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-13653/UKB-b-13653_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13653/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:51 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13653/UKB-b-13653_data.vcf.gz ...
Read summary statistics for 9538366 SNPs.
Dropped 11921 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, 1288454 SNPs remain.
After merging with regression SNP LD, 1288454 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0626 (0.0025)
Lambda GC: 1.45
Mean Chi^2: 1.574
Intercept: 1.0239 (0.0092)
Ratio: 0.0416 (0.0161)
Analysis finished at Thu Oct 17 14:44:32 2019
Total time elapsed: 1.0m:41.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9492,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 4.7328e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 38,
    "n_p_sig": 4732,
    "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": 138234,
    "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": 1288454,
    "ldsc_nsnp_merge_regression_ld": 1288454,
    "ldsc_observed_scale_h2_beta": 0.0626,
    "ldsc_observed_scale_h2_se": 0.0025,
    "ldsc_intercept_beta": 1.0239,
    "ldsc_intercept_se": 0.0092,
    "ldsc_lambda_gc": 1.45,
    "ldsc_mean_chisq": 1.574,
    "ldsc_ratio": 0.0416
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 9526506 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 9538366 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 8.628371e+00 5.751236e+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 7.883362e+07 5.630526e+07 828.0000000 3.254291e+07 6.942323e+07 1.145657e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.700000e-06 4.451400e-03 -0.0579563 -1.671600e-03 1.170000e-05 1.683900e-03 6.812860e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.232800e-03 2.741800e-03 0.0010098 1.223500e-03 1.982000e-03 4.389600e-03 3.502840e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.556968e-01 3.005836e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.556958e-01 3.005591e-01 0.0000000 1.842313e-01 4.400944e-01 7.159360e-01 9.999999e-01 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.090814e-01 2.572421e-01 0.0016510 1.548100e-02 8.586100e-02 3.270190e-01 9.983490e-01 ▇▂▁▁▁
numeric AF_reference 138234 0.9855076 NA NA NA NA NA NA NA 2.109172e-01 2.489459e-01 0.0000000 1.317890e-02 1.056310e-01 3.284740e-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 0.0027420 0.0018582 0.1400000 0.1400497 0.623708 0.7821490 NA
1 54676 rs2462492 C T -0.0026721 0.0018400 0.1499999 0.1464344 0.400520 NA NA
1 86028 rs114608975 T C 0.0041578 0.0029451 0.1600000 0.1580215 0.103474 0.0277556 NA
1 91536 rs6702460 G T -0.0001621 0.0018120 0.9299999 0.9287317 0.456917 0.4207270 NA
1 234313 rs8179466 C T -0.0002517 0.0035732 0.9400001 0.9438381 0.074508 NA NA
1 534192 rs6680723 C T -0.0014084 0.0020695 0.5000000 0.4961496 0.240986 NA NA
1 546697 rs12025928 A G 0.0042205 0.0025790 0.1000000 0.1017430 0.913365 NA NA
1 693731 rs12238997 A G 0.0002508 0.0017346 0.8900000 0.8850537 0.116258 0.1417730 NA
1 705882 rs72631875 G A 0.0008265 0.0025393 0.7400005 0.7448266 0.067343 0.0315495 NA
1 706368 rs55727773 A G -0.0018965 0.0012846 0.1400000 0.1398570 0.515770 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0009313 0.0026979 0.7300002 0.7299404 0.041958 0.0473243 NA
22 51219766 rs182321900 C T -0.0118733 0.0125511 0.3400001 0.3441502 0.001944 NA NA
22 51220146 rs868950473 C T -0.0109408 0.0124218 0.3800004 0.3784401 0.001996 NA NA
22 51221190 rs369304721 G A -0.0008872 0.0026940 0.7400005 0.7419243 0.049701 NA NA
22 51221731 rs115055839 T C -0.0001944 0.0020156 0.9199999 0.9231567 0.073165 0.0625000 NA
22 51222100 rs114553188 G T 0.0026639 0.0023715 0.2599998 0.2613143 0.054465 0.0880591 NA
22 51223637 rs375798137 G A 0.0024088 0.0023830 0.3100002 0.3120853 0.054094 0.0788738 NA
22 51229805 rs9616985 T C -0.0000934 0.0020230 0.9599999 0.9631816 0.072997 0.0730831 NA
22 51232488 rs376461333 A G -0.0027203 0.0047584 0.5700002 0.5675444 0.020064 NA NA
22 51237063 rs3896457 T C -0.0001918 0.0012363 0.8800001 0.8767348 0.298073 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623708 ES:SE:LP:AF:ID  0.00274203:0.00185824:0.853872:0.623708:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40052  ES:SE:LP:AF:ID  -0.00267211:0.00183999:0.823909:0.40052:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103474 ES:SE:LP:AF:ID  0.00415778:0.00294511:0.79588:0.103474:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456917 ES:SE:LP:AF:ID  -0.000162071:0.00181205:0.0315171:0.456917:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074508 ES:SE:LP:AF:ID  -0.000251718:0.00357317:0.0268721:0.074508:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240986 ES:SE:LP:AF:ID  -0.00140842:0.0020695:0.30103:0.240986:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913365 ES:SE:LP:AF:ID  0.0042205:0.00257904:1:0.913365:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116258 