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-8549/UKB-b-8549_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8549/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8549/UKB-b-8549_data.vcf.gz ...
Read summary statistics for 1995552 SNPs.
Dropped 196 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, 511401 SNPs remain.
After merging with regression SNP LD, 511401 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0016 (0.0013)
Lambda GC: 1.0203
Mean Chi^2: 1.0187
Intercept: 1.0011 (0.0105)
Ratio: 0.0575 (0.5625)
Analysis finished at Thu Oct 17 14:42:50 2019
Total time elapsed: 54.69s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.6949,
    "inflation_factor": 1,
    "mean_EFFECT": 6.1491e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 32,
    "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": 15816,
    "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": 511401,
    "ldsc_nsnp_merge_regression_ld": 511401,
    "ldsc_observed_scale_h2_beta": 0.0016,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0011,
    "ldsc_intercept_se": 0.0105,
    "ldsc_lambda_gc": 1.0203,
    "ldsc_mean_chisq": 1.0187,
    "ldsc_ratio": 0.0588
}
 

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 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 4 58 0 1995358 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 1995552 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 8.649136e+00 5.763430e+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 7.873488e+07 5.664714e+07 5687.0000000 3.183629e+07 6.927727e+07 1.148468e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 6.000000e-07 1.127000e-04 -0.0006785 -7.550000e-05 2.000000e-07 7.650000e-05 7.235000e-04 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.119000e-04 4.200000e-06 0.0001037 1.086000e-04 1.108000e-04 1.146000e-04 2.127000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.980761e-01 2.892641e-01 0.0000000 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 4.980770e-01 2.892375e-01 0.0000000 2.466859e-01 4.962987e-01 7.495414e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.692727e-01 1.249547e-01 0.2813510 3.594838e-01 4.540760e-01 5.716032e-01 7.186490e-01 ▇▆▆▅▅
numeric AF_reference 15816 0.9920744 NA NA NA NA NA NA NA 4.489606e-01 1.602746e-01 0.0001997 3.254790e-01 4.394970e-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 -0.0000054 0.0001908 0.9800000 0.9776250 0.623765 0.782149 NA
1 54676 rs2462492 C T -0.0001018 0.0001891 0.5900000 0.5900894 0.400401 NA NA
1 91536 rs6702460 G T 0.0000321 0.0001862 0.8600001 0.8630382 0.456846 0.420727 NA
1 706368 rs55727773 A G -0.0001462 0.0001320 0.2700001 0.2680916 0.515645 0.275160 NA
1 763394 rs369924889 G A 0.0001216 0.0001548 0.4299995 0.4319105 0.706753 0.617612 NA
1 814495 rs74461805 C A 0.0002336 0.0001810 0.2000000 0.1969095 0.340396 NA NA
1 830181 rs28444699 A G 0.0000067 0.0001211 0.9599999 0.9557747 0.697255 0.691294 NA
1 831489 rs4970385 C T -0.0000165 0.0001189 0.8900000 0.8899256 0.705397 0.649161 NA
1 831909 rs9697642 C T -0.0000172 0.0001189 0.8800001 0.8848768 0.705442 0.648562 NA
1 832066 rs9697380 G C -0.0000051 0.0001189 0.9699999 0.9660879 0.705627 0.664337 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51171693 rs756638 G A -0.0000818 0.0001231 0.5099998 0.5061727 0.282284 0.304912 NA
22 51174048 rs9628245 G C -0.0001043 0.0001226 0.3900004 0.3950016 0.380135 0.433107 NA
22 51180501 rs5770999 T C 0.0000599 0.0001242 0.6300007 0.6295195 0.713656 0.636981 NA
22 51181919 rs9616825 G C 0.0000935 0.0001236 0.4500005 0.4491926 0.695470 0.619409 NA
22 51182485 rs6009961 A G 0.0000775 0.0001246 0.5300002 0.5339884 0.715502 0.638379 NA
22 51186143 rs2879914 T C 0.0000661 0.0001156 0.5700002 0.5672721 0.381825 0.273363 NA
22 51186228 rs3865766 C T 0.0000468 0.0001126 0.6800001 0.6778286 0.451061 0.453275 NA
22 51197266 rs61290853 A G -0.0000363 0.0001163 0.7600007 0.7552382 0.386333 0.422923 NA
22 51212875 rs2238837 A C -0.0000139 0.0001240 0.9100000 0.9107554 0.331457 0.372404 NA
22 51237063 rs3896457 T C -0.0000046 0.0001270 0.9699999 0.9710677 0.297974 0.205072 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  -5.3524e-06:0.00019084:0.00877392:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.00010185:0.000189064:0.229148:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  3.21134e-05:0.000186156:0.0655015:0.456846:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000146188:0.000132002:0.568636:0.515645:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  0.00012163:0.00015476:0.366532:0.706753:rs3115847
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  0.000233561:0.000180998:0.69897:0.340396:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697255 ES:SE:LP:AF:ID  6.71563e-06:0.000121097:0.0177288:0.697255:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705397 ES:SE:LP:AF:ID  -1.64564e-05:0.000118906:0.05061:0.705397:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705442 ES:SE:LP:AF:ID  -1.72158e-05:0.000118902:0.0555173:0.705442:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705627 ES:SE:LP:AF:ID  -5.05537e-06:0.000118907:0.0132283:0.705627:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705655 ES:SE:LP:AF:ID  -5.21918e-06:0.00011892:0.0177288:0.705655:rs4500250
