.037053 ES:SE:LP:AF:ID  -0.000245348:0.00284818:0.0315171:0.037053:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838548 ES:SE:LP:AF:ID  0.00214917:0.00144384:0.853872:0.838548:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838134 ES:SE:LP:AF:ID  0.00211954:0.00144205:0.853872:0.838134:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869551 ES:SE:LP:AF:ID  0.00214121:0.00154759:0.769551:0.869551:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130136 ES:SE:LP:AF:ID  -0.00214043:0.00155037:0.769551:0.130136:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037551 ES:SE:LP:AF:ID  -0.000409899:0.00279983:0.0555173:0.037551:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037804 ES:SE:LP:AF:ID  -0.000410178:0.0027819:0.0555173:0.037804:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868852 ES:SE:LP:AF:ID  0.00203919:0.00154429:0.721246:0.868852:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86895  ES:SE:LP:AF:ID  0.00204224:0.00154492:0.721246:0.86895:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037757 ES:SE:LP:AF:ID  -0.000522562:0.00279426:0.0705811:0.037757:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868857 ES:SE:LP:AF:ID  0.00207569:0.00154431:0.744727:0.868857:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837569 ES:SE:LP:AF:ID  0.00204972:0.00143805:0.823909:0.837569:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037772 ES:SE:LP:AF:ID  -0.000623721:0.00279811:0.0861861:0.037772:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838224 ES:SE:LP:AF:ID  0.00211514:0.00144214:0.853872:0.838224:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013657 ES:SE:LP:AF:ID  0.00154333:0.00507397:0.119186:0.013657:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839351 ES:SE:LP:AF:ID  0.00202228:0.00146173:0.769551:0.839351:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  0.00223924:0.00154264:0.823909:0.869154:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868702 ES:SE:LP:AF:ID  0.00228905:0.00153874:0.853872:0.868702:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867609 ES:SE:LP:AF:ID  0.00208681:0.0015355:0.769551:0.867609:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868849 ES:SE:LP:AF:ID  0.00230485:0.00154007:0.886057:0.868849:rs4951929