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-9049/UKB-b-9049_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9049/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9049/UKB-b-9049_data.vcf.gz ...
Read summary statistics for 8336011 SNPs.
Dropped 6794 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, 1284567 SNPs remain.
After merging with regression SNP LD, 1284567 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0121 (0.0015)
Lambda GC: 1.1057
Mean Chi^2: 1.1177
Intercept: 1.0073 (0.0075)
Ratio: 0.0618 (0.0638)
Analysis finished at Thu Oct 17 14:43:41 2019
Total time elapsed: 1.0m:31.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9448,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 7.7968e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 78537,
    "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": 1284567,
    "ldsc_nsnp_merge_regression_ld": 1284567,
    "ldsc_observed_scale_h2_beta": 0.0121,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0073,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.1057,
    "ldsc_mean_chisq": 1.1177,
    "ldsc_ratio": 0.062
}

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 8329247 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 8336011 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 8.654581e+00 5.762185e+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 7.874113e+07 5.638490e+07 828.0000000 3.233597e+07 6.923655e+07 1.145495e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.800000e-06 1.845700e-03 -0.0201249 -8.151000e-04 7.100000e-06 8.302000e-04 1.808660e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.520400e-03 9.821000e-04 0.0006430 7.517000e-04 1.078700e-03 2.030500e-03 1.005450e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.872960e-01 2.923777e-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 4.872962e-01 2.923526e-01 0.0000000 2.312191e-01 4.828473e-01 7.407379e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.364501e-01 2.601763e-01 0.0065520 2.957100e-02 1.240790e-01 3.744560e-01 9.934480e-01 ▇▂▂▁▁
numeric AF_reference 78537 0.9905786 NA NA NA NA NA NA NA 2.359680e-01 2.520733e-01 0.0000000 2.915340e-02 1.399760e-01 3.708070e-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 0.0007977 0.0011834 0.5000000 0.5002517 0.623799 0.7821490 NA
1 54676 rs2462492 C T -0.0018470 0.0011722 0.1199999 0.1151273 0.400435 NA NA
1 86028 rs114608975 T C -0.0009382 0.0018745 0.6200004 0.6167269 0.103546 0.0277556 NA
1 91536 rs6702460 G T 0.0010360 0.0011544 0.3700002 0.3694698 0.456844 0.4207270 NA
1 234313 rs8179466 C T -0.0018864 0.0022761 0.4100001 0.4072292 0.074511 NA NA
1 534192 rs6680723 C T 0.0016374 0.0013186 0.2099999 0.2143243 0.240982 NA NA
1 546697 rs12025928 A G 0.0013540 0.0016452 0.4100001 0.4105176 0.913490 NA NA
1 693731 rs12238997 A G 0.0002297 0.0011047 0.8400000 0.8352610 0.116360 0.1417730 NA
1 705882 rs72631875 G A 0.0027481 0.0016195 0.0899995 0.0897261 0.067257 0.0315495 NA
1 706368 rs55727773 A G -0.0005188 0.0008186 0.5300002 0.5262024 0.515625 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0017460 0.0009876 0.0769999 0.0770707 0.137940 0.2052720 NA
22 51219387 rs9616832 T C -0.0007155 0.0012820 0.5800000 0.5767784 0.073713 0.0654952 NA
22 51219704 rs147475742 G A -0.0022112 0.0017177 0.2000000 0.1979894 0.041941 0.0473243 NA
22 51221190 rs369304721 G A -0.0025922 0.0017152 0.1299999 0.1307041 0.049706 NA NA
22 51221731 rs115055839 T C -0.0008323 0.0012828 0.5199996 0.5164876 0.073202 0.0625000 NA
22 51222100 rs114553188 G T -0.0026492 0.0015097 0.0790005 0.0792877 0.054476 0.0880591 NA
22 51223637 rs375798137 G A -0.0026543 0.0015170 0.0800000 0.0801596 0.054106 0.0788738 NA
22 51229805 rs9616985 T C -0.0007680 0.0012875 0.5500004 0.5508308 0.073038 0.0730831 NA
22 51232488 rs376461333 A G -0.0033755 0.0030318 0.2700001 0.2655492 0.020043 NA NA
22 51237063 rs3896457 T C 0.0011179 0.0007873 0.1600000 0.1556480 0.297924 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623799 ES:SE:LP:AF:ID  0.000797709:0.00118338:0.30103:0.623799:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400435 ES:SE:LP:AF:ID  -0.00184695:0.00117225:0.920819:0.400435:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103546 ES:SE:LP:AF:ID  -0.000938192:0.00187453:0.207608:0.103546:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456844 ES:SE:LP:AF:ID  0.001036:0.00115436:0.431798:0.456844:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074511 ES:SE:LP:AF:ID  -0.00188641:0.00227613:0.387216:0.074511:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240982 ES:SE:LP:AF:ID  0.0016374:0.00131861:0.677781:0.240982:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91349  ES:SE:LP:AF:ID  0.00135398:0.00164521:0.387216:0.91349:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11636  ES:SE:LP:AF:ID  