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-10817/UKB-b-10817_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10817/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10817/UKB-b-10817_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: 0.0144 (0.0015)
Lambda GC: 1.2763
Mean Chi^2: 1.2877
Intercept: 1.1687 (0.0076)
Ratio: 0.5862 (0.0265)
Analysis finished at Thu Oct 17 14:42:10 2019
Total time elapsed: 1.0m:52.05s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0.0003,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 8,
    "n_p_sig": 43,
    "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": 0.0144,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.1687,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.2763,
    "ldsc_mean_chisq": 1.2877,
    "ldsc_ratio": 0.5864
}

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 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 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 1.000000 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+07 828.000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.341000e-04 1.105430e-02 -0.190382 -3.275900e-03 7.060000e-05 3.527900e-03 1.798090e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.405000e-03 6.997900e-03 0.002074 2.538800e-03 4.256700e-03 9.819500e-03 1.090630e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.658256e-01 2.974390e-01 0.000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.658251e-01 2.974137e-01 0.000000 1.994708e-01 4.523632e-01 7.238547e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035097e-01 2.568524e-01 0.000867 1.317700e-02 7.792300e-02 3.164240e-01 9.990500e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.000000 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 -0.0035719 0.0038188 0.3500000 0.3496140 0.623965 0.7821490 NA
1 54676 rs2462492 C T 0.0039270 0.0037819 0.2999998 0.2990880 0.400253 NA NA
1 86028 rs114608975 T C 0.0071306 0.0060597 0.2399999 0.2393049 0.103396 0.0277556 NA
1 91536 rs6702460 G T -0.0010382 0.0037231 0.7800007 0.7803624 0.456774 0.4207270 NA
1 234313 rs8179466 C T -0.0036626 0.0073357 0.6200004 0.6175757 0.074661 NA NA
1 534192 rs6680723 C T 0.0010438 0.0042573 0.8100000 0.8063088 0.240786 NA NA
1 546697 rs12025928 A G 0.0094745 0.0052985 0.0739997 0.0737538 0.913314 NA NA
1 693731 rs12238997 A G 0.0043196 0.0035547 0.2200002 0.2243081 0.116854 0.1417730 NA
1 705882 rs72631875 G A 0.0001819 0.0052234 0.9699999 0.9722226 0.067315 0.0315495 NA
1 706368 rs55727773 A G -0.0039039 0.0026398 0.1400000 0.1391707 0.515551 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0035478 0.0055482 0.5199996 0.5225266 0.041870 0.0473243 NA
22 51219766 rs182321900 C T 0.0222504 0.0255188 0.3800004 0.3832510 0.001982 NA NA
22 51220146 rs868950473 C T 0.0186771 0.0252754 0.4600002 0.4599411 0.002031 NA NA
22 51221190 rs369304721 G A 0.0005046 0.0055398 0.9299999 0.9274247 0.049576 NA NA
22 51221731 rs115055839 T C 0.0004947 0.0041451 0.9000000 0.9049953 0.072969 0.0625000 NA
22 51222100 rs114553188 G T 0.0020510 0.0048617 0.6700003 0.6731252 0.054648 0.0880591 NA
22 51223637 rs375798137 G A 0.0019736 0.0048854 0.6899999 0.6862280 0.054274 0.0788738 NA
22 51229805 rs9616985 T C -0.0000939 0.0041600 0.9800000 0.9819990 0.072809 0.0730831 NA
22 51232488 rs376461333 A G -0.0044669 0.0097881 0.6499995 0.6481297 0.020068 NA NA
22 51237063 rs3896457 T C -0.0027797 0.0025396 0.2700001 0.2737195 0.297729 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623965 ES:SE:LP:AF:ID  -0.00357187:0.0038188:0.455932:0.623965:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400253 ES:SE:LP:AF:ID  0.00392705:0.00378186:0.522879:0.400253:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103396 ES:SE:LP:AF:ID  0.00713056:0.00605966:0.619789:0.103396:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456774 ES:SE:LP:AF:ID  -0.00103818:0.00372312:0.107905:0.456774:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074661 ES:SE:LP:AF:ID  -0.00366265:0.00733573:0.207608:0.074661:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240786 ES:SE:LP:AF:ID  0.00104385:0.0042573:0.091515:0.240786:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913314 ES:SE:LP:AF:ID  0.0094745:0.00529853:1.13077:0.913314:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116854 ES:SE:LP:AF:ID  0.00431955:0.00355474:0.657577:0.116854:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067315 ES:SE:LP:AF:ID  0.000181885:0.00522345:0.0132283:0.067315:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515551 ES:SE:LP:AF:ID  -0.00390392:0.00263977:0.853872:0.515551:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033064 ES:SE:LP:AF:ID  0.00793388:0.0066482:0.638272:0.033064:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036686 ES:SE:LP:AF:ID  0.00653435:0.00603814:0.552842:0.036686:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  0.00640568:0.00601438:0.537602:0.036808:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036496 ES:SE:LP:AF:ID  0.00590588:0.00605887:0.481486:0.036496:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016498 ES:SE:LP:AF:ID  -0.00534306:0.00930753:0.244125:0.016498:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037045 ES:SE:LP:AF:ID  0.00626492:0.00599108:0.522879:0.037045:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037143 ES:SE:LP:AF:ID  0.00566233:0.00597042:0.468521:0.037143:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101564 ES:SE:LP:AF:ID  -0.00612755:0.00434688:0.79588:0.101564:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958946 ES:SE:LP:AF:ID  -0.00759123:0.00575367:0.721246:0.958946:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031611 ES:SE:LP:AF:ID  -0.00830907:0.0104191:0.366532:0.031611:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053093 ES:SE:LP:AF:ID  -0.0067992:0.00835206:0.376751:0.053093:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036662 ES:SE:LP:AF:ID  0.00693194:0.00600833:0.60206:0.036662:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036978 ES:SE:LP:AF:ID  0.00661365:0.00595444:0.568636:0.036978:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842588 ES:SE:LP:AF:ID  -0.0052864:0.00308215:1.0655:0.842588:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056119 ES:SE:LP:AF:ID  0.0063218:0.00499113:0.677781:0.056119:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122837 ES:SE:LP:AF:ID  0.00377981:0.00337265:0.585027:0.122837:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02572  ES:SE:LP:AF:ID  -0.00221823:0.00831105:0.102373:0.02572:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122077 ES:SE:LP:AF:ID  0.00391971:0.00337398:0.60206:0.122077:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132784 ES:SE:LP:AF:ID  0.0062313:0.00332703:1.21467:0.132784:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011024 ES:SE:LP:AF:ID  9.34272e-05:0.0121905:0.00436481:0.011024:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005795 ES:SE:LP:AF:ID  -0.00658574:0.0154952:0.173925:0.005795:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002315 ES:SE:LP:AF:ID  -0.00161305:0.0259931:0.0222764:0.002315:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001038 ES:SE:LP:AF:ID  0.0287927:0.0429017:0.30103:0.001038:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036894 ES:SE:LP:AF:ID  0.00627461:0.00589384:0.537602:0.036894:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  -0.00660662:0.00298458:1.56864:0.838313:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837932 ES:SE:LP:AF:ID  -0.00673826:0.00298133:1.61979:0.837932:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869174 ES:SE:LP:AF:ID  -0.00545532:0.00319767:1.05552:0.869174:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130463 ES:SE:LP:AF:ID  0.00611051:0.00320436:1.24413:0.130463:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037404 ES:SE:LP:AF:ID  0.00566288:0.00579352:0.481486:0.037404:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037649 ES:SE:LP:AF:ID  0.00557928:0.00575678:0.481486:0.037649:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868497 ES:SE:LP:AF:ID  -0.00568319:0.00319128:1.12494:0.868497:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868594 ES:SE:LP:AF:ID  -0.00558442:0.00319252:1.09691:0.868594:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037611 ES:SE:LP:AF:ID  0.0058088:0.00578167:0.49485:0.037611:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.8685   ES:SE:LP:AF:ID  -0.0056787:0.0031912:1.12494:0.8685:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005188 ES:SE:LP:AF:ID  0.0255939:0.0163099:0.920819:0.005188:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005154 ES:SE:LP:AF:ID  0.0241795:0.0163524:0.853872:0.005154:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837376 ES:SE:LP:AF:ID  -0.00659575:0.00297289:1.56864:0.837376:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037624 ES:SE:LP:AF:ID  0.00576385:0.00578997:0.49485:0.037624:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838009 ES:SE:LP:AF:ID  -0.00665899:0.00298126:1.58503:0.838009:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013551 ES:SE:LP:AF:ID  -0.00703897:0.0105179:0.30103:0.013551:rs181660517