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_914.vcf.gz --id UKB-b:13932 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_914.txt.gz --cohort_controls 251501 --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-13932/UKB-b-13932_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13932/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13932/UKB-b-13932_data.vcf.gz ...
Read summary statistics for 9646034 SNPs.
Dropped 12837 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, 1288680 SNPs remain.
After merging with regression SNP LD, 1288680 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0324 (0.0024)
Lambda GC: 1.1372
Mean Chi^2: 1.1584
Intercept: 1.0013 (0.0067)
Ratio: 0.0085 (0.0421)
Analysis finished at Thu Oct 17 14:44:49 2019
Total time elapsed: 1.0m:44.9s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9494,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 157,
    "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": 153474,
    "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": 1288680,
    "ldsc_nsnp_merge_regression_ld": 1288680,
    "ldsc_observed_scale_h2_beta": 0.0324,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0013,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.1372,
    "ldsc_mean_chisq": 1.1584,
    "ldsc_ratio": 0.0082
}

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 9633259 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 9646034 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 8.626461e+00 5.750640e+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 7.883949e+07 5.629635e+07 828.0000000 3.255859e+07 6.943847e+07 1.145703e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.062000e-04 1.219420e-02 -0.1917160 -3.992500e-03 3.430000e-05 4.144900e-03 1.896560e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 8.981800e-03 7.899600e-03 0.0027062 3.290500e-03 5.392700e-03 1.212050e-02 1.410960e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.848081e-01 2.931934e-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 4.848076e-01 2.931677e-01 0.0000000 2.271157e-01 4.801499e-01 7.388593e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.070692e-01 2.570523e-01 0.0013920 1.464800e-02 8.307800e-02 3.233600e-01 9.986080e-01 ▇▂▁▁▁
numeric AF_reference 153474 0.9840894 NA NA NA NA NA NA NA 2.093853e-01 2.486831e-01 0.0000000 1.257990e-02 1.036340e-01 3.254790e-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 0.0108523 0.0049791 0.0290001 0.0292900 0.623337 0.7821490 NA
1 54676 rs2462492 C T -0.0076809 0.0049285 0.1199999 0.1191203 0.400559 NA NA
1 86028 rs114608975 T C -0.0033285 0.0078750 0.6700003 0.6725353 0.103651 0.0277556 NA
1 91536 rs6702460 G T 0.0053148 0.0048582 0.2700001 0.2739688 0.457093 0.4207270 NA
1 234313 rs8179466 C T 0.0084432 0.0095944 0.3800004 0.3788499 0.074291 NA NA
1 534192 rs6680723 C T -0.0002611 0.0055528 0.9599999 0.9624952 0.241002 NA NA
1 546697 rs12025928 A G 0.0076818 0.0069187 0.2700001 0.2668708 0.913492 NA NA
1 693731 rs12238997 A G 0.0043997 0.0046515 0.3400001 0.3442163 0.116164 0.1417730 NA
1 705882 rs72631875 G A -0.0121801 0.0068030 0.0729995 0.0733873 0.067465 0.0315495 NA
1 706368 rs55727773 A G -0.0005958 0.0034416 0.8600001 0.8625674 0.515415 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0013833 0.0072734 0.8499999 0.8491654 0.041478 0.0473243 NA
22 51219766 rs182321900 C T 0.0204262 0.0341728 0.5500004 0.5500183 0.001896 NA NA
22 51220146 rs868950473 C T 0.0167718 0.0339380 0.6200004 0.6211724 0.001933 NA NA
22 51221190 rs369304721 G A 0.0032626 0.0072592 0.6499995 0.6531119 0.049157 NA NA
22 51221731 rs115055839 T C 0.0031224 0.0054359 0.5700002 0.5656935 0.072317 0.0625000 NA
22 51222100 rs114553188 G T 0.0039687 0.0063584 0.5300002 0.5325187 0.054219 0.0880591 NA
22 51223637 rs375798137 G A 0.0032689 0.0063897 0.6100002 0.6089376 0.053847 0.0788738 NA
22 51229805 rs9616985 T C 0.0034166 0.0054546 0.5300002 0.5310711 0.072174 0.0730831 NA
22 51232488 rs376461333 A G 0.0047608 0.0127912 0.7099994 0.7097460 0.019941 NA NA
22 51237063 rs3896457 T C -0.0019903 0.0033142 0.5500004 0.5481524 0.298031 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623337 ES:SE:LP:AF:ID  0.0108523:0.00497912:1.5376:0.623337:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400559 ES:SE:LP:AF:ID  -0.00768092:0.00492848:0.920819:0.400559:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103651 ES:SE:LP:AF:ID  -0.00332853:0.00787499:0.173925:0.103651:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457093 ES:SE:LP:AF:ID  0.00531475:0.00485823:0.568636:0.457093:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074291 ES:SE:LP:AF:ID  0.00844323:0.00959439:0.420216:0.074291:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241002 ES:SE:LP:AF:ID  -0.000261106:0.00555278:0.0177288:0.241002:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913492 ES:SE:LP:AF:ID  