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_3083.vcf.gz --id UKB-b:17848 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_3083.txt.gz --cohort_controls 40613 --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-17848/UKB-b-17848_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17848/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:28 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17848/UKB-b-17848_data.vcf.gz ...
Read summary statistics for 7939558 SNPs.
Dropped 6016 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, 1281557 SNPs remain.
After merging with regression SNP LD, 1281557 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2999 (0.0304)
Lambda GC: 1.1672
Mean Chi^2: 1.2631
Intercept: 1.0188 (0.0089)
Ratio: 0.0715 (0.0337)
Analysis finished at Thu Oct 17 14:41:59 2019
Total time elapsed: 1.0m:30.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9425,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -6.2152e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 55,
    "n_p_sig": 4172,
    "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": 74070,
    "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": 1281557,
    "ldsc_nsnp_merge_regression_ld": 1281557,
    "ldsc_observed_scale_h2_beta": 0.2999,
    "ldsc_observed_scale_h2_se": 0.0304,
    "ldsc_intercept_beta": 1.0188,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.1672,
    "ldsc_mean_chisq": 1.2631,
    "ldsc_ratio": 0.0715
}
 

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 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 7933569 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 7939558 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 8.660405e+00 5.763588e+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 7.870876e+07 5.642285e+07 828.0000000 3.225644e+07 6.918309e+07 1.145575e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.200000e-06 1.729010e-02 -0.2238300 -8.247900e-03 -3.500000e-06 8.198900e-03 2.260410e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.417500e-02 8.421000e-03 0.0065098 7.545200e-03 1.045560e-02 1.860220e-02 7.886220e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.782197e-01 2.951159e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.782172e-01 2.950901e-01 0.0000000 2.173726e-01 4.701114e-01 7.339249e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.471889e-01 2.607850e-01 0.0086180 3.650920e-02 1.388410e-01 3.914740e-01 9.913820e-01 ▇▂▂▁▁
numeric AF_reference 74070 0.9906708 NA NA NA NA NA NA NA 2.463905e-01 2.526037e-01 0.0000000 3.873800e-02 1.541530e-01 3.865810e-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 -0.0041393 0.0119690 0.7300002 0.7294642 0.623882 0.7821490 NA
1 54676 rs2462492 C T -0.0150131 0.0118886 0.2099999 0.2066557 0.401861 NA NA
1 86028 rs114608975 T C 0.0156024 0.0188210 0.4100001 0.4071107 0.103927 0.0277556 NA
1 91536 rs6702460 G T -0.0183345 0.0116095 0.1100001 0.1142748 0.458825 0.4207270 NA
1 234313 rs8179466 C T -0.0261657 0.0232096 0.2599998 0.2595880 0.073683 NA NA
1 534192 rs6680723 C T -0.0050524 0.0132524 0.6999999 0.7030193 0.242155 NA NA
1 546697 rs12025928 A G 0.0141411 0.0169115 0.4000000 0.4030523 0.915728 NA NA
1 693731 rs12238997 A G 0.0072409 0.0113707 0.5199996 0.5242541 0.112708 0.1417730 NA
1 705882 rs72631875 G A 0.0132682 0.0167646 0.4299995 0.4286864 0.064258 0.0315495 NA
1 706368 rs55727773 A G -0.0073090 0.0083152 0.3800004 0.3794061 0.513756 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0073680 0.0099904 0.4600002 0.4608137 0.139274 0.2052720 NA
22 51219387 rs9616832 T C -0.0039316 0.0128618 0.7600007 0.7598492 0.076170 0.0654952 NA
22 51219704 rs147475742 G A 0.0035848 0.0174188 0.8400000 0.8369466 0.042286 0.0473243 NA
22 51221190 rs369304721 G A 0.0090613 0.0173128 0.5999997 0.6007043 0.051070 NA NA
22 51221731 rs115055839 T C -0.0021991 0.0128622 0.8600001 0.8642443 0.075698 0.0625000 NA
22 51222100 rs114553188 G T 0.0218875 0.0154457 0.1600000 0.1564651 0.053592 0.0880591 NA
22 51223637 rs375798137 G A 0.0222904 0.0155179 0.1499999 0.1508796 0.053223 0.0788738 NA
22 51229805 rs9616985 T C -0.0014050 0.0129094 0.9100000 0.9133336 0.075449 0.0730831 NA
22 51232488 rs376461333 A G 0.0687784 0.0307647 0.0250000 0.0253762 0.019783 NA NA
22 51237063 rs3896457 T C -0.0139434 0.0079592 0.0800000 0.0797995 0.300040 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623882 ES:SE:LP:AF:ID  -0.00413934:0.011969:0.136677:0.623882:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.401861 ES:SE:LP:AF:ID  -0.0150131:0.0118886:0.677781:0.401861:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103927 ES:SE:LP:AF:ID  0.0156024:0.018821:0.387216:0.103927:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.458825 ES:SE:LP:AF:ID  -0.0183345:0.0116095:0.958607:0.458825:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.073683 ES:SE:LP:AF:ID  -0.0261657:0.0232096:0.585027:0.073683:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242155 ES:SE:LP:AF:ID  -0.00505245:0.0132524:0.154902:0.242155:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.915728 