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-18189/UKB-b-18189_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18189/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18189/UKB-b-18189_data.vcf.gz ...
Read summary statistics for 6863217 SNPs.
Dropped 4102 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, 1258913 SNPs remain.
After merging with regression SNP LD, 1258913 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0078 (0.0013)
Lambda GC: 1.1611
Mean Chi^2: 1.1694
Intercept: 1.0987 (0.0081)
Ratio: 0.5826 (0.0476)
Analysis finished at Thu Oct 17 14:41:40 2019
Total time elapsed: 1.0m:21.68s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9345,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 4.1815e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 30,
    "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": 63115,
    "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": 1258913,
    "ldsc_nsnp_merge_regression_ld": 1258913,
    "ldsc_observed_scale_h2_beta": 0.0078,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0987,
    "ldsc_intercept_se": 0.0081,
    "ldsc_lambda_gc": 1.1611,
    "ldsc_mean_chisq": 1.1694,
    "ldsc_ratio": 0.5826
}

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 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 6859137 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 6863217 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 8.664480e+00 5.764757e+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 7.861957e+07 5.646650e+07 828.0000000 3.211109e+07 6.905742e+07 1.145179e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.200000e-06 8.200000e-04 -0.0084293 -4.483000e-04 7.000000e-07 4.502000e-04 7.148100e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.039000e-04 3.150000e-04 0.0003999 4.502000e-04 5.730000e-04 8.784000e-04 3.960800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.774581e-01 2.948055e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.774576e-01 2.947792e-01 0.0000000 2.168502e-01 4.690304e-01 7.331486e-01 9.999995e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.804086e-01 2.592179e-01 0.0183730 6.401900e-02 1.859110e-01 4.388710e-01 9.816270e-01 ▇▃▂▁▁
numeric AF_reference 63115 0.9908039 NA NA NA NA NA NA NA 2.784970e-01 2.513163e-01 0.0000000 7.248400e-02 1.974840e-01 4.311100e-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 -0.0007984 0.0007359 0.2800000 0.2779633 0.623741 0.7821490 NA
1 54676 rs2462492 C T -0.0000835 0.0007290 0.9100000 0.9088482 0.400426 NA NA
1 86028 rs114608975 T C 0.0001711 0.0011656 0.8800001 0.8832997 0.103554 0.0277556 NA
1 91536 rs6702460 G T -0.0012108 0.0007178 0.0920005 0.0916388 0.456883 0.4207270 NA
1 234313 rs8179466 C T -0.0015125 0.0014162 0.2900000 0.2855172 0.074476 NA NA
1 534192 rs6680723 C T 0.0002036 0.0008200 0.8000000 0.8039299 0.240976 NA NA
1 546697 rs12025928 A G -0.0011172 0.0010227 0.2700001 0.2746652 0.913454 NA NA
1 693731 rs12238997 A G 0.0010324 0.0006871 0.1299999 0.1329653 0.116324 0.1417730 NA
1 705882 rs72631875 G A 0.0011572 0.0010069 0.2500000 0.2504710 0.067295 0.0315495 NA
1 706368 rs55727773 A G -0.0002786 0.0005090 0.5800000 0.5840590 0.515659 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0011378 0.0006142 0.0640000 0.0639808 0.137953 0.2052720 NA
22 51219387 rs9616832 T C -0.0011749 0.0007974 0.1400000 0.1406364 0.073729 0.0654952 NA
22 51219704 rs147475742 G A -0.0007308 0.0010687 0.4899999 0.4940629 0.041942 0.0473243 NA
22 51221190 rs369304721 G A -0.0012630 0.0010669 0.2399999 0.2365101 0.049714 NA NA
22 51221731 rs115055839 T C -0.0011559 0.0007979 0.1499999 0.1474528 0.073220 0.0625000 NA
22 51222100 rs114553188 G T -0.0011445 0.0009391 0.2200002 0.2229358 0.054481 0.0880591 NA
22 51223637 rs375798137 G A -0.0011772 0.0009436 0.2099999 0.2121889 0.054113 0.0788738 NA
22 51229805 rs9616985 T C -0.0011392 0.0008008 0.1499999 0.1548535 0.073053 0.0730831 NA
22 51232488 rs376461333 A G -0.0017145 0.0018859 0.3599996 0.3632820 0.020048 NA NA
22 51237063 rs3896457 T C 0.0002914 0.0004897 0.5500004 0.5518547 0.297968 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623741 ES:SE:LP:AF:ID  -0.000798378:0.000735896:0.552842:0.623741:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400426 ES:SE:LP:AF:ID  -8.34677e-05:0.00072903:0.0409586:0.400426:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103554 ES:SE:LP:AF:ID  0.000171097:0.00116561:0.0555173:0.103554:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456883 ES:SE:LP:AF:ID  -0.00121084:0.000717826:1.03621:0.456883:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074476 ES:SE:LP:AF:ID  -0.00151248:0.00141617:0.537602:0.074476:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240976 ES:SE:LP:AF:ID  0.000203582:0.000820021:0.09691:0.240976:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913454 ES:SE:LP:AF:ID  -0.00111719:0.00102271:0.568636:0.913454:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116324 