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-5474/UKB-b-5474_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5474/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:22 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5474/UKB-b-5474_data.vcf.gz ...
Read summary statistics for 2182519 SNPs.
Dropped 232 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, 556764 SNPs remain.
After merging with regression SNP LD, 556764 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0024 (0.0085)
Lambda GC: 1.0028
Mean Chi^2: 0.9993
Intercept: 0.9956 (0.0094)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Thu Oct 17 14:45:51 2019
Total time elapsed: 29.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7262,
    "inflation_factor": 1,
    "mean_EFFECT": -3.5133e-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": 17285,
    "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": 556764,
    "ldsc_nsnp_merge_regression_ld": 556764,
    "ldsc_observed_scale_h2_beta": 0.0024,
    "ldsc_observed_scale_h2_se": 0.0085,
    "ldsc_intercept_beta": 0.9956,
    "ldsc_intercept_se": 0.0094,
    "ldsc_lambda_gc": 1.0028,
    "ldsc_mean_chisq": 0.9993,
    "ldsc_ratio": 6.2857
}
 

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 2182289 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 2182519 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 8.644588e+00 5.764500e+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 7.870492e+07 5.665296e+07 5687.0000000 3.179712e+07 6.925834e+07 1.148254e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.500000e-06 8.230000e-04 -0.0053650 -5.581000e-04 -2.800000e-06 5.518000e-04 3.954700e-03 ▁▁▇▅▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 8.230000e-04 3.550000e-05 0.0007578 7.939000e-04 8.134000e-04 8.465000e-04 1.603500e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.000102e-01 2.887564e-01 0.0000028 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 5.000067e-01 2.887338e-01 0.0000028 2.503346e-01 4.995111e-01 7.495850e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.636280e-01 1.351458e-01 0.2631580 3.449380e-01 4.460260e-01 5.735940e-01 7.368420e-01 ▇▆▅▅▃
numeric AF_reference 17285 0.9920803 NA NA NA NA NA NA NA 4.440350e-01 1.663889e-01 0.0001997 3.146960e-01 4.325080e-01 5.650960e-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 -0.0022593 0.0013967 0.1100001 0.1057528 0.623812 0.7821490 NA
1 54676 rs2462492 C T 0.0021497 0.0013926 0.1199999 0.1226789 0.399144 NA NA
1 91536 rs6702460 G T 0.0008637 0.0013698 0.5300002 0.5283161 0.455916 0.4207270 NA
1 706368 rs55727773 A G 0.0010244 0.0009656 0.2900000 0.2887180 0.513304 0.2751600 NA
1 763394 rs369924889 G A 0.0018159 0.0011312 0.1100001 0.1084331 0.705804 0.6176120 NA
1 776546 rs12124819 A G 0.0005301 0.0010360 0.6100002 0.6088531 0.263729 0.0756789 NA
1 814495 rs74461805 C A 0.0001703 0.0013222 0.9000000 0.8975182 0.340108 NA NA
1 830181 rs28444699 A G 0.0012834 0.0008846 0.1499999 0.1468327 0.696612 0.6912940 NA
1 831489 rs4970385 C T 0.0015052 0.0008686 0.0830004 0.0831035 0.705031 0.6491610 NA
1 831909 rs9697642 C T 0.0015001 0.0008686 0.0840001 0.0841542 0.705083 0.6485620 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51174662 rs1858748 T C 0.0000279 0.0009310 0.9800000 0.9760726 0.736049 0.732827 NA
22 51180501 rs5770999 T C -0.0000650 0.0009048 0.9400001 0.9427456 0.712571 0.636981 NA
22 51181919 rs9616825 G C 0.0000155 0.0009011 0.9900000 0.9862540 0.695031 0.619409 NA
22 51182485 rs6009961 A G -0.0000507 0.0009078 0.9599999 0.9554392 0.714237 0.638379 NA
22 51186143 rs2879914 T C -0.0004738 0.0008454 0.5800000 0.5752291 0.380077 0.273363 NA
22 51186228 rs3865766 C T 0.0002398 0.0008235 0.7700005 0.7709267 0.449547 0.453275 NA
22 51197266 rs61290853 A G 0.0003526 0.0008486 0.6800001 0.6778025 0.386693 0.422923 NA
22 51211106 rs9628250 T C -0.0005215 0.0009547 0.5800000 0.5848776 0.271468 0.167133 NA
22 51212875 rs2238837 A C -0.0004020 0.0009075 0.6600001 0.6578020 0.331351 0.372404 NA
22 51237063 rs3896457 T C -0.0008562 0.0009272 0.3599996 0.3557741 0.298393 0.205072 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.00225926:0.00139669:0.958607:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  0.0021497:0.00139263:0.920819:0.399144:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  0.000863735:0.00136975:0.275724:0.455916:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  0.00102441:0.00096557:0.537602:0.513304:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.705804 ES:SE:LP:AF:ID  0.00181592:0.00113122:0.958607:0.705804:rs3115847
1   776546  rs12124819  A   G   .   PASS    AF=0.263729 ES:SE:LP:AF:ID  0.000530138:0.00103601:0.21467:0.263729:rs12124819