ES:SE:LP:AF:ID  0.0141411:0.0169115:0.39794:0.915728:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.112708 ES:SE:LP:AF:ID  0.00724088:0.0113707:0.283997:0.112708:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.064258 ES:SE:LP:AF:ID  0.0132682:0.0167646:0.366532:0.064258:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513756 ES:SE:LP:AF:ID  -0.00730897:0.00831518:0.420216:0.513756:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.031782 ES:SE:LP:AF:ID  -0.0309788:0.0213067:0.823909:0.031782:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.035201 ES:SE:LP:AF:ID  -0.0281029:0.0193701:0.823909:0.035201:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.035252 ES:SE:LP:AF:ID  -0.0288402:0.0193105:0.853872:0.035252:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035033 ES:SE:LP:AF:ID  -0.0262097:0.0194304:0.744727:0.035033:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016372 ES:SE:LP:AF:ID  -0.035199:0.029451:0.638272:0.016372:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.035597 ES:SE:LP:AF:ID  -0.0268709:0.0192067:0.79588:0.035597:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.035636 ES:SE:LP:AF:ID  -0.0253454:0.0191552:0.721246:0.035636:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.1009   ES:SE:LP:AF:ID  0.00854096:0.0137084:0.275724:0.1009:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.96074  ES:SE:LP:AF:ID  0.0199767:0.0184825:0.552842:0.96074:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031119 ES:SE:LP:AF:ID  -0.0523657:0.0329195:0.958607:0.031119:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05433  ES:SE:LP:AF:ID  0.0280731:0.025941:0.552842:0.05433:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.035163 ES:SE:LP:AF:ID  -0.0277466:0.0192842:0.823909:0.035163:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.035499 ES:SE:LP:AF:ID  -0.028559:0.0190918:0.886057:0.035499:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.848068 ES:SE:LP:AF:ID  -0.00337326:0.00983478:0.136677:0.848068:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.054239 ES:SE:LP:AF:ID  0.024065:0.0159378:0.886057:0.054239:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.118715 ES:SE:LP:AF:ID  0.00999625:0.0107669:0.455932:0.118715:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.026176 ES:SE:LP:AF:ID  -0.0390924:0.0258485:0.886057:0.026176:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.117985 ES:SE:LP:AF:ID  0.00989044:0.0107764:0.443698:0.117985:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.127457 ES:SE:LP:AF:ID  0.00866783:0.0106461:0.376751:0.127457:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011719 ES:SE:LP:AF:ID  0.0052722:0.0366682:0.05061:0.011719:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.035231 ES:SE:LP:AF:ID  -0.026648:0.0189468:0.79588:0.035231:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.844081 ES:SE:LP:AF:ID  -0.0028901:0.00953376:0.119186:0.844081:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.843762 ES:SE:LP:AF:ID  -0.00354849:0.00952374:0.148742:0.843762:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.873824 ES:SE:LP:AF:ID  -0.00840137:0.0102223:0.387216:0.873824:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.125756 ES:SE:LP:AF:ID  0.0101164:0.0102508:0.49485:0.125756:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.035873 ES:SE:LP:AF:ID  -0.0257774:0.0185847:0.769551:0.035873:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.036099 ES:SE:LP:AF:ID  -0.0258384:0.0184692:0.79588:0.036099:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.873233 ES:SE:LP:AF:ID  -0.00917393:0.0102037:0.431798:0.873233:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.873396 ES:SE:LP:AF:ID  -0.00872516:0.01021:0.408935:0.873396:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.036056 ES:SE:LP:AF:ID  -0.0258534:0.0185545:0.79588:0.036056:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.87325  ES:SE:LP:AF:ID  -0.00928114:0.0102032:0.443698:0.87325:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.843261 ES:SE:LP:AF:ID  -0.00305326:0.00950116:0.124939:0.843261:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.036051 ES:SE:LP:AF:ID  -0.0250339:0.0185846:0.744727:0.036051:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.843845 ES:SE:LP:AF:ID  -0.00305284:0.00952784:0.124939:0.843845:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.014003 ES:SE:LP:AF:ID  -0.0472683:0.0326496:0.823909:0.014003:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.844672 ES:SE:LP:AF:ID  -0.00437367:0.00965535:0.187087:0.844672:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.873462 ES:SE:LP:AF:ID  -0.00818843:0.0101906:0.376751:0.873462:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.872965 ES:SE:LP:AF:ID  -0.0082857:0.0101641:0.387216:0.872965:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.872051 ES:SE:LP:AF:ID  -0.00850346:0.0101467:0.39794:0.872051:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.873174 ES:SE:LP:AF:ID  -0.00791651:0.0101745:0.356547:0.873174:rs4951929