ES:SE:LP:AF:ID  0.000250758:0.00173456:0.05061:0.116258:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067343 ES:SE:LP:AF:ID  0.000826462:0.0025393:0.130768:0.067343:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51577  ES:SE:LP:AF:ID  -0.00189653:0.00128463:0.853872:0.51577:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032991 ES:SE:LP:AF:ID  0.00385732:0.00323943:0.638272:0.032991:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036599 ES:SE:LP:AF:ID  0.00383777:0.00294263:0.721246:0.036599:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036713 ES:SE:LP:AF:ID  0.00406805:0.00293167:0.769551:0.036713:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03641  ES:SE:LP:AF:ID  0.00432504:0.00295293:0.853872:0.03641:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016414 ES:SE:LP:AF:ID  -0.000425088:0.00454439:0.0315171:0.016414:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036958 ES:SE:LP:AF:ID  0.00443118:0.00291974:0.886057:0.036958:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  0.00416992:0.0029099:0.823909:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101235 ES:SE:LP:AF:ID  0.000576813:0.00211893:0.102373:0.101235:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959113 ES:SE:LP:AF:ID  -0.00241513:0.00280636:0.408935:0.959113:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031452 ES:SE:LP:AF:ID  0.00114867:0.00509235:0.0861861:0.031452:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053275 ES:SE:LP:AF:ID  -0.0032961:0.00405026:0.376751:0.053275:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036576 ES:SE:LP:AF:ID  0.00464845:0.00292852:0.958607:0.036576:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036896 ES:SE:LP:AF:ID  0.00445189:0.00290176:0.920819:0.036896:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843289 ES:SE:LP:AF:ID  -0.000132258:0.00150314:0.0315171:0.843289:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05586  ES:SE:LP:AF:ID  0.000872615:0.00243442:0.142668:0.05586:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122234 ES:SE:LP:AF:ID  2.19006e-05:0.00164547:0.00436481:0.122234:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025702 ES:SE:LP:AF:ID  -0.00456969:0.00404737:0.585027:0.025702:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121473 ES:SE:LP:AF:ID  0.000114663:0.0016462:0.0268721:0.121473:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132258 ES:SE:LP:AF:ID  0.000565524:0.00162237:0.136677:0.132258:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011129 ES:SE:LP:AF:ID  0.00311788:0.00589742:0.221849:0.011129:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005711 ES:SE:LP:AF:ID  -0.00330975:0.00760531:0.180456:0.005711:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002271 ES:SE:LP:AF:ID  -0.0149041:0.012803:0.619789:0.002271:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036809 ES:SE:LP:AF:ID  0.00387126:0.00287255:0.744727:0.036809:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839027 ES:SE:LP:AF:ID  -0.000373958:0.0014558:0.09691:0.839027:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838658 ES:SE:LP:AF:ID  -0.000166068:0.00145423:0.0409586:0.838658:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869848 ES:SE:LP:AF:ID  0.000107579:0.00156057:0.0222764:0.869848:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129808 ES:SE:LP:AF:ID  -9.08918e-05:0.00156376:0.0222764:0.129808:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037325 ES:SE:LP:AF:ID  0.00371712:0.00282362:0.721246:0.037325:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037569 ES:SE:LP:AF:ID  0.00390946:0.00280572:0.79588:0.037569:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86919  ES:SE:LP:AF:ID  0.000177496:0.00155752:0.0409586:0.86919:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869291 ES:SE:LP:AF:ID  0.000174661:0.00155815:0.0409586:0.869291:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  0.00375401:0.00281799:0.744727:0.037526:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869192 ES:SE:LP:AF:ID  0.000144484:0.00155749:0.0315171:0.869192:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00511  ES:SE:LP:AF:ID  -0.0113904:0.0080033:0.823909:0.00511:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005076 ES:SE:LP:AF:ID  -0.0115223:0.00802417:0.823909:0.005076:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838105 ES:SE:LP:AF:ID  -0.000263894:0.00145014:0.0655015:0.838105:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037538 ES:SE:LP:AF:ID  0.00376413:0.00282202:0.744727:0.037538:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838736 ES:SE:LP:AF:ID  -0.000279152:0.00145424:0.0705811:0.838736:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013793 ES:SE:LP:AF:ID  -0.000793496:0.00507197:0.0555173:0.013793:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005559 ES:SE:LP:AF:ID  0.00837008:0.00781943:0.552842:0.005559:rs184270342