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_4241.vcf.gz --id UKB-b:18697 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_4241.txt.gz --cohort_controls 148695 --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-18697/UKB-b-18697_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18697/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18697/UKB-b-18697_data.vcf.gz ...
Read summary statistics for 9312917 SNPs.
Dropped 10348 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, 1287972 SNPs remain.
After merging with regression SNP LD, 1287972 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0224 (0.0036)
Lambda GC: 1.1142
Mean Chi^2: 1.1213
Intercept: 1.0559 (0.0065)
Ratio: 0.4614 (0.0534)
Analysis finished at Thu Oct 17 14:41:58 2019
Total time elapsed: 1.0m:39.05s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0002,
    "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": 112623,
    "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": 1287972,
    "ldsc_nsnp_merge_regression_ld": 1287972,
    "ldsc_observed_scale_h2_beta": 0.0224,
    "ldsc_observed_scale_h2_se": 0.0036,
    "ldsc_intercept_beta": 1.0559,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.1142,
    "ldsc_mean_chisq": 1.1213,
    "ldsc_ratio": 0.4608
}

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 9302621 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 9312917 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 8.634870e+00 5.754008e+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 7.881151e+07 5.630737e+07 828.0000000 3.250335e+07 6.939476e+07 1.145407e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.466000e-04 1.364950e-02 -0.1732320 -4.878300e-03 7.880000e-05 5.118700e-03 1.742620e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.040230e-02 8.225700e-03 0.0034833 4.191400e-03 6.625400e-03 1.425820e-02 1.203280e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.858475e-01 2.929565e-01 0.0000004 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 4.858476e-01 2.929312e-01 0.0000004 2.281926e-01 4.806850e-01 7.401101e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.136450e-01 2.577975e-01 0.0023540 1.743600e-02 9.233600e-02 3.354420e-01 9.976460e-01 ▇▂▁▁▁
numeric AF_reference 112623 0.9879068 NA NA NA NA NA NA NA 2.146733e-01 2.495867e-01 0.0000000 1.477640e-02 1.108230e-01 3.354630e-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 -0.0064868 0.0064164 0.3100002 0.3120321 0.623714 0.7821490 NA
1 54676 rs2462492 C T 0.0009189 0.0063771 0.8900000 0.8854211 0.399195 NA NA
1 86028 rs114608975 T C 0.0061297 0.0101628 0.5500004 0.5464117 0.103773 0.0277556 NA
1 91536 rs6702460 G T 0.0006994 0.0062822 0.9100000 0.9113563 0.456293 0.4207270 NA
1 234313 rs8179466 C T -0.0020265 0.0123920 0.8700001 0.8700969 0.074543 NA NA
1 534192 rs6680723 C T -0.0042957 0.0071812 0.5500004 0.5497150 0.241197 NA NA
1 546697 rs12025928 A G -0.0057259 0.0089075 0.5199996 0.5203426 0.913022 NA NA
1 693731 rs12238997 A G 0.0002847 0.0059876 0.9599999 0.9620778 0.116941 0.1417730 NA
1 705882 rs72631875 G A 0.0067626 0.0087578 0.4400003 0.4400066 0.067577 0.0315495 NA
1 706368 rs55727773 A G -0.0038184 0.0044328 0.3900004 0.3890213 0.514813 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0022162 0.0053715 0.6800001 0.6799116 0.137060 0.2052720 NA
22 51219387 rs9616832 T C 0.0052567 0.0069926 0.4500005 0.4522031 0.072582 0.0654952 NA
22 51219704 rs147475742 G A 0.0000654 0.0093335 0.9900000 0.9944070 0.041569 0.0473243 NA
22 51221190 rs369304721 G A 0.0026864 0.0093594 0.7700005 0.7740882 0.049004 NA NA
22 51221731 rs115055839 T C 0.0046479 0.0069977 0.5099998 0.5065567 0.072054 0.0625000 NA
22 51222100 rs114553188 G T -0.0021268 0.0081766 0.7899998 0.7947804 0.054561 0.0880591 NA
22 51223637 rs375798137 G A -0.0025422 0.0082179 0.7600007 0.7570599 0.054177 0.0788738 NA
22 51229805 rs9616985 T C 0.0042992 0.0070240 0.5400003 0.5404929 0.071900 0.0730831 NA
22 51232488 rs376461333 A G -0.0168433 0.0164042 0.2999998 0.3045299 0.020218 NA NA
22 51237063 rs3896457 T C 0.0049572 0.0042676 0.2500000 0.2454011 0.297543 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623714 ES:SE:LP:AF:ID  -0.0064868:0.00641643:0.508638:0.623714:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399195 ES:SE:LP:AF:ID  0.000918939:0.00637707:0.05061:0.399195:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103773 ES:SE:LP:AF:ID  0.00612965:0.0101628:0.259637:0.103773:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456293 ES:SE:LP:AF:ID  0.000699381:0.00628217:0.0409586:0.456293:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074543 ES:SE:LP:AF:ID  -0.00202653:0.012392:0.0604807:0.074543:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241197 ES:SE:LP:AF:ID  -0.00429572:0.00718123:0.259637:0.241197:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913022 ES:SE:LP:AF:ID  -0.00572589:0.00890749:0.283997:0.913022:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116941 