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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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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-7710/UKB-b-7710_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7710/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:52 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7710/UKB-b-7710_data.vcf.gz ...
Read summary statistics for 7904694 SNPs.
Dropped 5961 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, 1281055 SNPs remain.
After merging with regression SNP LD, 1281055 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1394 (0.0173)
Lambda GC: 1.1079
Mean Chi^2: 1.1277
Intercept: 1.0166 (0.0074)
Ratio: 0.1304 (0.0577)
Analysis finished at Thu Oct 17 14:42:23 2019
Total time elapsed: 1.0m:31.75s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9421,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 16,
    "n_p_sig": 642,
    "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": 73737,
    "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": 1281055,
    "ldsc_nsnp_merge_regression_ld": 1281055,
    "ldsc_observed_scale_h2_beta": 0.1394,
    "ldsc_observed_scale_h2_se": 0.0173,
    "ldsc_intercept_beta": 1.0166,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.1079,
    "ldsc_mean_chisq": 1.1277,
    "ldsc_ratio": 0.13
}

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 7898760 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 7904694 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 8.660725e+00 5.763708e+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 7.870419e+07 5.642640e+07 828.0000000 3.224837e+07 6.916675e+07 1.145573e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.750000e-05 1.761090e-02 -0.1959460 -8.309400e-03 3.470000e-05 8.362900e-03 1.935410e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.472520e-02 8.685900e-03 0.0068146 7.884300e-03 1.089400e-02 1.929370e-02 8.241800e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.860106e-01 2.925881e-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 4.860102e-01 2.925619e-01 0.0000000 2.299551e-01 4.809583e-01 7.397084e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.481216e-01 2.608182e-01 0.0088060 3.715500e-02 1.401870e-01 3.929430e-01 9.911940e-01 ▇▂▂▁▁
numeric AF_reference 73737 0.9906717 NA NA NA NA NA NA NA 2.472700e-01 2.526217e-01 0.0000000 3.953670e-02 1.553510e-01 3.877800e-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 0.0001034 0.0124416 0.9900000 0.9933685 0.621393 0.7821490 NA
1 54676 rs2462492 C T 0.0039931 0.0123651 0.7499995 0.7467484 0.401510 NA NA
1 86028 rs114608975 T C -0.0107643 0.0194999 0.5800000 0.5809359 0.104451 0.0277556 NA
1 91536 rs6702460 G T 0.0278525 0.0121365 0.0219999 0.0217367 0.457337 0.4207270 NA
1 234313 rs8179466 C T 0.0202453 0.0239683 0.4000000 0.3982952 0.073935 NA NA
1 534192 rs6680723 C T 0.0006994 0.0138460 0.9599999 0.9597148 0.241068 NA NA
1 546697 rs12025928 A G -0.0023104 0.0175543 0.9000000 0.8952892 0.915206 NA NA
1 693731 rs12238997 A G 0.0004994 0.0118732 0.9699999 0.9664480 0.113460 0.1417730 NA
1 705882 rs72631875 G A -0.0132549 0.0172717 0.4400003 0.4428232 0.066131 0.0315495 NA
1 706368 rs55727773 A G 0.0074828 0.0086653 0.3900004 0.3878374 0.514760 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0002249 0.0104738 0.9800000 0.9828662 0.138239 0.2052720 NA
22 51219387 rs9616832 T C 0.0011475 0.0133657 0.9299999 0.9315812 0.076701 0.0654952 NA
22 51219704 rs147475742 G A -0.0068473 0.0179576 0.6999999 0.7029762 0.043303 0.0473243 NA
22 51221190 rs369304721 G A 0.0011313 0.0177594 0.9500000 0.9492079 0.052223 NA NA
22 51221731 rs115055839 T C 0.0017486 0.0133752 0.9000000 0.8959865 0.076180 0.0625000 NA
22 51222100 rs114553188 G T -0.0009206 0.0163741 0.9599999 0.9551660 0.052689 0.0880591 NA
22 51223637 rs375798137 G A -0.0002928 0.0164542 0.9900000 0.9858026 0.052307 0.0788738 NA
22 51229805 rs9616985 T C 0.0025833 0.0134387 0.8499999 0.8475633 0.075823 0.0730831 NA
22 51232488 rs376461333 A G -0.0168552 0.0328221 0.6100002 0.6075792 0.019190 NA NA
22 51237063 rs3896457 T C -0.0063014 0.0083800 0.4500005 0.4520778 0.299456 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.621393 ES:SE:LP:AF:ID  0.000103408:0.0124416:0.00436481:0.621393:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40151  ES:SE:LP:AF:ID  0.00399306:0.0123651:0.124939:0.40151:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104451 ES:SE:LP:AF:ID  -0.0107643:0.0194999:0.236572:0.104451:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457337 ES:SE:LP:AF:ID  0.0278525:0.0121365:1.65758:0.457337:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.073935 ES:SE:LP:AF:ID  0.0202453:0.0239683:0.39794:0.073935:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241068 ES:SE:LP:AF:ID  0.000699382:0.013846:0.0177288:0.241068:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.915206 ES:SE:LP:AF:ID  -0.0023104:0.0175543:0.0457575:0.915206:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11346  ES:SE:LP:AF:ID  0.000499429:0.0118732:0.0132283:0.11346:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066131 ES:SE:LP:AF:ID  -0.0132549:0.0172717:0.356547:0.066131:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51476  ES:SE:LP:AF:ID  0.00748285:0.00866526:0.408935:0.51476:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032191 ES:SE:LP:AF:ID  -0.00755118:0.0221073:0.136677:0.032191:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.035725 ES:SE:LP:AF:ID  -0.0124341:0.0201024:0.267606:0.035725:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.035777 ES:SE:LP:AF:ID  -0.0114718:0.0200522:0.244125:0.035777:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035528 ES:SE:LP:AF:ID  -0.0103172:0.0201847:0.21467:0.035528:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016184 ES:SE:LP:AF:ID  -0.0021707:0.0307925:0.0268721:0.016184:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036004 ES:SE:LP:AF:ID  -0.0106202:0.0199714:0.229148:0.036004:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036147 ES:SE:LP:AF:ID  -0.00945693:0.0198835:0.200659:0.036147:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.098971 ES:SE:LP:AF:ID  -0.0120247:0.0144415:0.387216:0.098971:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.960699 ES:SE:LP:AF:ID  0.00489682:0.0193044:0.09691:0.960699:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.0302   ES:SE:LP:AF:ID  -0.0610669:0.0357667:1.05552:0.0302:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.054738 ES:SE:LP:AF:ID  0.0014693:0.0264813:0.0177288:0.054738:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.035551 ES:SE:LP:AF:ID  -0.0103482:0.020065:0.21467:0.035551:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03591  ES:SE:LP:AF:ID  -0.0126946:0.0198509:0.283997:0.03591:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.847513 ES:SE:LP:AF:ID  -0.00134126:0.0102833:0.0457575:0.847513:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055223 ES:SE:LP:AF:ID  -0.0128058:0.0165052:0.356547:0.055223:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.119463 ES:SE:LP:AF:ID  0.00226857:0.0112569:0.0757207:0.119463:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.026622 ES:SE:LP:AF:ID  0.00658446:0.0269174:0.091515:0.026622:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.118702 ES:SE:LP:AF:ID  0.00174595:0.0112598:0.0555173:0.118702:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.129102 ES:SE:LP:AF:ID  -0.00204422:0.0110621:0.0705811:0.129102:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011191 ES:SE:LP:AF:ID  0.0078344:0.0396743:0.0757207:0.011191:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.035799 ES:SE:LP:AF:ID  -0.0110624:0.0196608:0.244125:0.035799:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.843164 ES:SE:LP:AF:ID  0.00254647:0.00995758:0.09691:0.843164:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.84294  ES:SE:LP:AF:ID  0.00195414:0.00994781:0.0757207:0.84294:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.873098 ES:SE:LP:AF:ID  0.00165437:0.0106922:0.0555173:0.873098:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.126507 ES:SE:LP:AF:ID  -0.00116899:0.01071:0.0409586:0.126507:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036427 ES:SE:LP:AF:ID  -0.0164565:0.0193007:0.408935:0.036427:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.036658 ES:SE:LP:AF:ID  -0.0157127:0.0191816:0.387216:0.036658:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.872659 ES:SE:LP:AF:ID  0.00113944:0.0106744:0.0409586:0.872659:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.872744 ES:SE:LP:AF:ID  0.00157416:0.0106791:0.0555173:0.872744:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.036599 ES:SE:LP:AF:ID  -0.0166016:0.0192623:0.408935:0.036599:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.87267  ES:SE:LP:AF:ID  0.00108499:0.0106755:0.0362122:0.87267:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.84246  ES:SE:LP:AF:ID  0.00193227:0.0099239:0.0705811:0.84246:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.036598 ES:SE:LP:AF:ID  -0.017191:0.0192894:0.431798:0.036598:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.843046 ES:SE:LP:AF:ID  0.00224876:0.00995123:0.0861861:0.843046:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.015369 ES:SE:LP:AF:ID  -0.00484924:0.0322775:0.0555173:0.015369:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.843502 ES:SE:LP:AF:ID  0.000814846:0.0100714:0.0268721:0.843502:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.872656 ES:SE:LP:AF:ID  7.71697e-05:0.010657:0.00436481:0.872656:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.872201 ES:SE:LP:AF:ID  8.72328e-05:0.0106298:0.00436481:0.872201:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.87156  ES:SE:LP:AF:ID  0.000137822:0.0106197:0.00436481:0.87156:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.872379 ES:SE:LP:AF:ID  -0.000123365:0.0106397:0.00436481:0.872379:rs4951929