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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_2267.vcf.gz --id UKB-b:7422 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2267.txt.gz --cohort_controls 459416 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-7422/ukb-b-7422.vcf.gz; Date=Sun May 10 14:39:41 2020"
}
 

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-7422/UKB-b-7422_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7422/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7422/UKB-b-7422_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0587 (0.0049)
Lambda GC: 1.4238
Mean Chi^2: 1.5997
Intercept: 1.0648 (0.0108)
Ratio: 0.108 (0.0179)
Analysis finished at Thu Oct 17 14:42:59 2019
Total time elapsed: 2.0m:41.94s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 51,
    "n_p_sig": 5401,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.0587,
    "ldsc_observed_scale_h2_se": 0.0049,
    "ldsc_intercept_beta": 1.0648,
    "ldsc_intercept_se": 0.0108,
    "ldsc_lambda_gc": 1.4238,
    "ldsc_mean_chisq": 1.5997,
    "ldsc_ratio": 0.1081
}
 

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 3 58 0 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.052000e-04 9.077200e-03 -0.1684140 -3.044900e-03 -5.830000e-05 2.871800e-03 3.673680e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.199600e-03 5.869200e-03 0.0017349 2.123500e-03 3.560800e-03 8.216500e-03 9.109080e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.581774e-01 3.002704e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.581787e-01 3.002458e-01 0.0000000 1.870311e-01 4.433748e-01 7.184307e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035075e-01 2.568628e-01 0.0009870 1.316900e-02 7.791300e-02 3.164560e-01 9.990110e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 0.0006112 0.0031906 0.8499999 0.8480732 0.623814 0.7821490 NA
1 54676 rs2462492 C T 0.0022994 0.0031612 0.4700002 0.4669814 0.400374 NA NA
1 86028 rs114608975 T C -0.0063525 0.0050546 0.2099999 0.2088353 0.103542 0.0277556 NA
1 91536 rs6702460 G T 0.0044470 0.0031123 0.1499999 0.1530472 0.456853 0.4207270 NA
1 234313 rs8179466 C T -0.0006677 0.0061358 0.9100000 0.9133424 0.074522 NA NA
1 534192 rs6680723 C T -0.0015286 0.0035562 0.6700003 0.6673170 0.240930 NA NA
1 546697 rs12025928 A G 0.0005171 0.0044347 0.9100000 0.9071827 0.913448 NA NA
1 693731 rs12238997 A G 0.0019719 0.0029790 0.5099998 0.5080024 0.116339 0.1417730 NA
1 705882 rs72631875 G A 0.0079174 0.0043659 0.0700003 0.0697587 0.067302 0.0315495 NA
1 706368 rs55727773 A G -0.0002085 0.0022071 0.9199999 0.9247203 0.515660 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0064859 0.0046351 0.1600000 0.1617213 0.041949 0.0473243 NA
22 51219766 rs182321900 C T -0.0125379 0.0216024 0.5600000 0.5616491 0.001935 NA NA
22 51220146 rs868950473 C T -0.0087562 0.0214000 0.6800001 0.6824179 0.001984 NA NA
22 51221190 rs369304721 G A 0.0094766 0.0046279 0.0409996 0.0405897 0.049709 NA NA
22 51221731 rs115055839 T C 0.0066604 0.0034612 0.0539995 0.0543151 0.073219 0.0625000 NA
22 51222100 rs114553188 G T -0.0058662 0.0040741 0.1499999 0.1498998 0.054477 0.0880591 NA
22 51223637 rs375798137 G A -0.0060406 0.0040938 0.1400000 0.1400691 0.054105 0.0788738 NA
22 51229805 rs9616985 T C 0.0070322 0.0034736 0.0430002 0.0429230 0.073057 0.0730831 NA
22 51232488 rs376461333 A G -0.0124052 0.0081780 0.1299999 0.1292931 0.020060 NA NA
22 51237063 rs3896457 T C -0.0012860 0.0021243 0.5400003 0.5449237 0.297922 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623814 ES:SE:LP:AF:ID  0.000611247:0.0031906:0.0705811:0.623814:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400374 ES:SE:LP:AF:ID  0.00229944:0.00316118:0.327902:0.400374:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103542 ES:SE:LP:AF:ID  -0.00635253:0.00505463:0.677781:0.103542:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456853 ES:SE:LP:AF:ID  0.00444704:0.00311232:0.823909:0.456853:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074522 ES:SE:LP:AF:ID  -0.00066772:0.0061358:0.0409586:0.074522:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24093  ES:SE:LP:AF:ID  -0.00152856:0.00355617:0.173925:0.24093:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913448 ES:SE:LP:AF:ID  0.000517051:0.00443467:0.0409586:0.913448:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116339 ES:SE:LP:AF:ID  0.00197194:0.00297898:0.29243:0.116339:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067302 ES:SE:LP:AF:ID  0.00791741:0.00436588:1.1549:0.067302:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51566  