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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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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_2634.vcf.gz --id UKB-b:2634 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2634.txt.gz --cohort_controls 182778 --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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}

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-2634/UKB-b-2634_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2634/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:51 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2634/UKB-b-2634_data.vcf.gz ...
Read summary statistics for 9431066 SNPs.
Dropped 11167 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, 1288201 SNPs remain.
After merging with regression SNP LD, 1288201 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0326 (0.003)
Lambda GC: 1.1248
Mean Chi^2: 1.1323
Intercept: 1.0155 (0.0064)
Ratio: 0.1168 (0.0484)
Analysis finished at Thu Oct 17 14:44:35 2019
Total time elapsed: 1.0m:44.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9488,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 2,
    "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": 126642,
    "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": 1288201,
    "ldsc_nsnp_merge_regression_ld": 1288201,
    "ldsc_observed_scale_h2_beta": 0.0326,
    "ldsc_observed_scale_h2_se": 0.003,
    "ldsc_intercept_beta": 1.0155,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.1248,
    "ldsc_mean_chisq": 1.1323,
    "ldsc_ratio": 0.1172
}

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 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 9419957 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 9431066 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 8.630832e+00 5.752271e+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 7.882861e+07 5.630437e+07 828.0000000 3.252907e+07 6.941728e+07 1.145577e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.890000e-05 2.148380e-02 -0.2970890 -7.732000e-03 -6.630000e-05 7.636000e-03 2.822340e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.638240e-02 1.346290e-02 0.0052852 6.383800e-03 1.021950e-02 2.234840e-02 1.809290e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.869227e-01 2.924474e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.869240e-01 2.924222e-01 0.0000000 2.305811e-01 4.821185e-01 7.409818e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.111329e-01 2.574678e-01 0.0019150 1.633600e-02 8.871400e-02 3.308600e-01 9.980850e-01 ▇▂▁▁▁
numeric AF_reference 126642 0.9865718 NA NA NA NA NA NA NA 2.125425e-01 2.492343e-01 0.0000000 1.377800e-02 1.078270e-01 3.316690e-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 -0.0066278 0.0097412 0.5000000 0.4962585 0.624469 0.7821490 NA
1 54676 rs2462492 C T 0.0029218 0.0096656 0.7600007 0.7624344 0.399700 NA NA
1 86028 rs114608975 T C 0.0169528 0.0154788 0.2700001 0.2734172 0.103397 0.0277556 NA
1 91536 rs6702460 G T 0.0066885 0.0095030 0.4799997 0.4815357 0.456981 0.4207270 NA
1 234313 rs8179466 C T 0.0293125 0.0188104 0.1199999 0.1191590 0.074554 NA NA
1 534192 rs6680723 C T -0.0016508 0.0108745 0.8800001 0.8793381 0.240871 NA NA
1 546697 rs12025928 A G -0.0044679 0.0134643 0.7400005 0.7400176 0.913167 NA NA
1 693731 rs12238997 A G 0.0046536 0.0090646 0.6100002 0.6076855 0.116866 0.1417730 NA
1 705882 rs72631875 G A 0.0108908 0.0132924 0.4100001 0.4126008 0.067456 0.0315495 NA
1 706368 rs55727773 A G -0.0014945 0.0067255 0.8200001 0.8241473 0.516489 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0079469 0.0081269 0.3300000 0.3281461 0.137110 0.2052720 NA
22 51219387 rs9616832 T C 0.0137947 0.0106019 0.1900002 0.1932059 0.072786 0.0654952 NA
22 51219704 rs147475742 G A 0.0255034 0.0142056 0.0729995 0.0726049 0.041395 0.0473243 NA
22 51221190 rs369304721 G A 0.0196191 0.0141939 0.1700000 0.1669040 0.049037 NA NA
22 51221731 rs115055839 T C 0.0133612 0.0106116 0.2099999 0.2079896 0.072250 0.0625000 NA
22 51222100 rs114553188 G T -0.0046054 0.0123382 0.7099994 0.7089505 0.054881 0.0880591 NA
22 51223637 rs375798137 G A -0.0060627 0.0123948 0.6200004 0.6247456 0.054526 0.0788738 NA
22 51229805 rs9616985 T C 0.0126517 0.0106491 0.2300001 0.2348124 0.072092 0.0730831 NA
22 51232488 rs376461333 A G -0.0248717 0.0248336 0.3200000 0.3165686 0.020161 NA NA
