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_1797.vcf.gz --id UKB-b:13160 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_1797.txt.gz --cohort_cases 103919 --cohort_controls 346414 --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-13160/UKB-b-13160_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13160/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13160/UKB-b-13160_data.vcf.gz ...
Read summary statistics for 9046903 SNPs.
Dropped 8948 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, 1287268 SNPs remain.
After merging with regression SNP LD, 1287268 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0072 (0.0012)
Lambda GC: 1.1374
Mean Chi^2: 1.1361
Intercept: 1.0717 (0.0069)
Ratio: 0.5266 (0.0504)
Analysis finished at Thu Oct 17 14:43:54 2019
Total time elapsed: 1.0m:37.71s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9478,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 67,
    "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": 95567,
    "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": 1287268,
    "ldsc_nsnp_merge_regression_ld": 1287268,
    "ldsc_observed_scale_h2_beta": 0.0072,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0717,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.1374,
    "ldsc_mean_chisq": 1.1361,
    "ldsc_ratio": 0.5268
}

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 TRUE
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 9037996 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 9046903 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 8.642193e+00 5.757818e+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 7.879252e+07 5.633579e+07 828.0000000 3.244105e+07 6.935741e+07 1.145361e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.560000e-05 3.074500e-03 -0.0375032 -1.189600e-03 7.600000e-06 1.213700e-03 3.982040e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.380200e-03 1.761300e-03 0.0008557 1.021400e-03 1.571000e-03 3.265400e-03 1.979130e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.823755e-01 2.930564e-01 0.0000000 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.823761e-01 2.930309e-01 0.0000000 2.242522e-01 4.758101e-01 7.357201e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.192877e-01 2.584493e-01 0.0033690 2.004300e-02 1.002150e-01 3.457970e-01 9.966310e-01 ▇▂▁▁▁
numeric AF_reference 95567 0.9894365 NA NA NA NA NA NA NA 2.196436e-01 2.503334e-01 0.0000000 1.717250e-02 1.178120e-01 3.442490e-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 0.0013540 0.0015750 0.3900004 0.3899630 0.623821 0.7821490 NA
1 54676 rs2462492 C T -0.0022965 0.0015600 0.1400000 0.1409896 0.400461 NA NA
1 86028 rs114608975 T C -0.0035267 0.0024955 0.1600000 0.1575869 0.103512 0.0277556 NA
1 91536 rs6702460 G T -0.0014750 0.0015366 0.3400001 0.3370931 0.456967 0.4207270 NA
1 234313 rs8179466 C T 0.0021355 0.0030288 0.4799997 0.4807761 0.074526 NA NA
1 534192 rs6680723 C T 0.0001737 0.0017548 0.9199999 0.9211596 0.241007 NA NA
1 546697 rs12025928 A G 0.0005835 0.0021895 0.7899998 0.7898407 0.913451 NA NA
1 693731 rs12238997 A G 0.0010476 0.0014709 0.4799997 0.4763478 0.116227 0.1417730 NA
1 705882 rs72631875 G A -0.0010015 0.0021554 0.6400000 0.6421700 0.067313 0.0315495 NA
1 706368 rs55727773 A G -0.0000928 0.0010893 0.9299999 0.9320848 0.515682 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0005234 0.0013148 0.6899999 0.6906057 0.137832 0.2052720 NA
22 51219387 rs9616832 T C 0.0001818 0.0017064 0.9199999 0.9151326 0.073725 0.0654952 NA
22 51219704 rs147475742 G A 0.0013784 0.0022868 0.5500004 0.5466776 0.041936 0.0473243 NA
22 51221190 rs369304721 G A -0.0004670 0.0022824 0.8400000 0.8378719 0.049727 NA NA
22 51221731 rs115055839 T C 0.0000871 0.0017075 0.9599999 0.9593142 0.073214 0.0625000 NA
22 51222100 rs114553188 G T -0.0011332 0.0020110 0.5700002 0.5731064 0.054400 0.0880591 NA
22 51223637 rs375798137 G A -0.0009208 0.0020207 0.6499995 0.6486166 0.054034 0.0788738 NA
22 51229805 rs9616985 T C 0.0001747 0.0017136 0.9199999 0.9187929 0.073047 0.0730831 NA
22 51232488 rs376461333 A G 0.0016785 0.0040375 0.6800001 0.6776141 0.020024 NA NA
22 51237063 rs3896457 T C -0.0003904 0.0010479 0.7099994 0.7095167 0.297995 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623821 ES:SE:LP:AF:ID  0.00135396:0.00157495:0.408935:0.623821:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400461 ES:SE:LP:AF:ID  -0.00229653:0.00156002:0.853872:0.400461:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103512 ES:SE:LP:AF:ID  -0.00352674:0.00249551:0.79588:0.103512:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456967 ES:SE:LP:AF:ID  -0.00147503:0.00153661:0.468521:0.456967:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074526 ES:SE:LP:AF:ID  0.00213547:0.0030288:0.318759:0.074526:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241007 ES:SE:LP:AF:ID  0.000173675:0.00175477:0.0362122:0.241007:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913451 ES:SE:LP:AF:ID  