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-16671/UKB-b-16671_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16671/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16671/UKB-b-16671_data.vcf.gz ...
Read summary statistics for 4211030 SNPs.
Dropped 856 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, 991122 SNPs remain.
After merging with regression SNP LD, 991122 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0085 (0.0012)
Lambda GC: 1.097
Mean Chi^2: 1.0907
Intercept: 1.0066 (0.0081)
Ratio: 0.0722 (0.0893)
Analysis finished at Thu Oct 17 14:46:10 2019
Total time elapsed: 53.49s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8833,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -2.4223e-07,
    "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": 34596,
    "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": 991122,
    "ldsc_nsnp_merge_regression_ld": 991122,
    "ldsc_observed_scale_h2_beta": 0.0085,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0066,
    "ldsc_intercept_se": 0.0081,
    "ldsc_lambda_gc": 1.097,
    "ldsc_mean_chisq": 1.0907,
    "ldsc_ratio": 0.0728
}

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 4210179 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 4211030 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 8.653763e+00 5.765216e+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 7.859704e+07 5.673653e+07 828.0000000 3.167502e+07 6.896243e+07 1.146783e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.000000e-07 2.220000e-04 -0.0016293 -1.470000e-04 -5.000000e-07 1.459000e-04 1.401800e-03 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.106000e-04 3.220000e-05 0.0001705 1.827000e-04 1.998000e-04 2.324000e-04 6.233000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.854250e-01 2.920316e-01 0.0000003 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 4.854233e-01 2.920060e-01 0.0000003 2.294219e-01 4.791776e-01 7.382000e-01 9.999991e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.852051e-01 2.191371e-01 0.1055490 1.946610e-01 3.334840e-01 5.457000e-01 8.944510e-01 ▇▅▃▂▂
numeric AF_reference 34596 0.9917844 NA NA NA NA NA NA NA 3.752396e-01 2.212456e-01 0.0000000 1.930910e-01 3.312700e-01 5.337460e-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 0.0005129 0.0003136 0.1000000 0.1019724 0.623753 0.782149 NA
1 54676 rs2462492 C T 0.0000440 0.0003107 0.8900000 0.8873570 0.400435 NA NA
1 91536 rs6702460 G T -0.0000205 0.0003060 0.9500000 0.9465768 0.456835 0.420727 NA
1 534192 rs6680723 C T 0.0002953 0.0003495 0.4000000 0.3981924 0.240974 NA NA
1 693731 rs12238997 A G 0.0006497 0.0002929 0.0269998 0.0265420 0.116360 0.141773 NA
1 706368 rs55727773 A G -0.0003653 0.0002170 0.0920005 0.0923065 0.515638 0.275160 NA
1 729679 rs4951859 C G -0.0004776 0.0002538 0.0599998 0.0598738 0.843184 0.639976 NA
1 731718 rs142557973 T C 0.0005193 0.0002778 0.0619998 0.0616035 0.122347 0.154353 NA
1 734349 rs141242758 T C 0.0005200 0.0002779 0.0610000 0.0613317 0.121590 0.152556 NA
1 736289 rs79010578 T A 0.0005494 0.0002739 0.0449997 0.0448935 0.132378 0.139577 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G 0.0000593 0.0002164 0.7800007 0.7841083 0.254513 0.0984425 NA
22 51208537 rs72619593 G A -0.0002241 0.0002892 0.4400003 0.4384064 0.120735 0.1142170 NA
22 51210289 rs112565862 C T 0.0001421 0.0002881 0.6200004 0.6217241 0.129965 0.1018370 NA
22 51211106 rs9628250 T C -0.0000899 0.0002145 0.6800001 0.6753203 0.271518 0.1671330 NA
22 51211392 rs3888396 T C 0.0001614 0.0002855 0.5700002 0.5718084 0.132642 0.1641370 NA
22 51212875 rs2238837 A C 0.0002192 0.0002039 0.2800000 0.2822184 0.331465 0.3724040 NA
22 51213613 rs34726907 C T -0.0001357 0.0002686 0.6100002 0.6134278 0.127811 0.1727240 NA
22 51216564 rs9616970 T C -0.0001505 0.0002674 0.5700002 0.5736126 0.128326 0.1563500 NA
22 51219006 rs28729663 G A -0.0001230 0.0002618 0.6400000 0.6385240 0.137953 0.2052720 NA
22 51237063 rs3896457 T C 0.0001865 0.0002087 0.3700002 0.3714805 0.297970 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623753 ES:SE:LP:AF:ID  0.000512921:0.000313643:1:0.623753:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400435 ES:SE:LP:AF:ID  4.40123e-05:0.000310713:0.05061:0.400435:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456835 ES:SE:LP:AF:ID  -2.0503e-05:0.000305987:0.0222764:0.456835:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240974 ES:SE:LP:AF:ID  0.000295279:0.000349503:0.39794:0.240974:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.11636  ES:SE:LP:AF:ID  0.000649665:0.000292881:1.56864:0.11636:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515638 ES:SE:LP:AF:ID  -0.000365266:0.000216987:1.03621:0.515638:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843184 ES:SE:LP:AF:ID  -0.000477643:0.000253833:1.22185:0.843184:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122347 ES:SE:LP:AF:ID  