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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_20150.vcf.gz --id UKB-b:11141 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20150.txt.gz --cohort_controls 345665 --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-11141/UKB-b-11141_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11141/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-11141/UKB-b-11141_data.vcf.gz ...
Read summary statistics for 9812233 SNPs.
Dropped 14512 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, 1289096 SNPs remain.
After merging with regression SNP LD, 1289096 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1493 (0.0057)
Lambda GC: 1.7359
Mean Chi^2: 2.1519
Intercept: 1.1107 (0.0121)
Ratio: 0.0961 (0.0105)
Analysis finished at Thu Oct 17 14:42:05 2019
Total time elapsed: 1.0m:46.48s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9497,
    "inflation_factor": 1.4921,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 233,
    "n_p_sig": 29362,
    "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": 184138,
    "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": 1289096,
    "ldsc_nsnp_merge_regression_ld": 1289096,
    "ldsc_observed_scale_h2_beta": 0.1493,
    "ldsc_observed_scale_h2_se": 0.0057,
    "ldsc_intercept_beta": 1.1107,
    "ldsc_intercept_se": 0.0121,
    "ldsc_lambda_gc": 1.7359,
    "ldsc_mean_chisq": 2.1519,
    "ldsc_ratio": 0.0961
}

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 9797788 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 9812233 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 8.622788e+00 5.748247e+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 7.885532e+07 5.628170e+07 828.0000000 3.258516e+07 6.948605e+07 1.145847e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.580000e-05 9.679800e-03 -0.1471970 -3.430000e-03 -2.310000e-05 3.393500e-03 1.882550e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.490200e-03 6.101900e-03 0.0018357 2.245000e-03 3.748700e-03 8.611600e-03 9.691200e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.359261e-01 3.054910e-01 0.0000000 1.499999e-01 4.100001e-01 6.999999e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.359268e-01 3.054692e-01 0.0000000 1.548115e-01 4.121359e-01 7.001585e-01 9.999999e-01 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.039861e-01 2.567240e-01 0.0010130 1.340400e-02 7.876300e-02 3.174880e-01 9.989870e-01 ▇▂▁▁▁
numeric AF_reference 184138 0.9812338 NA NA NA NA NA NA NA 2.071270e-01 2.483005e-01 0.0000000 1.198080e-02 1.004390e-01 3.212860e-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 0.0000259 0.0033737 0.9900000 0.9938822 0.624025 0.7821490 NA
1 54676 rs2462492 C T -0.0008560 0.0033416 0.8000000 0.7978210 0.400692 NA NA
1 86028 rs114608975 T C -0.0052912 0.0053426 0.3200000 0.3219897 0.103524 0.0277556 NA
1 91536 rs6702460 G T -0.0024712 0.0032905 0.4500005 0.4526441 0.457113 0.4207270 NA
1 234313 rs8179466 C T -0.0001233 0.0065053 0.9800000 0.9848739 0.074356 NA NA
1 534192 rs6680723 C T -0.0080094 0.0037569 0.0329997 0.0330162 0.241112 NA NA
1 546697 rs12025928 A G 0.0034863 0.0046914 0.4600002 0.4574043 0.913454 NA NA
1 693731 rs12238997 A G -0.0083387 0.0031492 0.0080999 0.0081006 0.116533 0.1417730 NA
1 705882 rs72631875 G A -0.0000170 0.0046165 1.0000000 0.9970699 0.067299 0.0315495 NA
1 706368 rs55727773 A G 0.0036942 0.0023335 0.1100001 0.1133950 0.516019 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0022318 0.0049261 0.6499995 0.6505083 0.041720 0.0473243 NA
22 51219766 rs182321900 C T -0.0264286 0.0235022 0.2599998 0.2607942 0.001842 NA NA
22 51220146 rs868950473 C T -0.0245912 0.0232763 0.2900000 0.2907440 0.001892 NA NA
22 51221190 rs369304721 G A -0.0038033 0.0049129 0.4400003 0.4388399 0.049485 NA NA
22 51221731 rs115055839 T C -0.0008970 0.0036752 0.8100000 0.8071828 0.072924 0.0625000 NA
22 51222100 rs114553188 G T 0.0038546 0.0043124 0.3700002 0.3714071 0.054681 0.0880591 NA
22 51223637 rs375798137 G A 0.0037826 0.0043330 0.3800004 0.3826861 0.054322 0.0788738 NA
22 51229805 rs9616985 T C -0.0012102 0.0036888 0.7400005 0.7428508 0.072740 0.0730831 NA
22 51232488 rs376461333 A G 0.0073746 0.0086363 0.3900004 0.3931573 0.020176 NA NA
22 51237063 rs3896457 T C 0.0018292 0.0022529 0.4199997 0.4168269 0.297991 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624025 ES:SE:LP:AF:ID  2.58683e-05:0.0033737:0.00436481:0.624025:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400692 ES:SE:LP:AF:ID  -0.000856019:0.00334163:0.09691:0.400692:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103524 ES:SE:LP:AF:ID  -0.00529117:0.00534258:0.49485:0.103524:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457113 ES:SE:LP:AF:ID  -0.00247119:0.00329047:0.346787:0.457113:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074356 ES:SE:LP:AF:ID  -0.000123334:0.00650533:0.00877392:0.074356:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241112 ES:SE:LP:AF:ID  -0.00800937:0.00375694:1.48149:0.241112:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913454 ES:SE:LP:AF:ID  0.00348628:0.00469136:0.337242:0.913454:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116533 ES:SE:LP:AF:ID  -0.00833866:0.00314922:2.09152:0.116533:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067299 ES:SE:LP:AF:ID  -1.69535e-05:0.00461647:-0:0.067299:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516019 ES:SE:LP:AF:ID  0.00369417:0.00233348:0.958607:0.516019:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032932 ES:SE:LP:AF:ID  0.00541858:0.00589229:0.443698:0.032932:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036539 ES:SE:LP:AF:ID  0.00443804:0.00535096:0.387216:0.036539:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036647 ES:SE:LP:AF:ID  0.00462549:0.00533145:0.408935:0.036647:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036358 ES:SE:LP:AF:ID  0.00473047:0.00536868:0.420216:0.036358:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016417 ES:SE:LP:AF:ID  0.00168194:0.00825526:0.0757207:0.016417:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036878 ES:SE:LP:AF:ID  0.00443416:0.00531069:0.39794:0.036878:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036975 ES:SE:LP:AF:ID  0.00463738:0.00529239:0.420216:0.036975:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101341 ES:SE:LP:AF:ID  0.00238328:0.00384539:0.267606:0.101341:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959496 ES:SE:LP:AF:ID  -0.00388577:0.00512324:0.346787:0.959496:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031474 ES:SE:LP:AF:ID  0.000332105:0.00924808:0.0132283:0.031474:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053151 ES:SE:LP:AF:ID  -0.00533518:0.00736574:0.327902:0.053151:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036509 ES:SE:LP:AF:ID  0.00476147:0.00532554:0.431798:0.036509:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036799 ES:SE:LP:AF:ID  0.00502213:0.00527812:0.468521:0.036799:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843356 ES:SE:LP:AF:ID  0.00543532:0.00273314:1.3279:0.843356:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056236 ES:SE:LP:AF:ID  -0.00747582:0.00441192:1.04576:0.056236:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12255  ES:SE:LP:AF:ID  -0.00853512:0.00298721:2.36653:0.12255:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025757 ES:SE:LP:AF:ID  0.00679269:0.00734385:0.455932:0.025757:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121808 ES:SE:LP:AF:ID  -0.00863002:0.00298825:2.40894:0.121808:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132564 ES:SE:LP:AF:ID  -0.00677771:0.00294546:1.67778:0.132564:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011115 ES:SE:LP:AF:ID  -0.0105908:0.0107266:0.49485:0.011115:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  -0.0165727:0.0138493:0.638272:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002088 ES:SE:LP:AF:ID  -0.042454:0.0243893:1.08619:0.002088:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036726 ES:SE:LP:AF:ID  0.00466407:0.00522465:0.431798:0.036726:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838977 ES:SE:LP:AF:ID  0.0052599:0.00264585:1.3279:0.838977:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838692 ES:SE:LP:AF:ID  0.00516697:0.00264371:1.29243:0.838692:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869721 ES:SE:LP:AF:ID  0.00823581:0.00283598:2.4318:0.869721:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129867 ES:SE:LP:AF:ID  -0.00755774:0.00284205:2.10791:0.129867:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037242 ES:SE:LP:AF:ID  0.00304798:0.00513577:0.259637:0.037242:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037481 ES:SE:LP:AF:ID  0.0028766:0.00510352:0.244125:0.037481:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  0.00793523:0.00283118:2.29243:0.869154:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869251 ES:SE:LP:AF:ID  0.00792481:0.00283219:2.29243:0.869251:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037446 ES:SE:LP:AF:ID  0.00269654:0.00512538:0.221849:0.037446:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869155 ES:SE:LP:AF:ID  0.0079848:0.0028311:2.31876:0.869155:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005109 ES:SE:LP:AF:ID  -0.00226527:0.0145497:0.0555173:0.005109:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005075 ES:SE:LP:AF:ID  -0.00204381:0.0145874:0.05061:0.005075:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838133 ES:SE:LP:AF:ID  0.00523794:0.00263627:1.3279:0.838133:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037464 ES:SE:LP:AF:ID  0.00264366:0.00513213:0.21467:0.037464:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838766 ES:SE:LP:AF:ID  0.00535172:0.00264371:1.36653:0.838766:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  0.0129779:0.00921807:0.79588:0.013775:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005547 ES:SE:LP:AF:ID  0.0110325:0.0142178:0.356547:0.005547:rs184270342