ES:SE:LP:AF:ID  -0.000208544:0.00220706:0.0362122:0.51566:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032991 ES:SE:LP:AF:ID  0.0013331:0.0055653:0.091515:0.032991:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036606 ES:SE:LP:AF:ID  0.00156722:0.00505504:0.119186:0.036606:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036722 ES:SE:LP:AF:ID  0.00227526:0.00503591:0.187087:0.036722:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036425 ES:SE:LP:AF:ID  0.00205677:0.00507187:0.161151:0.036425:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016407 ES:SE:LP:AF:ID  -0.0108669:0.00780821:0.79588:0.016407:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036961 ES:SE:LP:AF:ID  0.00222681:0.00501597:0.180456:0.036961:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037058 ES:SE:LP:AF:ID  0.00194306:0.00499875:0.154902:0.037058:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101236 ES:SE:LP:AF:ID  -0.00188548:0.00364061:0.221849:0.101236:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959109 ES:SE:LP:AF:ID  -0.00311858:0.0048209:0.283997:0.959109:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031456 ES:SE:LP:AF:ID  0.0103085:0.00874874:0.619789:0.031456:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053262 ES:SE:LP:AF:ID  0.00184582:0.00695987:0.102373:0.053262:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036576 ES:SE:LP:AF:ID  0.00228491:0.00503106:0.187087:0.036576:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036895 ES:SE:LP:AF:ID  0.00208918:0.00498511:0.167491:0.036895:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843226 ES:SE:LP:AF:ID  -0.00409693:0.00258212:0.958607:0.843226:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055906 ES:SE:LP:AF:ID  0.00760719:0.00418104:1.16115:0.055906:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122315 ES:SE:LP:AF:ID  0.00277463:0.00282604:0.481486:0.122315:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.0257   ES:SE:LP:AF:ID  -0.00283828:0.00695364:0.167491:0.0257:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121557 ES:SE:LP:AF:ID  0.00276921:0.00282723:0.481486:0.121557:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132317 ES:SE:LP:AF:ID  0.00518317:0.00278693:1.20066:0.132317:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  0.00373649:0.0101327:0.148742:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005702 ES:SE:LP:AF:ID  -0.0324768:0.0130757:1.88606:0.005702:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002273 ES:SE:LP:AF:ID  0.0300739:0.0219625:0.769551:0.002273:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001031 ES:SE:LP:AF:ID  0.00709404:0.0359778:0.0757207:0.001031:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036807 ES:SE:LP:AF:ID  0.00142362:0.00493492:0.113509:0.036807:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838965 ES:SE:LP:AF:ID  -0.00481921:0.00250067:1.26761:0.838965:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838593 ES:SE:LP:AF:ID  -0.00485873:0.00249795:1.284:0.838593:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869771 ES:SE:LP:AF:ID  -0.00384147:0.0026802:0.823909:0.869771:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129878 ES:SE:LP:AF:ID  0.00344707:0.0026856:0.69897:0.129878:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  0.00128652:0.00485126:0.102373:0.037317:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03756  ES:SE:LP:AF:ID  0.000956693:0.00482067:0.0757207:0.03756:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  -0.00397961:0.00267494:0.853872:0.869114:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869209 ES:SE:LP:AF:ID  -0.00392904:0.00267597:0.853872:0.869209:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037518 ES:SE:LP:AF:ID  0.00113798:0.00484149:0.091515:0.037518:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  -0.0039657:0.00267489:0.853872:0.869116:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005129 ES:SE:LP:AF:ID  0.0171121:0.0137237:0.677781:0.005129:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005094 ES:SE:LP:AF:ID  0.0173665:0.0137597:0.677781:0.005094:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838049 ES:SE:LP:AF:ID  -0.00475194:0.00249105:1.25181:0.838049:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037531 ES:SE:LP:AF:ID  0.00106149:0.00484829:0.0809219:0.037531:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838681 ES:SE:LP:AF:ID  -0.00487407:0.00249806:1.29243:0.838681:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013792 ES:SE:LP:AF:ID  -0.000576574:0.0087132:0.0222764:0.013792:rs181660517