0.000583532:0.00218947:0.102373:0.913451:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116227 ES:SE:LP:AF:ID  0.00104758:0.00147093:0.318759:0.116227:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067313 ES:SE:LP:AF:ID  -0.00100152:0.00215535:0.19382:0.067313:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515682 ES:SE:LP:AF:ID  -9.28291e-05:0.00108926:0.0315171:0.515682:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032997 ES:SE:LP:AF:ID  3.33387e-05:0.00274652:0.00436481:0.032997:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036614 ES:SE:LP:AF:ID  0.000972373:0.00249465:0.154902:0.036614:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036729 ES:SE:LP:AF:ID  0.00123658:0.00248522:0.207608:0.036729:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03643  ES:SE:LP:AF:ID  0.000972075:0.00250313:0.154902:0.03643:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016403 ES:SE:LP:AF:ID  -0.000808833:0.00385382:0.0809219:0.016403:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03697  ES:SE:LP:AF:ID  0.00109068:0.00247534:0.180456:0.03697:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037065 ES:SE:LP:AF:ID  0.000937626:0.00246687:0.154902:0.037065:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101302 ES:SE:LP:AF:ID  -0.0018002:0.00179623:0.49485:0.101302:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959131 ES:SE:LP:AF:ID  -0.00150603:0.00237991:0.275724:0.959131:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031458 ES:SE:LP:AF:ID  0.00422068:0.00431453:0.481486:0.031458:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053249 ES:SE:LP:AF:ID  0.00300558:0.00343534:0.420216:0.053249:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036583 ES:SE:LP:AF:ID  0.000887528:0.00248288:0.142668:0.036583:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036907 ES:SE:LP:AF:ID  0.00096468:0.00246001:0.161151:0.036907:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843329 ES:SE:LP:AF:ID  -0.00090915:0.00127467:0.318759:0.843329:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055893 ES:SE:LP:AF:ID  0.000680371:0.00206353:0.130768:0.055893:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122206 ES:SE:LP:AF:ID  0.000580645:0.00139535:0.167491:0.122206:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025756 ES:SE:LP:AF:ID  -0.00491115:0.00342812:0.823909:0.025756:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121447 ES:SE:LP:AF:ID  0.000466179:0.00139594:0.130768:0.121447:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132269 ES:SE:LP:AF:ID  0.000672942:0.00137576:0.207608:0.132269:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011116 ES:SE:LP:AF:ID  -0.00319357:0.00500296:0.283997:0.011116:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005687 ES:SE:LP:AF:ID  0.00383885:0.00646168:0.259637:0.005687:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036826 ES:SE:LP:AF:ID  0.00106111:0.00243497:0.180456:0.036826:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839043 ES:SE:LP:AF:ID  -0.00129375:0.00123446:0.537602:0.839043:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838682 ES:SE:LP:AF:ID  -0.00124215:0.00123316:0.508638:0.838682:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869885 ES:SE:LP:AF:ID  -0.000976744:0.00132338:0.337242:0.869885:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129752 ES:SE:LP:AF:ID  0.000801476:0.00132613:0.259637:0.129752:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037333 ES:SE:LP:AF:ID  0.000787165:0.00239381:0.130768:0.037333:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037574 ES:SE:LP:AF:ID  0.000784097:0.00237881:0.130768:0.037574:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869241 ES:SE:LP:AF:ID  -0.000947334:0.00132084:0.327902:0.869241:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869339 ES:SE:LP:AF:ID  -0.000974771:0.00132135:0.337242:0.869339:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037537 ES:SE:LP:AF:ID  0.000723866:0.00238893:0.119186:0.037537:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869241 ES:SE:LP:AF:ID  -0.000944731:0.0013208:0.327902:0.869241:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00513  ES:SE:LP:AF:ID  0.0117229:0.0067741:1.07572:0.00513:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005097 ES:SE:LP:AF:ID  0.0115999:0.00679092:1.05552:0.005097:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838134 ES:SE:LP:AF:ID  -0.0012791:0.00122973:0.522879:0.838134:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037548 ES:SE:LP:AF:ID  0.000714182:0.00239239:0.113509:0.037548:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838766 ES:SE:LP:AF:ID  -0.00129417:0.0012332:0.537602:0.838766:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013786 ES:SE:LP:AF:ID  0.00195716:0.00430124:0.187087:0.013786:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005548 ES:SE:LP:AF:ID  -0.00704321:0.0066398:0.537602:0.005548:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839855 ES:SE:LP:AF:ID  -0.00133207:0.00124979:0.537602:0.839855:rs3131965