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-6538/UKB-b-6538_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6538/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-6538/UKB-b-6538_data.vcf.gz ...
Read summary statistics for 2018081 SNPs.
Dropped 201 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, 516929 SNPs remain.
After merging with regression SNP LD, 516929 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0002 (0.0013)
Lambda GC: 1.0165
Mean Chi^2: 1.0222
Intercept: 1.02 (0.0107)
Ratio: 0.9035 (0.4831)
Analysis finished at Thu Oct 17 14:40:49 2019
Total time elapsed: 30.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.6989,
    "inflation_factor": 1,
    "mean_EFFECT": -5.2272e-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": 16022,
    "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": 516929,
    "ldsc_nsnp_merge_regression_ld": 516929,
    "ldsc_observed_scale_h2_beta": 0.0002,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.02,
    "ldsc_intercept_se": 0.0107,
    "ldsc_lambda_gc": 1.0165,
    "ldsc_mean_chisq": 1.0222,
    "ldsc_ratio": 0.9009
}
 

Flags

name value
af_correlation TRUE
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 2017882 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 2018081 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 8.648259e+00 5.763879e+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 7.872480e+07 5.664432e+07 5687.0000000 3.182465e+07 6.929218e+07 1.148182e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.000000e-07 1.138000e-04 -0.0005800 -7.690000e-05 -7.000000e-07 7.590000e-05 5.427000e-04 ▁▂▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.126000e-04 4.300000e-06 0.0001042 1.092000e-04 1.115000e-04 1.153000e-04 2.138000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.973838e-01 2.893184e-01 0.0000071 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 4.973843e-01 2.892937e-01 0.0000071 2.467368e-01 4.966447e-01 7.472001e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.686598e-01 1.262134e-01 0.2791070 3.577240e-01 4.530310e-01 5.719350e-01 7.208930e-01 ▇▆▆▅▅
numeric AF_reference 16022 0.9920608 NA NA NA NA NA NA NA 4.484506e-01 1.610425e-01 0.0001997 3.240810e-01 4.386980e-01 5.652960e-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 0.0001787 0.0001918 0.3500000 0.3515555 0.623763 0.782149 NA
1 54676 rs2462492 C T -0.0003075 0.0001901 0.1100001 0.1056323 0.400401 NA NA
1 91536 rs6702460 G T -0.0000467 0.0001871 0.8000000 0.8031391 0.456851 0.420727 NA
1 706368 rs55727773 A G -0.0000081 0.0001327 0.9500000 0.9515953 0.515650 0.275160 NA
1 763394 rs369924889 G A 0.0000010 0.0001556 0.9900000 0.9949539 0.706753 0.617612 NA
1 814495 rs74461805 C A -0.0003723 0.0001820 0.0409996 0.0407748 0.340397 NA NA
1 830181 rs28444699 A G 0.0000369 0.0001217 0.7600007 0.7620132 0.697259 0.691294 NA
1 831489 rs4970385 C T 0.0001059 0.0001195 0.3800004 0.3757984 0.705403 0.649161 NA
1 831909 rs9697642 C T 0.0001049 0.0001195 0.3800004 0.3800270 0.705448 0.648562 NA
1 832066 rs9697380 G C 0.0001074 0.0001195 0.3700002 0.3689868 0.705634 0.664337 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51171693 rs756638 G A -0.0000896 0.0001237 0.4700002 0.4691558 0.282282 0.304912 NA
22 51174048 rs9628245 G C 0.0000626 0.0001233 0.6100002 0.6115722 0.380130 0.433107 NA
22 51180501 rs5770999 T C -0.0001602 0.0001249 0.2000000 0.1994765 0.713658 0.636981 NA
22 51181919 rs9616825 G C -0.0001498 0.0001243 0.2300001 0.2279395 0.695471 0.619409 NA
22 51182485 rs6009961 A G -0.0001741 0.0001253 0.1600000 0.1647232 0.715505 0.638379 NA
22 51186143 rs2879914 T C 0.0000930 0.0001162 0.4199997 0.4234141 0.381826 0.273363 NA
22 51186228 rs3865766 C T 0.0000241 0.0001132 0.8300000 0.8315336 0.451063 0.453275 NA
22 51197266 rs61290853 A G 0.0000063 0.0001169 0.9599999 0.9571323 0.386333 0.422923 NA
22 51212875 rs2238837 A C 0.0000921 0.0001247 0.4600002 0.4600915 0.331455 0.372404 NA
22 51237063 rs3896457 T C 0.0000904 0.0001276 0.4799997 0.4788528 0.297971 0.205072 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.000178722:0.000191849:0.455932:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000307547:0.000190062:0.958607:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -4.6652e-05:0.000187142:0.09691:0.456851:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -8.05543e-06:0.000132701:0.0222764:0.51565:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  9.83943e-07:0.00015558:0.00436481:0.706753:rs3115847
1   814495  rs74461805  C   A   .   PASS    AF=0.340397 ES:SE:LP:AF:ID  -0.000372254:0.000181959:1.38722:0.340397:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697259 ES:SE:LP:AF:ID  3.68663e-05:0.000121736:0.119186:0.697259:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705403 ES:SE:LP:AF:ID  0.000105867:0.000119534:0.420216:0.705403:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705448 ES:SE:LP:AF:ID  0.000104929:0.00011953:0.420216:0.705448:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705634 ES:SE:LP:AF:ID  0.000107387:0.000119535:0.431798:0.705634:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705662 ES:SE:LP:AF:ID  0.000107585:0.000119548:0.431798:0.705662:rs4500250
