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-16576/UKB-b-16576_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16576/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16576/UKB-b-16576_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0621 (0.0024)
Lambda GC: 1.4498
Mean Chi^2: 1.5598
Intercept: 1.0592 (0.009)
Ratio: 0.1058 (0.0161)
Analysis finished at Thu Oct 17 14:46:50 2019
Total time elapsed: 1.0m:38.39s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 43,
    "n_p_sig": 3183,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.0621,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0592,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.4498,
    "ldsc_mean_chisq": 1.5598,
    "ldsc_ratio": 0.1058
}

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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.150000e-05 8.363100e-03 -0.1240810 -2.788300e-03 -1.420000e-05 2.734300e-03 1.535750e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.760800e-03 5.457000e-03 0.0016119 1.972600e-03 3.308000e-03 7.633400e-03 8.487520e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.568234e-01 3.003303e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.568247e-01 3.003052e-01 0.0000000 1.857983e-01 4.414911e-01 7.166013e-01 9.999998e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035071e-01 2.568656e-01 0.0009530 1.316700e-02 7.790700e-02 3.164560e-01 9.990320e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 0.0023414 0.0029638 0.4299995 0.4295348 0.623793 0.7821490 NA
1 54676 rs2462492 C T -0.0045212 0.0029371 0.1199999 0.1237239 0.400406 NA NA
1 86028 rs114608975 T C 0.0025644 0.0046959 0.5800000 0.5849981 0.103551 0.0277556 NA
1 91536 rs6702460 G T 0.0012839 0.0028905 0.6600001 0.6569114 0.456821 0.4207270 NA
1 234313 rs8179466 C T -0.0002619 0.0057004 0.9599999 0.9633579 0.074485 NA NA
1 534192 rs6680723 C T 0.0009056 0.0033017 0.7800007 0.7838630 0.240908 NA NA
1 546697 rs12025928 A G -0.0032317 0.0041208 0.4299995 0.4328950 0.913504 NA NA
1 693731 rs12238997 A G 0.0009362 0.0027692 0.7400005 0.7352902 0.116255 0.1417730 NA
1 705882 rs72631875 G A 0.0091414 0.0040599 0.0239999 0.0243469 0.067196 0.0315495 NA
1 706368 rs55727773 A G 0.0005178 0.0020506 0.8000000 0.8006421 0.515734 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0050382 0.0043080 0.2399999 0.2421959 0.041877 0.0473243 NA
22 51219766 rs182321900 C T 0.0070563 0.0202154 0.7300002 0.7270468 0.001910 NA NA
22 51220146 rs868950473 C T 0.0181322 0.0200019 0.3599996 0.3646586 0.001961 NA NA
22 51221190 rs369304721 G A -0.0022398 0.0043031 0.5999997 0.6027116 0.049592 NA NA
22 51221731 rs115055839 T C -0.0042362 0.0032162 0.1900002 0.1877888 0.073103 0.0625000 NA
22 51222100 rs114553188 G T -0.0092457 0.0037826 0.0150000 0.0145140 0.054490 0.0880591 NA
22 51223637 rs375798137 G A -0.0091837 0.0038009 0.0160000 0.0156838 0.054117 0.0788738 NA
22 51229805 rs9616985 T C -0.0041982 0.0032277 0.1900002 0.1933702 0.072944 0.0730831 NA
22 51232488 rs376461333 A G -0.0154992 0.0076095 0.0420001 0.0416689 0.020014 NA NA
22 51237063 rs3896457 T C 0.0026412 0.0019726 0.1800002 0.1805808 0.297943 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623793 ES:SE:LP:AF:ID  0.00234139:0.00296383:0.366532:0.623793:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  -0.00452118:0.00293711:0.920819:0.400406:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103551 ES:SE:LP:AF:ID  0.00256443:0.00469591:0.236572:0.103551:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456821 ES:SE:LP:AF:ID  0.00128392:0.00289053:0.180456:0.456821:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074485 ES:SE:LP:AF:ID  -0.00026188:0.00570045:0.0177288:0.074485:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240908 ES:SE:LP:AF:ID  0.000905629:0.00330174:0.107905:0.240908:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913504 ES:SE:LP:AF:ID  -0.00323175:0.00412083:0.366532:0.913504:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116255 ES:SE:LP:AF:ID  0.000936241:0.00276915:0.130768:0.116255:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067196 ES:SE:LP:AF:ID  0.00914136:0.00405992:1.61979:0.067196:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515734 ES:SE:LP:AF:ID  0.000517797:0.00205055:0.09691:0.515734:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03298  ES:SE:LP:AF:ID  0.00354893:0.00517038:0.309804:0.03298:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036583 