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-6652/UKB-b-6652_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6652/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6652/UKB-b-6652_data.vcf.gz ...
Read summary statistics for 2450764 SNPs.
Dropped 283 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, 621069 SNPs remain.
After merging with regression SNP LD, 621069 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0017 (0.0014)
Lambda GC: 1.1334
Mean Chi^2: 1.1244
Intercept: 1.1415 (0.0108)
Ratio: 1.1375 (0.0864)
Analysis finished at Thu Oct 17 14:40:51 2019
Total time elapsed: 32.97s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7624,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 1.3906e-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": 19404,
    "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": 621069,
    "ldsc_nsnp_merge_regression_ld": 621069,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.1415,
    "ldsc_intercept_se": 0.0108,
    "ldsc_lambda_gc": 1.1334,
    "ldsc_mean_chisq": 1.1244,
    "ldsc_ratio": 1.1375
}
 

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 2450484 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 2450764 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 8.652162e+00 5.766321e+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 7.856260e+07 5.661981e+07 5687.0000000 3.169393e+07 6.898754e+07 1.147678e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.400000e-06 1.367000e-04 -0.0007560 -9.080000e-05 8.000000e-07 9.340000e-05 6.748000e-04 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.291000e-04 6.800000e-06 0.0001174 1.234000e-04 1.272000e-04 1.337000e-04 2.541000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.817019e-01 2.927759e-01 0.0000009 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.817019e-01 2.927485e-01 0.0000009 2.238978e-01 4.745490e-01 7.348191e-01 9.999995e-01 ▇▇▇▇▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.551410e-01 1.491910e-01 0.2379340 3.239620e-01 4.335930e-01 5.750772e-01 7.620660e-01 ▇▆▅▅▃
numeric AF_reference 19404 0.9920825 NA NA NA NA NA NA NA 4.365522e-01 1.748760e-01 0.0001997 2.987220e-01 4.217250e-01 5.642970e-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 -0.0002620 0.0002160 0.2300001 0.2251040 0.623749 0.7821490 NA
1 54676 rs2462492 C T 0.0001061 0.0002140 0.6200004 0.6202207 0.400420 NA NA
1 91536 rs6702460 G T 0.0000485 0.0002107 0.8200001 0.8180844 0.456859 0.4207270 NA
1 534192 rs6680723 C T -0.0002582 0.0002407 0.2800000 0.2833847 0.240912 NA NA
1 706368 rs55727773 A G -0.0002542 0.0001494 0.0890000 0.0889624 0.515716 0.2751600 NA
1 763394 rs369924889 G A -0.0000217 0.0001752 0.9000000 0.9012697 0.706659 0.6176120 NA
1 768253 rs2977608 A C -0.0001132 0.0001430 0.4299995 0.4287073 0.761326 0.4894170 NA
1 776546 rs12124819 A G -0.0001016 0.0001598 0.5199996 0.5246384 0.265287 0.0756789 NA
1 814495 rs74461805 C A 0.0001904 0.0002049 0.3500000 0.3527929 0.340409 NA NA
1 830181 rs28444699 A G -0.0000014 0.0001371 0.9900000 0.9917926 0.697228 0.6912940 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0001870 0.0001407 0.1800002 0.1837192 0.713710 0.6369810 NA
22 51181919 rs9616825 G C 0.0001991 0.0001400 0.1499999 0.1548210 0.695497 0.6194090 NA
22 51182485 rs6009961 A G 0.0001753 0.0001411 0.2099999 0.2140376 0.715545 0.6383790 NA
22 51186143 rs2879914 T C 0.0001455 0.0001309 0.2700001 0.2661250 0.382031 0.2733630 NA
22 51186228 rs3865766 C T 0.0001185 0.0001275 0.3500000 0.3526466 0.451301 0.4532750 NA
22 51197266 rs61290853 A G 0.0001566 0.0001317 0.2300001 0.2342398 0.386527 0.4229230 NA
22 51198027 rs34939255 A G 0.0000549 0.0001491 0.7099994 0.7125388 0.254380 0.0984425 NA
22 51211106 rs9628250 T C 0.0000646 0.0001478 0.6600001 0.6619349 0.271368 0.1671330 NA
22 51212875 rs2238837 A C 0.0001781 0.0001404 0.2000000 0.2047068 0.331620 0.3724040 NA
22 51237063 rs3896457 T C 0.0001426 0.0001437 0.3200000 0.3209743 0.298157 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623749 ES:SE:LP:AF:ID  -0.000262025:0.000216002:0.638272:0.623749:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40042  ES:SE:LP:AF:ID  0.000106051:0.000214012:0.207608:0.40042:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  4.84584e-05:0.00021068:0.0861861:0.456859:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240912 ES:SE:LP:AF:ID  -0.000258222:0.000240711:0.552842:0.240912:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515716 ES:SE:LP:AF:ID  -0.000254182:0.00014944:1.05061:0.515716:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706659 ES:SE:LP:AF:ID  -2.17329e-05:0.000175184:0.0457575:0.706659:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761326 ES:SE:LP:AF:ID  -0.000113209:0.000143048:0.366532:0.761326:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265287 ES:SE:LP:AF:ID  -0.000101638:0.000159755:0.283997:0.265287:rs12124819