1   832918  rs28765502  T   C   .   PASS    AF=0.294371 ES:SE:LP:AF:ID  -0.000108154:0.000119542:0.431798:0.294371:rs28765502
1   840753  rs4970382   T   C   .   PASS    AF=0.400106 ES:SE:LP:AF:ID  -3.83579e-05:0.00011026:0.136677:0.400106:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362599 ES:SE:LP:AF:ID  0.000131759:0.000136876:0.468521:0.362599:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590333 ES:SE:LP:AF:ID  1.62293e-05:0.000109937:0.0555173:0.590333:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603726 ES:SE:LP:AF:ID  1.77359e-05:0.000110554:0.0604807:0.603726:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603944 ES:SE:LP:AF:ID  2.82881e-05:0.000110538:0.09691:0.603944:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589688 ES:SE:LP:AF:ID  3.80515e-07:0.000110116:-0:0.589688:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589667 ES:SE:LP:AF:ID  -7.15018e-07:0.000110066:0.00436481:0.589667:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607674 ES:SE:LP:AF:ID  1.26168e-05:0.000110786:0.0409586:0.607674:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607833 ES:SE:LP:AF:ID  1.08994e-05:0.000110801:0.0362122:0.607833:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610318 ES:SE:LP:AF:ID  1.86795e-05:0.00011091:0.0604807:0.610318:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603286 ES:SE:LP:AF:ID  4.72119e-07:0.000110581:-0:0.603286:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610338 ES:SE:LP:AF:ID  1.8079e-05:0.000110912:0.0604807:0.610338:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389935 ES:SE:LP:AF:ID  -2.38454e-05:0.000110933:0.0809219:0.389935:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389918 ES:SE:LP:AF:ID  -2.38216e-05:0.000110938:0.0809219:0.389918:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350351 ES:SE:LP:AF:ID  3.28461e-05:0.000113965:0.113509:0.350351:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.610554 ES:SE:LP:AF:ID  -5.27606e-05:0.000111535:0.19382:0.610554:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297865 ES:SE:LP:AF:ID  -3.53481e-05:0.000122546:0.113509:0.297865:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.291287 ES:SE:LP:AF:ID  -9.38579e-05:0.000121569:0.356547:0.291287:rs28576697
1   871334  rs4072383   G   T   .   PASS    AF=0.720619 ES:SE:LP:AF:ID  7.58771e-05:0.000120816:0.275724:0.720619:rs4072383
1   873558  rs1110052   G   T   .   PASS    AF=0.715253 ES:SE:LP:AF:ID  8.20557e-05:0.000119856:0.309804:0.715253:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.600084 ES:SE:LP:AF:ID  -9.92807e-06:0.000112462:0.0315171:0.600084:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.65239  ES:SE:LP:AF:ID  -3.60505e-05:0.000113606:0.124939:0.65239:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.652428 ES:SE:LP:AF:ID  -4.11242e-05:0.000113588:0.142668:0.652428:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.65249  ES:SE:LP:AF:ID  -4.30213e-05:0.00011372:0.148742:0.65249:rs13303106
1   903245  rs28690976  A   G   .   PASS    AF=0.566937 ES:SE:LP:AF:ID  0.000111596:0.000112949:0.49485:0.566937:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386683 ES:SE:LP:AF:ID  3.57418e-05:0.000112642:0.124939:0.386683:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.571412 ES:SE:LP:AF:ID  5.36328e-05:0.00010909:0.207608:0.571412:rs3829740
1   910394  rs28477686  C   T   .   PASS    AF=0.324456 ES:SE:LP:AF:ID  -8.45916e-05:0.000118242:0.327902:0.324456:rs28477686
1   912049  rs7367995   T   C   .   PASS    AF=0.58525  ES:SE:LP:AF:ID  4.3242e-05:0.000110196:0.161151:0.58525:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.599213 ES:SE:LP:AF:ID  0.000109984:0.000110376:0.49485:0.599213:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.602521 ES:SE:LP:AF:ID  0.000117331:0.00011071:0.537602:0.602521:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.600078 ES:SE:LP:AF:ID  0.000114151:0.000110498:0.522879:0.600078:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.584292 ES:SE:LP:AF:ID  0.000139708:0.000109878:0.69897:0.584292:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.589106 ES:SE:LP:AF:ID  0.000146186:0.000110046:0.744727:0.589106:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.584205 ES:SE:LP:AF:ID  0.000142623:0.000109826:0.721246:0.584205:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.589331 ES:SE:LP:AF:ID  0.000147211:0.000109961:0.744727:0.589331:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.583932 ES:SE:LP:AF:ID  0.000198419:0.000113719:1.09151:0.583932:rs4970414
1   921716  rs13303278  C   A   .   PASS    AF=0.567888 ES:SE:LP:AF:ID  0.000161952:0.000109735:0.853872:0.567888:rs13303278