0.00768185:0.00691873:0.568636:0.913492:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116164 ES:SE:LP:AF:ID  0.00439972:0.00465152:0.468521:0.116164:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067465 ES:SE:LP:AF:ID  -0.0121801:0.00680295:1.13668:0.067465:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515415 ES:SE:LP:AF:ID  -0.000595756:0.00344155:0.0655015:0.515415:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03281  ES:SE:LP:AF:ID  0.0174582:0.00870932:1.34679:0.03281:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036418 ES:SE:LP:AF:ID  0.0170012:0.00790906:1.49485:0.036418:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036552 ES:SE:LP:AF:ID  0.0179908:0.00787733:1.65758:0.036552:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03625  ES:SE:LP:AF:ID  0.0181236:0.00793335:1.65758:0.03625:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016242 ES:SE:LP:AF:ID  -0.00113035:0.0122606:0.0315171:0.016242:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036804 ES:SE:LP:AF:ID  0.0174856:0.00784465:1.58503:0.036804:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036912 ES:SE:LP:AF:ID  0.0175031:0.00781662:1.60206:0.036912:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101473 ES:SE:LP:AF:ID  -0.0128049:0.00567461:1.61979:0.101473:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959238 ES:SE:LP:AF:ID  -0.0197198:0.00753767:2.05061:0.959238:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031438 ES:SE:LP:AF:ID  0.00345164:0.0136715:0.09691:0.031438:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053102 ES:SE:LP:AF:ID  0.0109322:0.0108849:0.49485:0.053102:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036437 ES:SE:LP:AF:ID  0.0185379:0.00786521:1.74473:0.036437:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036731 ES:SE:LP:AF:ID  0.0175354:0.00779717:1.60206:0.036731:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843441 ES:SE:LP:AF:ID  -0.0075091:0.00403112:1.20761:0.843441:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055873 ES:SE:LP:AF:ID  -0.000829866:0.00652042:0.0457575:0.055873:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122127 ES:SE:LP:AF:ID  0.00413224:0.00441283:0.455932:0.122127:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025493 ES:SE:LP:AF:ID  0.00327266:0.0109048:0.119186:0.025493:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121383 ES:SE:LP:AF:ID  0.00399773:0.00441432:0.431798:0.121383:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132215 ES:SE:LP:AF:ID  0.00802048:0.00435057:1.18709:0.132215:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011112 ES:SE:LP:AF:ID  -0.0163576:0.0158091:0.522879:0.011112:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005681 ES:SE:LP:AF:ID  0.0142548:0.0204233:0.309804:0.005681:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002287 ES:SE:LP:AF:ID  0.0130879:0.0340251:0.154902:0.002287:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036615 ES:SE:LP:AF:ID  0.0173519:0.00772147:1.60206:0.036615:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839211 ES:SE:LP:AF:ID  -0.00741094:0.00390482:1.23657:0.839211:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83885  ES:SE:LP:AF:ID  -0.00750551:0.00390101:1.26761:0.83885:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869921 ES:SE:LP:AF:ID  -0.0041598:0.00418444:0.49485:0.869921:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129705 ES:SE:LP:AF:ID  0.00401327:0.00419362:0.468521:0.129705:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03715  ES:SE:LP:AF:ID  0.0179521:0.0075864:1.74473:0.03715:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03739  ES:SE:LP:AF:ID  0.0173299:0.00753842:1.65758:0.03739:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869264 ES:SE:LP:AF:ID  -0.00428732:0.00417651:0.522879:0.869264:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869367 ES:SE:LP:AF:ID  -0.00426309:0.00417826:0.508638:0.869367:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037357 ES:SE:LP:AF:ID  0.0181712:0.0075714:1.79588:0.037357:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869261 ES:SE:LP:AF:ID  -0.00436098:0.00417634:0.522879:0.869261:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005142 ES:SE:LP:AF:ID  0.00644661:0.0214164:0.119186:0.005142:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005112 ES:SE:LP:AF:ID  0.00641345:0.0214682:0.113509:0.005112:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838261 ES:SE:LP:AF:ID  -0.0076685:0.00388918:1.3098:0.838261:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037382 ES:SE:LP:AF:ID  0.018555:0.00758035:1.85387:0.037382:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838878 ES:SE:LP:AF:ID  -0.00754044:0.00389982:1.27572:0.838878:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013548 ES:SE:LP:AF:ID  -0.00551216:0.0137315:0.161151:0.013548:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005489 ES:SE:LP:AF:ID  0.0302841:0.0211367:0.823909:0.005489:rs184270342