ES:SE:LP:AF:ID  0.000284691:0.00598765:0.0177288:0.116941:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067577 ES:SE:LP:AF:ID  0.00676264:0.00875783:0.356547:0.067577:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514813 ES:SE:LP:AF:ID  -0.00381836:0.00443277:0.408935:0.514813:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033524 ES:SE:LP:AF:ID  0.0201899:0.0110842:1.16115:0.033524:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037216 ES:SE:LP:AF:ID  0.0188242:0.0100678:1.20761:0.037216:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037343 ES:SE:LP:AF:ID  0.018587:0.0100279:1.19382:0.037343:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036998 ES:SE:LP:AF:ID  0.0193468:0.0101043:1.25181:0.036998:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016412 ES:SE:LP:AF:ID  -0.00972723:0.0157315:0.267606:0.016412:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037574 ES:SE:LP:AF:ID  0.018046:0.00998997:1.14874:0.037574:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037672 ES:SE:LP:AF:ID  0.0188649:0.00995722:1.23657:0.037672:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101516 ES:SE:LP:AF:ID  -0.0027458:0.00730068:0.148742:0.101516:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958398 ES:SE:LP:AF:ID  -0.0201152:0.00960876:1.4437:0.958398:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031737 ES:SE:LP:AF:ID  -0.000967247:0.0175338:0.0177288:0.031737:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052592 ES:SE:LP:AF:ID  -0.0226979:0.0141729:0.958607:0.052592:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037145 ES:SE:LP:AF:ID  0.019277:0.0100263:1.25964:0.037145:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037474 ES:SE:LP:AF:ID  0.019909:0.00993672:1.34679:0.037474:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842015 ES:SE:LP:AF:ID  -0.00567863:0.00518367:0.568636:0.842015:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056088 ES:SE:LP:AF:ID  0.00274167:0.00842188:0.130768:0.056088:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122872 ES:SE:LP:AF:ID  0.00215594:0.00568279:0.154902:0.122872:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02581  ES:SE:LP:AF:ID  -0.0100906:0.0139529:0.327902:0.02581:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122094 ES:SE:LP:AF:ID  0.00220084:0.00568552:0.154902:0.122094:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13331  ES:SE:LP:AF:ID  0.00691721:0.00559514:0.657577:0.13331:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011283 ES:SE:LP:AF:ID  -0.0192032:0.0202286:0.468521:0.011283:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005871 ES:SE:LP:AF:ID  -0.00580879:0.0258456:0.0861861:0.005871:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037418 ES:SE:LP:AF:ID  0.0195133:0.00983518:1.3279:0.037418:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837712 ES:SE:LP:AF:ID  -0.00564935:0.00501891:0.585027:0.837712:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837327 ES:SE:LP:AF:ID  -0.0058053:0.00501345:0.60206:0.837327:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868988 ES:SE:LP:AF:ID  -0.0025915:0.00538035:0.200659:0.868988:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130699 ES:SE:LP:AF:ID  0.00254496:0.00539158:0.19382:0.130699:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037906 ES:SE:LP:AF:ID  0.0197036:0.00967445:1.37675:0.037906:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038166 ES:SE:LP:AF:ID  0.0195476:0.00961184:1.37675:0.038166:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868313 ES:SE:LP:AF:ID  -0.00260397:0.00536978:0.200659:0.868313:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86842  ES:SE:LP:AF:ID  -0.00257131:0.00537221:0.200659:0.86842:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038096 ES:SE:LP:AF:ID  0.0190092:0.00965411:1.3098:0.038096:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868309 ES:SE:LP:AF:ID  -0.00259172:0.00536943:0.200659:0.868309:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005147 ES:SE:LP:AF:ID  -0.00403734:0.0276191:0.0555173:0.005147:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005118 ES:SE:LP:AF:ID  -0.0043062:0.0276792:0.0555173:0.005118:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83681  ES:SE:LP:AF:ID  -0.00539994:0.00500051:0.552842:0.83681:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038109 ES:SE:LP:AF:ID  0.0187321:0.00966711:1.27572:0.038109:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837435 ES:SE:LP:AF:ID  -0.00526947:0.00501428:0.537602:0.837435:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013244 ES:SE:LP:AF:ID  -0.0182055:0.0179415:0.508638:0.013244:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.00547  ES:SE:LP:AF:ID  0.0510387:0.0272039:1.21467:0.00547:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838655 ES:SE:LP:AF:ID  -0.00436229:0.00508242:0.408935:0.838655:rs3131965