1   814495  rs74461805  C   A   .   PASS    AF=0.340409 ES:SE:LP:AF:ID  0.000190418:0.00020493:0.455932:0.340409:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697228 ES:SE:LP:AF:ID  -1.40987e-06:0.000137059:0.00436481:0.697228:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705392 ES:SE:LP:AF:ID  -7.35486e-05:0.000134575:0.236572:0.705392:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705436 ES:SE:LP:AF:ID  -7.44975e-05:0.000134571:0.236572:0.705436:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705622 ES:SE:LP:AF:ID  -7.63149e-05:0.000134576:0.244125:0.705622:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.70565  ES:SE:LP:AF:ID  -7.57947e-05:0.00013459:0.244125:0.70565:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730094 ES:SE:LP:AF:ID  8.86606e-06:0.000138264:0.0222764:0.730094:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294384 ES:SE:LP:AF:ID  7.52384e-05:0.000134583:0.236572:0.294384:rs28765502
1   833641  rs28594623  T   C   .   PASS    AF=0.239768 ES:SE:LP:AF:ID  0.000223172:0.000142858:0.920819:0.239768:rs28594623
1   835499  rs4422948   A   G   .   PASS    AF=0.241163 ES:SE:LP:AF:ID  0.000199651:0.000142204:0.79588:0.241163:rs4422948
1   836896  rs28705752  T   C   .   PASS    AF=0.269519 ES:SE:LP:AF:ID  0.000281591:0.000137216:1.39794:0.269519:rs28705752
1   838555  rs4970383   C   A   .   PASS    AF=0.246253 ES:SE:LP:AF:ID  0.000189589:0.000141232:0.744727:0.246253:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270021 ES:SE:LP:AF:ID  0.000274879:0.000137309:1.34679:0.270021:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.40029  ES:SE:LP:AF:ID  1.69199e-05:0.000124152:0.05061:0.40029:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362612 ES:SE:LP:AF:ID  0.000141919:0.000154121:0.443698:0.362612:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590335 ES:SE:LP:AF:ID  6.50527e-06:0.000123805:0.0177288:0.590335:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603697 ES:SE:LP:AF:ID  1.12703e-06:0.000124505:0.00436481:0.603697:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603919 ES:SE:LP:AF:ID  -6.11785e-06:0.000124488:0.0177288:0.603919:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589697 ES:SE:LP:AF:ID  8.94217e-06:0.000124006:0.0268721:0.589697:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589682 ES:SE:LP:AF:ID  1.11488e-05:0.000123951:0.0315171:0.589682:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607669 ES:SE:LP:AF:ID  -5.54889e-06:0.000124771:0.0177288:0.607669:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607829 ES:SE:LP:AF:ID  -2.93146e-06:0.000124787:0.00877392:0.607829:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610313 ES:SE:LP:AF:ID  -7.65064e-06:0.00012491:0.0222764:0.610313:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603264 ES:SE:LP:AF:ID  1.08307e-05:0.000124535:0.0315171:0.603264:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610331 ES:SE:LP:AF:ID  -7.80752e-06:0.000124913:0.0222764:0.610331:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389943 ES:SE:LP:AF:ID  4.17354e-06:0.000124938:0.0132283:0.389943:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389927 ES:SE:LP:AF:ID  4.42682e-06:0.000124944:0.0132283:0.389927:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.35034  ES:SE:LP:AF:ID  4.6644e-05:0.000128337:0.142668:0.35034:rs4040605
1   864938  rs2340587   G   A   .   PASS    AF=0.760092 ES:SE:LP:AF:ID  1.53945e-05:0.000142906:0.0409586:0.760092:rs2340587
1   866893  rs2880024   T   C   .   PASS    AF=0.610568 ES:SE:LP:AF:ID  -6.9422e-05:0.00012558:0.236572:0.610568:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297795 ES:SE:LP:AF:ID  0.000131517:0.000138034:0.468521:0.297795:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.291185 ES:SE:LP:AF:ID  0.000114262:0.000136886:0.39794:0.291185:rs28576697
1   871334  rs4072383   G   T   .   PASS    AF=0.72069  ES:SE:LP:AF:ID  -3.52628e-05:0.000136041:0.09691:0.72069:rs4072383
1   872352  rs1806780   G   C   .   PASS    AF=0.267478 ES:SE:LP:AF:ID  6.5814e-05:0.000137879:0.200659:0.267478:rs1806780
1   873558  rs1110052   G   T   .   PASS    AF=0.715324 ES:SE:LP:AF:ID  -4.9135e-05:0.000134971:0.142668:0.715324:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.599966 ES:SE:LP:AF:ID  -0.000149961:0.000126623:0.619789:0.599966:rs4970379
1   877147  rs114982608 G   A   .   PASS    AF=0.242972 ES:SE:LP:AF:ID  8.99546e-05:0.000143411:0.275724:0.242972:rs114982608
1   881627  rs2272757   G   A   .   PASS    AF=0.652302 ES:SE:LP:AF:ID  -0.000164628:0.00012791:0.69897:0.652302:rs2272757
1   882033  rs2272756   G   A   .   PASS    AF=0.24393  ES:SE:LP:AF:ID  0.000117035:0.000142468:0.387216:0.24393:rs2272756
1   890104  rs28631199  G   A   .   PASS    AF=0.246807 ES:SE:LP:AF:ID  0.000134122:0.0001419:0.468521:0.246807:rs28631199
1   891059  rs13303065  C   T   .   PASS    AF=0.652355 ES:SE:LP:AF:ID  -0.00015209:0.000127892:0.638272:0.652355:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.652412 ES:SE:LP:AF:ID  -0.000156088:0.00012804:0.657577:0.652412:rs13303106