0.000519286:0.000277821:1.20761:0.122347:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12159  ES:SE:LP:AF:ID  0.000520047:0.000277937:1.21467:0.12159:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132378 ES:SE:LP:AF:ID  0.000549416:0.000273934:1.34679:0.132378:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838931 ES:SE:LP:AF:ID  -0.000406732:0.000245842:1.00877:0.838931:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838562 ES:SE:LP:AF:ID  -0.000414196:0.000245575:1.03621:0.838562:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869765 ES:SE:LP:AF:ID  -0.000375238:0.000263521:0.823909:0.869765:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129888 ES:SE:LP:AF:ID  0.000406761:0.000264055:0.920819:0.129888:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  -0.000373494:0.000263005:0.79588:0.86911:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869209 ES:SE:LP:AF:ID  -0.000371098:0.00026311:0.79588:0.869209:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869113 ES:SE:LP:AF:ID  -0.000385357:0.000263:0.853872:0.869113:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838015 ES:SE:LP:AF:ID  -0.000396836:0.000244895:0.958607:0.838015:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838644 ES:SE:LP:AF:ID  -0.000407859:0.000245584:1.01323:0.838644:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839751 ES:SE:LP:AF:ID  -0.000421724:0.000248904:1.04576:0.839751:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.86939  ES:SE:LP:AF:ID  -0.000354431:0.000262695:0.744727:0.86939:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868936 ES:SE:LP:AF:ID  -0.000356389:0.000262032:0.769551:0.868936:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867895 ES:SE:LP:AF:ID  -0.000354346:0.000261531:0.744727:0.867895:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86908  ES:SE:LP:AF:ID  -0.00035282:0.000262248:0.744727:0.86908:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869088 ES:SE:LP:AF:ID  -0.000352585:0.000262268:0.744727:0.869088:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869096 ES:SE:LP:AF:ID  -0.000348298:0.000262274:0.744727:0.869096:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869575 ES:SE:LP:AF:ID  -0.000356454:0.000262996:0.744727:0.869575:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838292 ES:SE:LP:AF:ID  -0.000382591:0.000244429:0.920819:0.838292:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838413 ES:SE:LP:AF:ID  -0.0003827:0.000244601:0.920819:0.838413:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862257 ES:SE:LP:AF:ID  -0.000299833:0.000261339:0.60206:0.862257:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706744 ES:SE:LP:AF:ID  -0.000159959:0.000254395:0.275724:0.706744:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.76136  ES:SE:LP:AF:ID  -0.000327154:0.000207651:0.920819:0.76136:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.10643  ES:SE:LP:AF:ID  0.000229011:0.000286241:0.376751:0.10643:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129593 ES:SE:LP:AF:ID  0.000387481:0.000263897:0.853872:0.129593:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868897 ES:SE:LP:AF:ID  -0.000352125:0.000262489:0.744727:0.868897:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129696 ES:SE:LP:AF:ID  0.00038207:0.000263723:0.823909:0.129696:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868908 ES:SE:LP:AF:ID  -0.000361862:0.000262495:0.769551:0.868908:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265474 ES:SE:LP:AF:ID  -0.000215341:0.000231919:0.455932:0.265474:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870027 ES:SE:LP:AF:ID  -0.000383755:0.000263028:0.853872:0.870027:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.128598 ES:SE:LP:AF:ID  0.000411965:0.000264061:0.920819:0.128598:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128895 ES:SE:LP:AF:ID  0.00040353:0.000263614:0.886057:0.128895:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868779 ES:SE:LP:AF:ID  -0.000379057:0.000262335:0.823909:0.868779:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129525 ES:SE:LP:AF:ID  0.000398249:0.000263539:0.886057:0.129525:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868535 ES:SE:LP:AF:ID  -0.000354437:0.000262275:0.744727:0.868535:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868476 ES:SE:LP:AF:ID  -0.000360903:0.000262438:0.769551:0.868476:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.860779 ES:SE:LP:AF:ID  -0.000360436:0.000262262:0.769551:0.860779:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.128482 ES:SE:LP:AF:ID  0.000397282:0.00026495:0.886057:0.128482:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861491 ES:SE:LP:AF:ID  -0.000325182:0.000262433:0.657577:0.861491:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  -0.000359683:0.000263391:0.769551:0.869221:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.127904 ES:SE:LP:AF:ID  0.000393078:0.000266647:0.853872:0.127904:rs111818025