ES:SE:LP:AF:ID  0.0035618:0.00469697:0.346787:0.036583:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036698 ES:SE:LP:AF:ID  0.00318691:0.00467926:0.30103:0.036698:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036404 ES:SE:LP:AF:ID  0.00354057:0.00471257:0.346787:0.036404:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016372 ES:SE:LP:AF:ID  0.00454177:0.00726338:0.275724:0.016372:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03694  ES:SE:LP:AF:ID  0.00411558:0.00466056:0.420216:0.03694:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037044 ES:SE:LP:AF:ID  0.00454001:0.00464406:0.481486:0.037044:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101142 ES:SE:LP:AF:ID  0.000460424:0.00338175:0.05061:0.101142:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959154 ES:SE:LP:AF:ID  -0.00320667:0.00448075:0.327902:0.959154:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031502 ES:SE:LP:AF:ID  -0.013529:0.00811353:1.02228:0.031502:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05331  ES:SE:LP:AF:ID  0.00961575:0.00645805:0.853872:0.05331:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036549 ES:SE:LP:AF:ID  0.00434019:0.00467511:0.455932:0.036549:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036872 ES:SE:LP:AF:ID  0.00423535:0.00463199:0.443698:0.036872:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843292 ES:SE:LP:AF:ID  -0.0016362:0.00239959:0.30103:0.843292:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.0559   ES:SE:LP:AF:ID  -0.0020312:0.00388321:0.221849:0.0559:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122257 ES:SE:LP:AF:ID  0.00112212:0.00262675:0.173925:0.122257:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025718 ES:SE:LP:AF:ID  0.000566509:0.00645765:0.0315171:0.025718:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121494 ES:SE:LP:AF:ID  0.00133653:0.00262808:0.21467:0.121494:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132324 ES:SE:LP:AF:ID  0.00139273:0.00258881:0.229148:0.132324:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  0.0017765:0.00941339:0.0705811:0.011132:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005715 ES:SE:LP:AF:ID  0.0208501:0.0121301:1.0655:0.005715:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002267 ES:SE:LP:AF:ID  -0.0114853:0.020419:0.244125:0.002267:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001028 ES:SE:LP:AF:ID  -0.00773271:0.0335646:0.0861861:0.001028:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036791 ES:SE:LP:AF:ID  0.00364699:0.00458492:0.366532:0.036791:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839056 ES:SE:LP:AF:ID  -0.00197496:0.00232372:0.39794:0.839056:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838689 ES:SE:LP:AF:ID  -0.0018095:0.00232132:0.356547:0.838689:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869881 ES:SE:LP:AF:ID  -0.00175143:0.00249131:0.318759:0.869881:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129771 ES:SE:LP:AF:ID  0.00162771:0.00249642:0.29243:0.129771:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037298 ES:SE:LP:AF:ID  0.0044167:0.00450709:0.481486:0.037298:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037541 ES:SE:LP:AF:ID  0.00435367:0.00447873:0.481486:0.037541:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869223 ES:SE:LP:AF:ID  -0.00173985:0.00248644:0.318759:0.869223:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869318 ES:SE:LP:AF:ID  -0.00162246:0.00248738:0.29243:0.869318:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037498 ES:SE:LP:AF:ID  0.00433969:0.00449806:0.481486:0.037498:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869225 ES:SE:LP:AF:ID  -0.00170916:0.0024864:0.309804:0.869225:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005115 ES:SE:LP:AF:ID  0.0044495:0.0127652:0.136677:0.005115:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00508  ES:SE:LP:AF:ID  0.00365263:0.0127994:0.107905:0.00508:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838143 ES:SE:LP:AF:ID  -0.00204176:0.00231493:0.420216:0.838143:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03751  ES:SE:LP:AF:ID  0.00415994:0.00450453:0.443698:0.03751:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838774 ES:SE:LP:AF:ID  -0.00209545:0.00232143:0.431798:0.838774:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013774 ES:SE:LP:AF:ID  -0.00185673:0.00809808:0.0861861:0.013774:rs181660517