1   832918  rs28765502  T   C   .   PASS    AF=0.294377 ES:SE:LP:AF:ID  1.39171e-05:0.000118914:0.0409586:0.294377:rs28765502
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  -1.27723e-05:0.00010968:0.0409586:0.400124:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362606 ES:SE:LP:AF:ID  0.000164068:0.000136153:0.638272:0.362606:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590331 ES:SE:LP:AF:ID  -9.47042e-05:0.000109361:0.408935:0.590331:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603723 ES:SE:LP:AF:ID  -8.53534e-05:0.000109974:0.356547:0.603723:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603942 ES:SE:LP:AF:ID  -8.73091e-05:0.000109959:0.366532:0.603942:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589686 ES:SE:LP:AF:ID  -9.84646e-05:0.000109538:0.431798:0.589686:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589665 ES:SE:LP:AF:ID  -9.81584e-05:0.000109489:0.431798:0.589665:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607671 ES:SE:LP:AF:ID  -0.000140884:0.000110204:0.69897:0.607671:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607829 ES:SE:LP:AF:ID  -0.000141861:0.000110219:0.69897:0.607829:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610316 ES:SE:LP:AF:ID  -0.000147:0.000110328:0.744727:0.610316:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603283 ES:SE:LP:AF:ID  -0.000100132:0.000110001:0.443698:0.603283:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610337 ES:SE:LP:AF:ID  -0.000148691:0.00011033:0.744727:0.610337:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389936 ES:SE:LP:AF:ID  0.000154173:0.000110351:0.79588:0.389936:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.38992  ES:SE:LP:AF:ID  0.000154155:0.000110356:0.79588:0.38992:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350356 ES:SE:LP:AF:ID  0.000116211:0.000113367:0.508638:0.350356:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.610552 ES:SE:LP:AF:ID  -4.3587e-05:0.000110949:0.161151:0.610552:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297867 ES:SE:LP:AF:ID  -5.67134e-05:0.000121901:0.19382:0.297867:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.291285 ES:SE:LP:AF:ID  4.73116e-05:0.000120931:0.154902:0.291285:rs28576697
1   873558  rs1110052   G   T   .   PASS    AF=0.715251 ES:SE:LP:AF:ID  -5.97114e-05:0.000119226:0.207608:0.715251:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.600085 ES:SE:LP:AF:ID  2.98288e-05:0.000111871:0.102373:0.600085:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.652393 ES:SE:LP:AF:ID  -1.6044e-05:0.000113009:0.05061:0.652393:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.652432 ES:SE:LP:AF:ID  -1.6067e-05:0.000112992:0.05061:0.652432:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.652494 ES:SE:LP:AF:ID  -1.18779e-05:0.000113123:0.0362122:0.652494:rs13303106
1   903245  rs28690976  A   G   .   PASS    AF=0.566938 ES:SE:LP:AF:ID  -0.000183585:0.000112356:1:0.566938:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386681 ES:SE:LP:AF:ID  -7.45004e-05:0.000112051:0.29243:0.386681:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.571408 ES:SE:LP:AF:ID  1.72706e-05:0.000108518:0.0604807:0.571408:rs3829740
1   910394  rs28477686  C   T   .   PASS    AF=0.324458 ES:SE:LP:AF:ID  -5.3377e-05:0.000117621:0.187087:0.324458:rs28477686
1   912049  rs7367995   T   C   .   PASS    AF=0.585249 ES:SE:LP:AF:ID  2.17185e-05:0.000109618:0.0757207:0.585249:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.59921  ES:SE:LP:AF:ID  -1.05523e-05:0.000109796:0.0362122:0.59921:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.602516 ES:SE:LP:AF:ID  -5.75885e-05:0.000110129:0.221849:0.602516:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.600074 ES:SE:LP:AF:ID  -9.20688e-06:0.000109917:0.0315171:0.600074:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.584289 ES:SE:LP:AF:ID  -1.7094e-07:0.000109301:-0:0.584289:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.589102 ES:SE:LP:AF:ID  -4.12857e-05:0.000109468:0.148742:0.589102:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.584202 ES:SE:LP:AF:ID  2.51862e-06:0.00010925:0.00877392:0.584202:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.589327 ES:SE:LP:AF:ID  -3.11026e-05:0.000109384:0.107905:0.589327:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.583926 ES:SE:LP:AF:ID  -1.57068e-05:0.000113121:0.05061:0.583926:rs4970414
1   921716  rs13303278  C   A   .   PASS    AF=0.567888 ES:SE:LP:AF:ID  -4.34221e-05:0.000109159:0.161151:0.567888:rs13303278
1   924528  rs34712273  C   A   .   PASS    AF=0.578491 ES:SE:LP:AF:ID  -3.97147e-05:0.000109472:0.142668:0.578491:rs34712273