22 51237063 rs3896457 T C -0.0002337 0.0064621 0.9699999 0.9711523 0.298004 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624469 ES:SE:LP:AF:ID  -0.00662778:0.00974117:0.30103:0.624469:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.3997   ES:SE:LP:AF:ID  0.00292178:0.00966563:0.119186:0.3997:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103397 ES:SE:LP:AF:ID  0.0169528:0.0154788:0.568636:0.103397:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456981 ES:SE:LP:AF:ID  0.00668852:0.00950297:0.318759:0.456981:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074554 ES:SE:LP:AF:ID  0.0293125:0.0188104:0.920819:0.074554:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240871 ES:SE:LP:AF:ID  -0.00165084:0.0108745:0.0555173:0.240871:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913167 ES:SE:LP:AF:ID  -0.00446786:0.0134643:0.130768:0.913167:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116866 ES:SE:LP:AF:ID  0.00465359:0.00906461:0.21467:0.116866:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067456 ES:SE:LP:AF:ID  0.0108908:0.0132924:0.387216:0.067456:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516489 ES:SE:LP:AF:ID  -0.0014945:0.0067255:0.0861861:0.516489:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032601 ES:SE:LP:AF:ID  -0.0119197:0.0170652:0.318759:0.032601:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036167 ES:SE:LP:AF:ID  -0.012427:0.0154982:0.376751:0.036167:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03631  ES:SE:LP:AF:ID  -0.0112822:0.0154317:0.337242:0.03631:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036037 ES:SE:LP:AF:ID  -0.0121348:0.0155366:0.366532:0.036037:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016311 ES:SE:LP:AF:ID  -0.000235856:0.0239312:0.00436481:0.016311:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03657  ES:SE:LP:AF:ID  -0.0138641:0.0153641:0.431798:0.03657:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036689 ES:SE:LP:AF:ID  -0.012779:0.0153045:0.39794:0.036689:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101511 ES:SE:LP:AF:ID  0.0242771:0.0110726:1.55284:0.101511:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959679 ES:SE:LP:AF:ID  0.0103707:0.0147945:0.318759:0.959679:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031658 ES:SE:LP:AF:ID  -0.0248362:0.0265768:0.455932:0.031658:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053386 ES:SE:LP:AF:ID  -0.0227051:0.0211506:0.552842:0.053386:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036162 ES:SE:LP:AF:ID  -0.0138115:0.0154135:0.431798:0.036162:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036471 ES:SE:LP:AF:ID  -0.0144447:0.015274:0.468521:0.036471:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843228 ES:SE:LP:AF:ID  0.00150573:0.00787476:0.0705811:0.843228:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056488 ES:SE:LP:AF:ID  -0.0129695:0.0126864:0.508638:0.056488:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122859 ES:SE:LP:AF:ID  0.0023239:0.00859995:0.102373:0.122859:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025315 ES:SE:LP:AF:ID  0.0346083:0.0213836:0.958607:0.025315:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122081 ES:SE:LP:AF:ID  0.0027679:0.00860601:0.124939:0.122081:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132798 ES:SE:LP:AF:ID  -0.00151494:0.00847714:0.0655015:0.132798:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.010983 ES:SE:LP:AF:ID  0.00388891:0.0311403:0.0457575:0.010983:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005796 ES:SE:LP:AF:ID  0.0361934:0.0396717:0.443698:0.005796:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002163 ES:SE:LP:AF:ID  0.142021:0.0688276:1.40894:0.002163:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036359 ES:SE:LP:AF:ID  -0.0167023:0.015127:0.568636:0.036359:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838881 ES:SE:LP:AF:ID  0.000131419:0.00762056:0.00436481:0.838881:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838569 ES:SE:LP:AF:ID  0.000359794:0.00761408:0.0177288:0.838569:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86932  ES:SE:LP:AF:ID  -0.00542132:0.00815597:0.29243:0.86932:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130301 ES:SE:LP:AF:ID  0.00418548:0.00817388:0.21467:0.130301:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036917 ES:SE:LP:AF:ID  -0.0169554:0.0148558:0.60206:0.036917:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03715  ES:SE:LP:AF:ID  -0.0166666:0.0147653:0.585027:0.03715:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868726 ES:SE:LP:AF:ID  -0.00541605:0.0081423:0.29243:0.868726:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868833 ES:SE:LP:AF:ID  -0.00567587:0.00814545:0.309804:0.868833:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037091 ES:SE:LP:AF:ID  -0.0171087:0.0148294:0.60206:0.037091:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868734 ES:SE:LP:AF:ID  -0.00524238:0.00814242:0.283997:0.868734:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005236 ES:SE:LP:AF:ID  0.0124653:0.0413636:0.119186:0.005236:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005199 ES:SE:LP:AF:ID  0.00897747:0.0414853:0.0809219:0.005199:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838022 ES:SE:LP:AF:ID  0.00062853:0.00759098:0.0315171:0.838022:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037119 ES:SE:LP:AF:ID  -0.017568:0.0148455:0.619789:0.037119:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838632 ES:SE:LP:AF:ID  0.000421827:0.00761114:0.0177288:0.838632:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013897 ES:SE:LP:AF:ID  -0.054586:0.0264226:1.40894:0.013897:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005465 ES:SE:LP:AF:ID  0.0494162:0.0413282:0.638272:0.005465:rs184270342