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_4653.vcf.gz --id UKB-b:8196 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_4653.txt.gz --cohort_cases 27205 --cohort_controls 122296 --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-8196/UKB-b-8196_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8196/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8196/UKB-b-8196_data.vcf.gz ...
Read summary statistics for 7372252 SNPs.
Dropped 4942 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, 1273628 SNPs remain.
After merging with regression SNP LD, 1273628 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0474 (0.0044)
Lambda GC: 1.1397
Mean Chi^2: 1.1582
Intercept: 1.0177 (0.0077)
Ratio: 0.1122 (0.0484)
Analysis finished at Thu Oct 17 14:42:57 2019
Total time elapsed: 1.0m:30.91s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9389,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 100,
    "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": 68205,
    "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": 1273628,
    "ldsc_nsnp_merge_regression_ld": 1273628,
    "ldsc_observed_scale_h2_beta": 0.0474,
    "ldsc_observed_scale_h2_se": 0.0044,
    "ldsc_intercept_beta": 1.0177,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.1397,
    "ldsc_mean_chisq": 1.1582,
    "ldsc_ratio": 0.1119
}

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 7367332 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 7372252 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 8.664004e+00 5.763840e+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 7.863522e+07 5.644517e+07 828.0000000 3.217438e+07 6.904877e+07 1.145177e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.100000e-05 3.084900e-03 -0.0271877 -1.584400e-03 1.370000e-05 1.615500e-03 2.812240e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.630700e-03 1.359800e-03 0.0013591 1.548500e-03 2.049200e-03 3.364200e-03 1.476320e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.808069e-01 2.943073e-01 0.0000000 2.200002e-01 4.700002e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.808084e-01 2.942824e-01 0.0000000 2.208919e-01 4.739242e-01 7.362972e-01 1.000000e+00 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.639879e-01 2.606231e-01 0.0128660 4.944500e-02 1.627070e-01 4.158052e-01 9.871340e-01 ▇▂▂▁▁
numeric AF_reference 68205 0.9907484 NA NA NA NA NA NA NA 2.627112e-01 2.525059e-01 0.0000000 5.531150e-02 1.761180e-01 4.097440e-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 0.0005985 0.0025049 0.8100000 0.8111504 0.623718 0.7821490 NA
1 54676 rs2462492 C T 0.0003009 0.0024884 0.9000000 0.9037424 0.399350 NA NA
1 86028 rs114608975 T C -0.0010543 0.0039692 0.7899998 0.7905355 0.103740 0.0277556 NA
1 91536 rs6702460 G T -0.0018224 0.0024509 0.4600002 0.4571374 0.456233 0.4207270 NA
1 234313 rs8179466 C T -0.0051091 0.0048438 0.2900000 0.2915283 0.074501 NA NA
1 534192 rs6680723 C T -0.0037450 0.0028038 0.1800002 0.1816391 0.241155 NA NA
1 546697 rs12025928 A G -0.0018281 0.0034766 0.5999997 0.5990036 0.913054 NA NA
1 693731 rs12238997 A G 0.0029734 0.0023368 0.2000000 0.2032244 0.116940 0.1417730 NA
1 705882 rs72631875 G A 0.0006013 0.0034137 0.8600001 0.8601797 0.067699 0.0315495 NA
1 706368 rs55727773 A G -0.0000081 0.0017299 1.0000000 0.9962742 0.515121 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0055364 0.0020957 0.0081999 0.0082460 0.137074 0.2052720 NA
22 51219387 rs9616832 T C 0.0040531 0.0027247 0.1400000 0.1368723 0.072769 0.0654952 NA
22 51219704 rs147475742 G A 0.0003611 0.0036348 0.9199999 0.9208631 0.041740 0.0473243 NA
22 51221190 rs369304721 G A 0.0035460 0.0036469 0.3300000 0.3308769 0.049126 NA NA
22 51221731 rs115055839 T C 0.0039089 0.0027266 0.1499999 0.1516834 0.072250 0.0625000 NA
22 51222100 rs114553188 G T 0.0057292 0.0031947 0.0729995 0.0729172 0.054385 0.0880591 NA
22 51223637 rs375798137 G A 0.0057210 0.0032107 0.0749998 0.0747776 0.054003 0.0788738 NA
22 51229805 rs9616985 T C 0.0035939 0.0027363 0.1900002 0.1890371 0.072111 0.0730831 NA
22 51232488 rs376461333 A G 0.0075098 0.0064142 0.2399999 0.2416732 0.020135 NA NA
22 51237063 rs3896457 T C -0.0031181 0.0016637 0.0610000 0.0609072 0.297681 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623718 ES:SE:LP:AF:ID  0.000598524:0.00250489:0.091515:0.623718:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39935  ES:SE:LP:AF:ID  0.00030094:0.00248844:0.0457575:0.39935:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10374  ES:SE:LP:AF:ID  -0.00105428:0.0039692:0.102373:0.10374:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456233 ES:SE:LP:AF:ID  -0.00182242:0.00245091:0.337242:0.456233:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074501 ES:SE:LP:AF:ID  -0.00510914:0.00484382:0.537602:0.074501:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241155 ES:SE:LP:AF:ID  -0.00374504:0.00280375:0.744727:0.241155:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913054 ES:SE:LP:AF:ID  -0.00182813:0.00347663:0.221849:0.913054:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11694  ES:SE:LP:AF:ID  0.00297335:0.00233677:0.69897:0.11694:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067699 ES:SE:LP:AF:ID  0.000601313:0.00341373:0.0655015:0.067699:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515121 ES:SE:LP:AF:ID  -8.07804e-06:0.00172993:-0:0.515121:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033519 ES:SE:LP:AF:ID  0.00489483:0.00432597:0.585027:0.033519:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037226 ES:SE:LP:AF:ID  0.00416333:0.00392797:0.537602:0.037226:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037351 ES:SE:LP:AF:ID  0.00424357:0.00391274:0.552842:0.037351:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037007 ES:SE:LP:AF:ID  0.00394639:0.00394239:0.49485:0.037007:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016346 ES:SE:LP:AF:ID  0.00301049:0.00615357:0.207608:0.016346:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037591 ES:SE:LP:AF:ID  0.00396058:0.00389709:0.508638:0.037591:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037687 ES:SE:LP:AF:ID  0.00412044:0.00388453:0.537602:0.037687:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101504 ES:SE:LP:AF:ID  -0.00425785:0.00284965:0.853872:0.101504:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958379 ES:SE:LP:AF:ID  -0.00455161:0.0037496:0.657577:0.958379:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031693 ES:SE:LP:AF:ID  0.00894704:0.00684748:0.721246:0.031693:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052629 ES:SE:LP:AF:ID  0.00064419:0.00552954:0.0409586:0.052629:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037147 ES:SE:LP:AF:ID  0.00422504:0.00391225:0.552842:0.037147:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037485 ES:SE:LP:AF:ID  0.00368821:0.00387684:0.468521:0.037485:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842014 ES:SE:LP:AF:ID  -0.00278637:0.00202283:0.769551:0.842014:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056077 ES:SE:LP:AF:ID  0.00167557:0.00328495:0.21467:0.056077:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122856 ES:SE:LP:AF:ID  0.00275327:0.00221788:0.677781:0.122856:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025797 ES:SE:LP:AF:ID  -0.00164679:0.00544767:0.119186:0.025797:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122067 ES:SE:LP:AF:ID  0.00281361:0.00221905:0.69897:0.122067:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133348 ES:SE:LP:AF:ID  0.00221724:0.00218289:0.508638:0.133348:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.037421 ES:SE:LP:AF:ID  0.00259858:0.00383736:0.30103:0.037421:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837758 ES:SE:LP:AF:ID  -0.00292135:0.00195869:0.853872:0.837758:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837378 ES:SE:LP:AF:ID  -0.00293438:0.00195658:0.886057:0.837378:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869058 ES:SE:LP:AF:ID  -0.00366874:0.0021003:1.09151:0.869058:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130639 ES:SE:LP:AF:ID  0.00339598:0.00210454:0.958607:0.130639:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037911 ES:SE:LP:AF:ID  0.00266139:0.00377461:0.318759:0.037911:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038164 ES:SE:LP:AF:ID  0.00267233:0.00375061:0.318759:0.038164:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868383 ES:SE:LP:AF:ID  -0.00363757:0.00209608:1.08092:0.868383:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868492 ES:SE:LP:AF:ID  -0.00359805:0.00209704:1.0655:0.868492:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038091 ES:SE:LP:AF:ID  0.00271143:0.00376713:0.327902:0.038091:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868379 ES:SE:LP:AF:ID  -0.00364226:0.00209594:1.08619:0.868379:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836858 ES:SE:LP:AF:ID  -0.00288043:0.00195149:0.853872:0.836858:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038103 ES:SE:LP:AF:ID  0.00286639:0.00377225:0.346787:0.038103:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837494 ES:SE:LP:AF:ID  -0.00289643:0.00195691:0.853872:0.837494:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01327  ES:SE:LP:AF:ID  -0.00492721:0.00699364:0.318759:0.01327:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.838728 ES:SE:LP:AF:ID  -0.00320997:0.00198361:0.958607:0.838728:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.86869  ES:SE:LP:AF:ID  -0.00353974:0.00209382:1.04096:0.86869:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868237 ES:SE:LP:AF:ID  -0.00343885:0.00208856:1:0.868237:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867053 ES:SE:LP:AF:ID  -0.00368591:0.00208363:1.11351:0.867053:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868381 ES:SE:LP:AF:ID  -0.00348522:0.00209024:1.02228:0.868381:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868393 ES:SE:LP:AF:ID  -0.00346724:0.00209039:1.01323:0.868393:rs4951862