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-19158/UKB-b-19158_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19158/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19158/UKB-b-19158_data.vcf.gz ...
Read summary statistics for 6097047 SNPs.
Dropped 2882 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, 1221151 SNPs remain.
After merging with regression SNP LD, 1221151 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0067 (0.0012)
Lambda GC: 1.0725
Mean Chi^2: 1.0793
Intercept: 1.0173 (0.007)
Ratio: 0.2185 (0.0879)
Analysis finished at Thu Oct 17 14:42:11 2019
Total time elapsed: 1.0m:10.29s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9259,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.6226e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 55453,
    "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": 1221151,
    "ldsc_nsnp_merge_regression_ld": 1221151,
    "ldsc_observed_scale_h2_beta": 0.0067,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0173,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0725,
    "ldsc_mean_chisq": 1.0793,
    "ldsc_ratio": 0.2182
}

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 6094184 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 6097047 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 8.670516e+00 5.762249e+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 7.858146e+07 5.651721e+07 828.0000000 3.199820e+07 6.902238e+07 1.145151e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.600000e-06 5.189000e-04 -0.0040160 -3.051000e-04 8.000000e-07 3.068000e-04 4.442000e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.760000e-04 1.655000e-04 0.0003072 3.402000e-04 4.110000e-04 5.720000e-04 1.709600e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.892635e-01 2.914213e-01 0.0000002 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.892664e-01 2.913982e-01 0.0000002 2.346198e-01 4.864941e-01 7.410470e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.079892e-01 2.542629e-01 0.0316490 9.264300e-02 2.247000e-01 4.727890e-01 9.683510e-01 ▇▃▂▂▁
numeric AF_reference 55453 0.9909049 NA NA NA NA NA NA NA 3.047284e-01 2.472387e-01 0.0000000 1.018370e-01 2.324280e-01 4.634580e-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 0.0008274 0.0005654 0.1400000 0.1433454 0.623762 0.7821490 NA
1 54676 rs2462492 C T -0.0002532 0.0005601 0.6499995 0.6512379 0.400415 NA NA
1 86028 rs114608975 T C -0.0001210 0.0008955 0.8900000 0.8925406 0.103553 0.0277556 NA
1 91536 rs6702460 G T 0.0005502 0.0005515 0.3200000 0.3184368 0.456847 0.4207270 NA
1 234313 rs8179466 C T 0.0025510 0.0010872 0.0189998 0.0189601 0.074513 NA NA
1 534192 rs6680723 C T 0.0002445 0.0006300 0.6999999 0.6979635 0.240955 NA NA
1 546697 rs12025928 A G 0.0000802 0.0007859 0.9199999 0.9187465 0.913469 NA NA
1 693731 rs12238997 A G -0.0000185 0.0005279 0.9699999 0.9720825 0.116331 0.1417730 NA
1 705882 rs72631875 G A -0.0001754 0.0007736 0.8200001 0.8206189 0.067287 0.0315495 NA
1 706368 rs55727773 A G 0.0002163 0.0003911 0.5800000 0.5802173 0.515637 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0003770 0.0006112 0.5400003 0.5373422 0.073612 0.0826677 NA
22 51219006 rs28729663 G A -0.0000679 0.0004718 0.8900000 0.8856245 0.137942 0.2052720 NA
22 51219387 rs9616832 T C 0.0003140 0.0006124 0.6100002 0.6081061 0.073734 0.0654952 NA
22 51219704 rs147475742 G A 0.0008025 0.0008207 0.3300000 0.3281910 0.041939 0.0473243 NA
22 51221190 rs369304721 G A 0.0007688 0.0008192 0.3500000 0.3480252 0.049727 NA NA
22 51221731 rs115055839 T C 0.0003346 0.0006128 0.5900000 0.5850370 0.073225 0.0625000 NA
22 51222100 rs114553188 G T -0.0002499 0.0007214 0.7300002 0.7289904 0.054460 0.0880591 NA
22 51223637 rs375798137 G A -0.0002542 0.0007249 0.7300002 0.7257940 0.054089 0.0788738 NA
22 51229805 rs9616985 T C 0.0003182 0.0006150 0.5999997 0.6048181 0.073060 0.0730831 NA
22 51237063 rs3896457 T C 0.0002117 0.0003761 0.5700002 0.5735764 0.297990 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  0.000827368:0.000565356:0.853872:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400415 ES:SE:LP:AF:ID  -0.000253179:0.000560077:0.187087:0.400415:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103553 ES:SE:LP:AF:ID  -0.000120968:0.000895461:0.05061:0.103553:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456847 ES:SE:LP:AF:ID  0.000550213:0.000551495:0.49485:0.456847:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074513 ES:SE:LP:AF:ID  0.00255103:0.00108725:1.72125:0.074513:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240955 ES:SE:LP:AF:ID  0.000244475:0.000629975:0.154902:0.240955:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913469 ES:SE:LP:AF:ID  8.01696e-05:0.000785878:0.0362122:0.913469:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116331 ES:SE:LP:AF:ID  -1.84746e-05:0.000527898:0.0132283:0.116331:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067287 ES:SE:LP:AF:ID  -0.000175414:0.000773604:0.0861861:0.067287:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515637 ES:SE:LP:AF:ID  0.000216293:0.000391079:0.236572:0.515637:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032998 ES:SE:LP:AF:ID  -0.000755958:0.000985983:0.356547:0.032998:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036614 ES:SE:LP:AF:ID  -0.000821099:0.000895596:0.443698:0.036614:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03673  ES:SE:LP:AF:ID  -0.000647007:0.000892215:0.327902:0.03673:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03643  ES:SE:LP:AF:ID  -0.000752104:0.00089862:0.39794:0.03643:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036969 ES:SE:LP:AF:ID  -0.000716559:0.000888673:0.376751:0.036969:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037065 ES:SE:LP:AF:ID  -0.000752526:0.00088563:0.39794:0.037065:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10123  ES:SE:LP:AF:ID  -0.000696873:0.000645091:0.552842:0.10123:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959105 ES:SE:LP:AF:ID  0.000540279:0.000854184:0.275724:0.959105:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053265 ES:SE:LP:AF:ID  -0.00103019:0.00123314:0.39794:0.053265:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036585 ES:SE:LP:AF:ID  -0.00068983:0.000891341:0.356547:0.036585:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036901 ES:SE:LP:AF:ID  -0.000538125:0.000883218:0.267606:0.036901:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843218 ES:SE:LP:AF:ID  0.000222864:0.000457519:0.200659:0.843218:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05592  ES:SE:LP:AF:ID  -0.00113673:0.000740727:0.920819:0.05592:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12231  ES:SE:LP:AF:ID  -0.000145434:0.000500769:0.113509:0.12231:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121555 ES:SE:LP:AF:ID  -0.000143196:0.000500977:0.107905:0.121555:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132327 ES:SE:LP:AF:ID  -0.000284529:0.000493793:0.251812:0.132327:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036814 ES:SE:LP:AF:ID  -0.00069383:0.000874326:0.366532:0.036814:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  0.000175313:0.000443078:0.161151:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838573 ES:SE:LP:AF:ID  0.000162501:0.0004426:0.148742:0.838573:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869766 ES:SE:LP:AF:ID  -3.30598e-05:0.000474919:0.0268721:0.869766:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129884 ES:SE:LP:AF:ID  9.65051e-05:0.000475883:0.0757207:0.129884:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037325 ES:SE:LP:AF:ID  -0.000751751:0.000859495:0.420216:0.037325:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037569 ES:SE:LP:AF:ID  -0.000725434:0.000854056:0.39794:0.037569:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869108 ES:SE:LP:AF:ID  -5.07443e-05:0.000473988:0.0409586:0.869108:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869206 ES:SE:LP:AF:ID  -4.18366e-05:0.000474175:0.0315171:0.869206:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  -0.000694425:0.000857755:0.376751:0.037527:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869111 ES:SE:LP:AF:ID  -4.90624e-05:0.000473978:0.0362122:0.869111:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838026 ES:SE:LP:AF:ID  0.000175469:0.00044137:0.161151:0.838026:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  -0.000683092:0.000858965:0.366532:0.03754:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838657 ES:SE:LP:AF:ID  0.000164423:0.000442612:0.148742:0.838657:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839766 ES:SE:LP:AF:ID  0.00020471:0.000448598:0.187087:0.839766:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869392 ES:SE:LP:AF:ID  -1.68013e-05:0.000473431:0.0132283:0.869392:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868939 ES:SE:LP:AF:ID  -6.29549e-05:0.00047224:0.05061:0.868939:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867892 ES:SE:LP:AF:ID  -1.51526e-05:0.000471333:0.0132283:0.867892:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869081 ES:SE:LP:AF:ID  -4.42332e-05:0.000472626:0.0315171:0.869081:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  -4.60142e-05:0.000472662:0.0362122:0.869089:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869097 ES:SE:LP:AF:ID  -4.62891e-05:0.000472673:0.0362122:0.869097:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869574 ES:SE:LP:AF:ID  -2.62526e-05:0.000473971:0.0177288:0.869574:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.03759  ES:SE:LP:AF:ID  -0.000632932:0.000853921:0.337242:0.03759:rs114525117
1   760912  rs1048488   C   T   .   PASS    AF=0.838307 ES:SE:LP:AF:ID  0.000153718:0.000440537:0.136677:0.838307:rs1048488