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-20435/UKB-b-20435_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20435/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20435/UKB-b-20435_data.vcf.gz ...
Read summary statistics for 2419500 SNPs.
Dropped 278 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, 613734 SNPs remain.
After merging with regression SNP LD, 613734 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0002 (0.0012)
Lambda GC: 1.0134
Mean Chi^2: 1.0104
Intercept: 1.0126 (0.0101)
Ratio: 1.2092 (0.9711)
Analysis finished at Thu Oct 17 14:42:43 2019
Total time elapsed: 35.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7584,
    "inflation_factor": 1,
    "mean_EFFECT": -3.04e-07,
    "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": 19136,
    "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": 613734,
    "ldsc_nsnp_merge_regression_ld": 613734,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0126,
    "ldsc_intercept_se": 0.0101,
    "ldsc_lambda_gc": 1.0134,
    "ldsc_mean_chisq": 1.0104,
    "ldsc_ratio": 1.2115
}
 

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 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 4 58 0 2419225 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 2419500 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 8.651970e+00 5.766934e+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 7.859171e+07 5.663792e+07 5687.0000000 3.171863e+07 6.902129e+07 1.147799e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.000000e-07 1.243000e-04 -0.0006012 -8.410000e-05 -5.000000e-07 8.360000e-05 6.537000e-04 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.232000e-04 6.300000e-06 0.0001122 1.178000e-04 1.214000e-04 1.275000e-04 2.429000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.965972e-01 2.888959e-01 0.0000021 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.965990e-01 2.888696e-01 0.0000021 2.454307e-01 4.953399e-01 7.464219e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.561183e-01 1.475820e-01 0.2407160 3.262500e-01 4.351300e-01 5.749432e-01 7.592840e-01 ▇▆▅▅▃
numeric AF_reference 19136 0.9920909 NA NA NA NA NA NA NA 4.374314e-01 1.738626e-01 0.0001997 3.007190e-01 4.229230e-01 5.644970e-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 0.0000056 0.0002065 0.9800000 0.9782656 0.623765 0.7821490 NA
1 54676 rs2462492 C T -0.0001501 0.0002045 0.4600002 0.4629627 0.400401 NA NA
1 91536 rs6702460 G T -0.0000696 0.0002014 0.7300002 0.7297103 0.456846 0.4207270 NA
1 534192 rs6680723 C T -0.0000742 0.0002300 0.7499995 0.7471977 0.240959 NA NA
1 706368 rs55727773 A G 0.0001760 0.0001428 0.2200002 0.2177831 0.515645 0.2751600 NA
1 763394 rs369924889 G A 0.0001846 0.0001674 0.2700001 0.2702468 0.706753 0.6176120 NA
1 776546 rs12124819 A G 0.0002259 0.0001526 0.1400000 0.1388561 0.265385 0.0756789 NA
1 814495 rs74461805 C A 0.0000574 0.0001958 0.7700005 0.7694392 0.340396 NA NA
1 830181 rs28444699 A G 0.0002033 0.0001310 0.1199999 0.1206482 0.697255 0.6912940 NA
1 831489 rs4970385 C T 0.0002437 0.0001286 0.0580003 0.0581711 0.705397 0.6491610 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0003316 0.0001344 0.0140001 0.0136080 0.713656 0.6369810 NA
22 51181919 rs9616825 G C 0.0003687 0.0001337 0.0058000 0.0058330 0.695470 0.6194090 NA
22 51182485 rs6009961 A G 0.0003398 0.0001348 0.0120000 0.0117339 0.715502 0.6383790 NA
22 51186143 rs2879914 T C 0.0001062 0.0001250 0.4000000 0.3957668 0.381825 0.2733630 NA
22 51186228 rs3865766 C T 0.0001871 0.0001218 0.1199999 0.1247329 0.451061 0.4532750 NA
22 51197266 rs61290853 A G 0.0001283 0.0001258 0.3100002 0.3076759 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0000862 0.0001424 0.5400003 0.5449250 0.254562 0.0984425 NA
22 51211106 rs9628250 T C 0.0001543 0.0001412 0.2700001 0.2744963 0.271547 0.1671330 NA
22 51212875 rs2238837 A C 0.0001486 0.0001342 0.2700001 0.2681110 0.331457 0.3724040 NA
22 51237063 rs3896457 T C 0.0000863 0.0001373 0.5300002 0.5295968 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  5.62457e-06:0.000206456:0.00877392:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000150124:0.000204535:0.337242:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -6.95821e-05:0.000201389:0.136677:0.456846:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  -7.41503e-05:0.00023004:0.124939:0.240959:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  0.000175998:0.000142804:0.657577:0.515645:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  0.000184584:0.000167424:0.568636:0.706753:rs3115847
1   776546  rs12124819  A   G   .   PASS    AF=0.265385 ES:SE:LP:AF:ID  0.000225917:0.00015264:0.853872:0.265385:rs12124819