1   814495  rs74461805  C   A   .   PASS    AF=0.340108 ES:SE:LP:AF:ID  0.000170302:0.00132225:0.0457575:0.340108:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.696612 ES:SE:LP:AF:ID  0.00128341:0.000884616:0.823909:0.696612:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705031 ES:SE:LP:AF:ID  0.00150523:0.000868591:1.08092:0.705031:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705083 ES:SE:LP:AF:ID  0.00150012:0.00086859:1.07572:0.705083:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705261 ES:SE:LP:AF:ID  0.00148485:0.00086855:1.06048:0.705261:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705286 ES:SE:LP:AF:ID  0.0014861:0.000868671:1.06048:0.705286:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730154 ES:SE:LP:AF:ID  0.00120728:0.000892634:0.744727:0.730154:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294729 ES:SE:LP:AF:ID  -0.00149001:0.000868644:1.0655:0.294729:rs28765502
1   836896  rs28705752  T   C   .   PASS    AF=0.269687 ES:SE:LP:AF:ID  -0.00076603:0.000886283:0.408935:0.269687:rs28705752
1   839103  rs28562941  A   G   .   PASS    AF=0.270067 ES:SE:LP:AF:ID  -0.000790393:0.00088701:0.431798:0.270067:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  -0.00188033:0.000801844:1.72125:0.400406:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362367 ES:SE:LP:AF:ID  0.000256038:0.000997631:0.09691:0.362367:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.589315 ES:SE:LP:AF:ID  0.000292271:0.000797497:0.148742:0.589315:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603035 ES:SE:LP:AF:ID  0.000528274:0.000801312:0.29243:0.603035:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603381 ES:SE:LP:AF:ID  0.000576065:0.000801326:0.327902:0.603381:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.588673 ES:SE:LP:AF:ID  0.000298845:0.000798635:0.148742:0.588673:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.588649 ES:SE:LP:AF:ID  0.000343058:0.000798275:0.173925:0.588649:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.606715 ES:SE:LP:AF:ID  0.000493962:0.000802645:0.267606:0.606715:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.60688  ES:SE:LP:AF:ID  0.000484491:0.000802728:0.259637:0.60688:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.609504 ES:SE:LP:AF:ID  0.000534035:0.000803531:0.29243:0.609504:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.602505 ES:SE:LP:AF:ID  0.000535936:0.000801452:0.30103:0.602505:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.609473 ES:SE:LP:AF:ID  0.000548103:0.000803425:0.30103:0.609473:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.390835 ES:SE:LP:AF:ID  -0.000513268:0.000803751:0.283997:0.390835:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.390777 ES:SE:LP:AF:ID  -0.000513642:0.000803834:0.283997:0.390777:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.352504 ES:SE:LP:AF:ID  -0.000305109:0.000825112:0.148742:0.352504:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.608083 ES:SE:LP:AF:ID  0.000372751:0.00081086:0.187087:0.608083:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.301063 ES:SE:LP:AF:ID  -0.000485559:0.000888085:0.236572:0.301063:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.293389 ES:SE:LP:AF:ID  0.000281097:0.000878378:0.124939:0.293389:rs28576697
1   871334  rs4072383   G   T   .   PASS    AF=0.717959 ES:SE:LP:AF:ID  0.000125406:0.000873819:0.05061:0.717959:rs4072383
1   872352  rs1806780   G   C   .   PASS    AF=0.269716 ES:SE:LP:AF:ID  -0.000405493:0.000884667:0.187087:0.269716:rs1806780
1   873558  rs1110052   G   T   .   PASS    AF=0.71249  ES:SE:LP:AF:ID  6.34422e-06:0.000867277:0.00436481:0.71249:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.598464 ES:SE:LP:AF:ID  0.000170342:0.000816924:0.0809219:0.598464:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.65048  ES:SE:LP:AF:ID  -0.00013344:0.000825242:0.0604807:0.65048:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.650626 ES:SE:LP:AF:ID  -7.30444e-05:0.000825161:0.0315171:0.650626:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.650689 ES:SE:LP:AF:ID  -7.78479e-05:0.000826105:0.0362122:0.650689:rs13303106
1   900505  rs28705211  G   C   .   PASS    AF=0.273272 ES:SE:LP:AF:ID  0.000187357:0.000890566:0.0809219:0.273272:rs28705211
1   903245  rs28690976  A   G   .   PASS    AF=0.565133 ES:SE:LP:AF:ID  0.000343772:0.000820313:0.167491:0.565133:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386217 ES:SE:LP:AF:ID  0.000169305:0.000818599:0.0757207:0.386217:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.572164 ES:SE:LP:AF:ID  0.00068773:0.00079195:0.408935:0.572164:rs3829740
1   910394  rs28477686  C   T   .   PASS    AF=0.322663 ES:SE:LP:AF:ID  0.00135038:0.000860214:0.920819:0.322663:rs28477686
1   912049  rs7367995   T   C   .   PASS    AF=0.585242 ES:SE:LP:AF:ID  -0.00126213:0.000799628:0.958607:0.585242:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.600025 ES:SE:LP:AF:ID  -0.00102745:0.000801218:0.69897:0.600025:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.60338  ES:SE:LP:AF:ID  -0.00126373:0.000803936:0.920819:0.60338:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.60101  ES:SE:LP:AF:ID  -0.00105334:0.000802456:0.721246:0.60101:rs13303368