0.000229726:0.00110467:0.0757207:0.11636:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067257 ES:SE:LP:AF:ID  0.00274809:0.00161953:1.04576:0.067257:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515625 ES:SE:LP:AF:ID  -0.000518826:0.000818578:0.275724:0.515625:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032997 ES:SE:LP:AF:ID  -0.00222286:0.00206384:0.552842:0.032997:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036611 ES:SE:LP:AF:ID  -0.00162562:0.00187469:0.408935:0.036611:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036726 ES:SE:LP:AF:ID  -0.00169806:0.00186763:0.443698:0.036726:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036428 ES:SE:LP:AF:ID  -0.00134464:0.001881:0.327902:0.036428:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016395 ES:SE:LP:AF:ID  0.00122103:0.00289698:0.173925:0.016395:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036967 ES:SE:LP:AF:ID  -0.00141202:0.00186016:0.346787:0.036967:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  -0.00147714:0.00185374:0.366532:0.037066:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101202 ES:SE:LP:AF:ID  -0.000279503:0.00135044:0.0757207:0.101202:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959115 ES:SE:LP:AF:ID  0.00196158:0.00178813:0.568636:0.959115:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031442 ES:SE:LP:AF:ID  0.00045664:0.0032459:0.05061:0.031442:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053274 ES:SE:LP:AF:ID  -0.00234054:0.00258027:0.443698:0.053274:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036581 ES:SE:LP:AF:ID  -0.00157924:0.00186582:0.39794:0.036581:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036898 ES:SE:LP:AF:ID  -0.00148809:0.00184877:0.376751:0.036898:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.8432   ES:SE:LP:AF:ID  0.000293455:0.000957482:0.119186:0.8432:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055952 ES:SE:LP:AF:ID  -0.000453863:0.00154985:0.113509:0.055952:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122336 ES:SE:LP:AF:ID  0.000563878:0.00104791:0.229148:0.122336:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025701 ES:SE:LP:AF:ID  -0.00379103:0.00257886:0.853872:0.025701:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12158  ES:SE:LP:AF:ID  0.00055007:0.00104835:0.221849:0.12158:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132365 ES:SE:LP:AF:ID  -0.000361924:0.00103331:0.136677:0.132365:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011137 ES:SE:LP:AF:ID  4.46745e-05:0.00375705:0.00436481:0.011137:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036812 ES:SE:LP:AF:ID  -0.00125731:0.00183014:0.309804:0.036812:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838931 ES:SE:LP:AF:ID  -0.000252925:0.000927281:0.102373:0.838931:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838565 ES:SE:LP:AF:ID  -0.00016115:0.000926293:0.0655015:0.838565:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869755 ES:SE:LP:AF:ID  -0.00103338:0.000993911:0.522879:0.869755:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129891 ES:SE:LP:AF:ID  0.00088667:0.000995946:0.431798:0.129891:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037323 ES:SE:LP:AF:ID  -0.00116857:0.00179909:0.283997:0.037323:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037566 ES:SE:LP:AF:ID  -0.00111091:0.00178773:0.275724:0.037566:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000947403:0.000991976:0.468521:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869199 ES:SE:LP:AF:ID  -0.000957963:0.00099237:0.481486:0.869199:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  -0.00128284:0.00179544:0.327902:0.037526:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.000964063:0.000991956:0.481486:0.869104:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838014 ES:SE:LP:AF:ID  -0.000292713:0.000923702:0.124939:0.838014:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -0.00136807:0.00179796:0.346787:0.037539:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838645 ES:SE:LP:AF:ID  -0.000301792:0.0009263:0.130768:0.838645:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013793 ES:SE:LP:AF:ID  -0.000416652:0.00323146:0.0457575:0.013793:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839752 ES:SE:LP:AF:ID  -0.000409792:0.00093882:0.180456:0.839752:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869378 ES:SE:LP:AF:ID  -0.00105392:0.000990796:0.537602:0.869378:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868926 ES:SE:LP:AF:ID  -0.00111018:0.000988303:0.585027:0.868926:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867883 ES:SE:LP:AF:ID  -0.00105391:0.000986412:0.537602:0.867883:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869069 ES:SE:LP:AF:ID  -0.00108126:0.000989113:0.568636:0.869069:rs4951929