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  5.73933e-05:0.000195809:0.113509:0.340396:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697255 ES:SE:LP:AF:ID  0.000203329:0.000131006:0.920819:0.697255:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705397 ES:SE:LP:AF:ID  0.000243687:0.000128635:1.23657:0.705397:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705442 ES:SE:LP:AF:ID  0.000243004:0.000128631:1.22915:0.705442:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705627 ES:SE:LP:AF:ID  0.000241137:0.000128637:1.21467:0.705627:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705655 ES:SE:LP:AF:ID  0.000240649:0.000128651:1.21467:0.705655:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730129 ES:SE:LP:AF:ID  0.000154285:0.000132156:0.619789:0.730129:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294377 ES:SE:LP:AF:ID  -0.000240818:0.000128645:1.21467:0.294377:rs28765502
1   835499  rs4422948   A   G   .   PASS    AF=0.241162 ES:SE:LP:AF:ID  -0.000182193:0.000135902:0.744727:0.241162:rs4422948
1   836896  rs28705752  T   C   .   PASS    AF=0.269511 ES:SE:LP:AF:ID  -0.000178606:0.000131135:0.769551:0.269511:rs28705752
1   838555  rs4970383   C   A   .   PASS    AF=0.246204 ES:SE:LP:AF:ID  -7.43356e-05:0.000134968:0.236572:0.246204:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270019 ES:SE:LP:AF:ID  -0.000177893:0.000131228:0.744727:0.270019:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  -0.00014793:0.000118655:0.677781:0.400124:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362606 ES:SE:LP:AF:ID  1.7192e-05:0.000147294:0.0409586:0.362606:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590331 ES:SE:LP:AF:ID  -1.25693e-05:0.000118309:0.0362122:0.590331:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603723 ES:SE:LP:AF:ID  -2.82283e-05:0.000118973:0.091515:0.603723:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603942 ES:SE:LP:AF:ID  -2.3522e-05:0.000118957:0.0757207:0.603942:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589686 ES:SE:LP:AF:ID  -1.28214e-05:0.000118502:0.0409586:0.589686:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589665 ES:SE:LP:AF:ID  -1.23786e-05:0.000118448:0.0362122:0.589665:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607671 ES:SE:LP:AF:ID  -3.89987e-05:0.000119222:0.130768:0.607671:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607829 ES:SE:LP:AF:ID  -3.48224e-05:0.000119238:0.113509:0.607829:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610316 ES:SE:LP:AF:ID  -1.87931e-05:0.000119356:0.0604807:0.610316:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603283 ES:SE:LP:AF:ID  -2.86084e-05:0.000119002:0.091515:0.603283:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610337 ES:SE:LP:AF:ID  -2.38046e-05:0.000119358:0.0757207:0.610337:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389936 ES:SE:LP:AF:ID  1.13685e-05:0.000119381:0.0362122:0.389936:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.38992  ES:SE:LP:AF:ID  1.13198e-05:0.000119387:0.0362122:0.38992:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350356 ES:SE:LP:AF:ID  -2.17906e-05:0.000122644:0.0655015:0.350356:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.610552 ES:SE:LP:AF:ID  3.32313e-05:0.000120028:0.107905:0.610552:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297867 ES:SE:LP:AF:ID  -0.000192658:0.000131875:0.853872:0.297867:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.291285 ES:SE:LP:AF:ID  -0.000242987:0.000130826:1.20066:0.291285:rs28576697
1   871334  rs4072383   G   T   .   PASS    AF=0.72062  ES:SE:LP:AF:ID  0.000252474:0.000130015:1.284:0.72062:rs4072383
1   872352  rs1806780   G   C   .   PASS    AF=0.267527 ES:SE:LP:AF:ID  -0.000262038:0.000131778:1.3279:0.267527:rs1806780
1   873558  rs1110052   G   T   .   PASS    AF=0.715251 ES:SE:LP:AF:ID  0.000258855:0.000128982:1.34679:0.715251:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.600085 ES:SE:LP:AF:ID  4.25858e-05:0.000121025:0.142668:0.600085:rs4970379
1   877147  rs114982608 G   A   .   PASS    AF=0.242966 ES:SE:LP:AF:ID  -0.000220402:0.000137071:0.958607:0.242966:rs114982608
1   881627  rs2272757   G   A   .   PASS    AF=0.652393 ES:SE:LP:AF:ID  2.52845e-05:0.000122256:0.0757207:0.652393:rs2272757
1   882033  rs2272756   G   A   .   PASS    AF=0.243918 ES:SE:LP:AF:ID  -0.00017063:0.000136163:0.677781:0.243918:rs2272756
1   890104  rs28631199  G   A   .   PASS    AF=0.246771 ES:SE:LP:AF:ID  -0.00020879:0.000135627:0.920819:0.246771:rs28631199
1   891059  rs13303065  C   T   .   PASS    AF=0.652432 ES:SE:LP:AF:ID  1.49007e-05:0.000122238:0.0457575:0.652432:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.652494 ES:SE:LP:AF:ID  1.72074e-05:0.00012238:0.05061:0.652494:rs13303106
1   900505  rs28705211  G   C   .   PASS    AF=0.271763 ES:SE:LP:AF:ID  -0.000236244:0.000132302:1.13077:0.271763:rs28705211
1   903245  rs28690976  A   G   .   PASS    AF=0.566938 ES:SE:LP:AF:ID  -0.000100913:0.00012155:0.387216:0.566938:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386681 ES:SE:LP:AF:ID  -6.67184e-05:0.00012122:0.236572:0.386681:rs3892467