ES:SE:LP:AF:ID  0.00103242:0.00068713:0.886057:0.116324:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067295 ES:SE:LP:AF:ID  0.00115717:0.00100693:0.60206:0.067295:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515659 ES:SE:LP:AF:ID  -0.000278649:0.00050898:0.236572:0.515659:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03301  ES:SE:LP:AF:ID  -0.000960899:0.00128323:0.346787:0.03301:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03663  ES:SE:LP:AF:ID  -0.000888465:0.00116551:0.346787:0.03663:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036746 ES:SE:LP:AF:ID  -0.000951377:0.00116109:0.387216:0.036746:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036445 ES:SE:LP:AF:ID  -0.00120012:0.00116947:0.522879:0.036445:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036984 ES:SE:LP:AF:ID  -0.00105343:0.00115652:0.443698:0.036984:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037081 ES:SE:LP:AF:ID  -0.00100436:0.00115254:0.420216:0.037081:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101191 ES:SE:LP:AF:ID  -0.000771497:0.000839886:0.443698:0.101191:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959094 ES:SE:LP:AF:ID  0.000655812:0.00111168:0.251812:0.959094:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031432 ES:SE:LP:AF:ID  0.00540643:0.00201937:2.13077:0.031432:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053273 ES:SE:LP:AF:ID  -0.00185249:0.00160471:0.60206:0.053273:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.0366   ES:SE:LP:AF:ID  -0.00113337:0.00115998:0.481486:0.0366:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036916 ES:SE:LP:AF:ID  -0.00114382:0.00114941:0.49485:0.036916:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843219 ES:SE:LP:AF:ID  -0.000837148:0.000595521:0.79588:0.843219:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055896 ES:SE:LP:AF:ID  0.00187338:0.000964353:1.284:0.055896:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122302 ES:SE:LP:AF:ID  0.000989477:0.000651831:0.886057:0.122302:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025715 ES:SE:LP:AF:ID  0.000623937:0.00160324:0.154902:0.025715:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121545 ES:SE:LP:AF:ID  0.000996634:0.000652096:0.886057:0.121545:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132334 ES:SE:LP:AF:ID  0.000601205:0.000642724:0.455932:0.132334:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036831 ES:SE:LP:AF:ID  -0.000887976:0.0011378:0.356547:0.036831:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838957 ES:SE:LP:AF:ID  -0.000885068:0.000576721:0.920819:0.838957:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838587 ES:SE:LP:AF:ID  -0.000860199:0.000576105:0.853872:0.838587:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869793 ES:SE:LP:AF:ID  -0.00109371:0.000618186:1.11351:0.869793:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129854 ES:SE:LP:AF:ID  0.00101876:0.000619457:1:0.129854:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037341 ES:SE:LP:AF:ID  -0.000832018:0.00111851:0.337242:0.037341:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037584 ES:SE:LP:AF:ID  -0.000869899:0.00111147:0.366532:0.037584:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869136 ES:SE:LP:AF:ID  -0.00106011:0.000616979:1.0655:0.869136:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869235 ES:SE:LP:AF:ID  -0.00105643:0.000617225:1.06048:0.869235:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037542 ES:SE:LP:AF:ID  -0.000883073:0.00111627:0.366532:0.037542:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869139 ES:SE:LP:AF:ID  -0.00105954:0.000616966:1.0655:0.869139:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838038 ES:SE:LP:AF:ID  -0.000830082:0.000574502:0.823909:0.838038:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037555 ES:SE:LP:AF:ID  -0.000946312:0.00111784:0.39794:0.037555:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838669 ES:SE:LP:AF:ID  -0.00084185:0.000576117:0.853872:0.838669:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839784 ES:SE:LP:AF:ID  -0.000893527:0.000583907:0.886057:0.839784:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869415 ES:SE:LP:AF:ID  -0.00106658:0.000616247:1.08092:0.869415:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868963 ES:SE:LP:AF:ID  -0.00104483:0.000614696:1.05061:0.868963:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867922 ES:SE:LP:AF:ID  -0.00107632:0.000613533:1.10237:0.867922:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  -0.00103828:0.0006152:1.04096:0.869106:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  -0.00103728:0.000615248:1.03621:0.869115:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  -0.00103922:0.000615262:1.04096:0.869122:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869599 ES:SE:LP:AF:ID  -0.00107299:0.00061695:1.08619:0.869599:rs3131954