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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}

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-18275/UKB-b-18275_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18275/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18275/UKB-b-18275_data.vcf.gz ...
Read summary statistics for 9401286 SNPs.
Dropped 10942 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, 1288165 SNPs remain.
After merging with regression SNP LD, 1288165 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0508 (0.002)
Lambda GC: 1.3811
Mean Chi^2: 1.4701
Intercept: 1.023 (0.0086)
Ratio: 0.049 (0.0183)
Analysis finished at Thu Oct 17 14:42:04 2019
Total time elapsed: 1.0m:46.36s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9489,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -1.3771e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 35,
    "n_p_sig": 5072,
    "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": 121951,
    "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": 1288165,
    "ldsc_nsnp_merge_regression_ld": 1288165,
    "ldsc_observed_scale_h2_beta": 0.0508,
    "ldsc_observed_scale_h2_se": 0.002,
    "ldsc_intercept_beta": 1.023,
    "ldsc_intercept_se": 0.0086,
    "ldsc_lambda_gc": 1.3811,
    "ldsc_mean_chisq": 1.4701,
    "ldsc_ratio": 0.0489
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 9390400 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 9401286 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 8.631520e+00 5.752730e+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 7.882494e+07 5.630840e+07 828.0000000 3.252091e+07 6.940769e+07 1.145536e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.400000e-06 4.038700e-03 -0.0734697 -1.563100e-03 -9.000000e-07 1.556700e-03 4.863410e-02 ▁▁▇▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.987200e-03 2.426600e-03 0.0009739 1.175100e-03 1.874600e-03 4.082100e-03 3.370080e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.607464e-01 2.995508e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.607493e-01 2.995270e-01 0.0000000 1.913216e-01 4.470990e-01 7.202799e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.117974e-01 2.575653e-01 0.0020400 1.661900e-02 8.965200e-02 3.319800e-01 9.979600e-01 ▇▂▁▁▁
numeric AF_reference 121951 0.9870283 NA NA NA NA NA NA NA 2.131097e-01 2.493268e-01 0.0000000 1.397760e-02 1.086260e-01 3.326680e-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 -0.0018322 0.0017914 0.3100002 0.3064008 0.623734 0.7821490 NA
1 54676 rs2462492 C T -0.0019145 0.0017745 0.2800000 0.2806552 0.400516 NA NA
1 86028 rs114608975 T C 0.0029278 0.0028374 0.2999998 0.3021375 0.103550 0.0277556 NA
1 91536 rs6702460 G T -0.0041167 0.0017469 0.0179999 0.0184447 0.456924 0.4207270 NA
1 234313 rs8179466 C T -0.0047880 0.0034482 0.1600000 0.1649749 0.074466 NA NA
1 534192 rs6680723 C T 0.0002826 0.0019959 0.8900000 0.8874175 0.240965 NA NA
1 546697 rs12025928 A G -0.0049258 0.0024900 0.0479999 0.0479087 0.913493 NA NA
1 693731 rs12238997 A G 0.0011689 0.0016724 0.4799997 0.4846075 0.116396 0.1417730 NA
1 705882 rs72631875 G A 0.0044488 0.0024505 0.0690001 0.0694512 0.067310 0.0315495 NA
1 706368 rs55727773 A G -0.0010329 0.0012389 0.4000000 0.4044346 0.515598 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0017437 0.0014960 0.2399999 0.2437792 0.137902 0.2052720 NA
22 51219387 rs9616832 T C 0.0016766 0.0019418 0.3900004 0.3879038 0.073737 0.0654952 NA
22 51219704 rs147475742 G A -0.0010012 0.0026023 0.6999999 0.7004438 0.041949 0.0473243 NA
22 51221190 rs369304721 G A 0.0023981 0.0025978 0.3599996 0.3559430 0.049719 NA NA
22 51221731 rs115055839 T C 0.0018247 0.0019430 0.3500000 0.3476639 0.073226 0.0625000 NA
22 51222100 rs114553188 G T 0.0019587 0.0022883 0.3900004 0.3920197 0.054414 0.0880591 NA
22 51223637 rs375798137 G A 0.0019282 0.0022993 0.4000000 0.4017064 0.054044 0.0788738 NA
22 51229805 rs9616985 T C 0.0019272 0.0019500 0.3200000 0.3230019 0.073063 0.0730831 NA
22 51232488 rs376461333 A G -0.0057302 0.0045940 0.2099999 0.2122802 0.020030 NA NA
22 51237063 rs3896457 T C -0.0016373 0.0011924 0.1700000 0.1697165 0.298079 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623734 ES:SE:LP:AF:ID  -0.00183225:0.0017914:0.508638:0.623734:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400516 ES:SE:LP:AF:ID  -0.00191446:0.00177454:0.552842:0.400516:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10355  ES:SE:LP:AF:ID  0.00292777:0.00283737:0.522879:0.10355:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456924 ES:SE:LP:AF:ID  -0.00411669:0.0017469:1.74473:0.456924:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074466 ES:SE:LP:AF:ID  -0.00478798:0.00344823:0.79588:0.074466:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  0.000282565:0.0019959:0.05061:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913493 ES:SE:LP:AF:ID  -0.00492576:0.00249005:1.31876:0.913493:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116396 ES:SE:LP:AF:ID  0.00116888:0.00167243:0.318759:0.116396:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06731  ES:SE:LP:AF:ID  0.0044488:0.00245049:1.16115:0.06731:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515598 ES:SE:LP:AF:ID  -0.00103293:0.00123893:0.39794:0.515598:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032972 ES:SE:LP:AF:ID  -0.00364448:0.00312563:0.619789:0.032972:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036593 ES:SE:LP:AF:ID  -0.00287402:0.0028387:0.508638:0.036593:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036708 ES:SE:LP:AF:ID  -0.00299773:0.00282806:0.537602:0.036708:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036404 ES:SE:LP:AF:ID  -0.00264707:0.00284856:0.455932:0.036404:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016406 ES:SE:LP:AF:ID  0.00238224:0.00438403:0.229148:0.016406:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036944 ES:SE:LP:AF:ID  -0.00265824:0.00281693:0.455932:0.036944:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037038 ES:SE:LP:AF:ID  -0.0030325:0.00280736:0.552842:0.037038:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10126  ES:SE:LP:AF:ID  -0.000760099:0.00204381:0.148742:0.10126:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959136 ES:SE:LP:AF:ID  0.00396022:0.00270792:0.853872:0.959136:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  -0.00573647:0.00491277:0.619789:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053266 ES:SE:LP:AF:ID  -0.00582827:0.00390691:0.853872:0.053266:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03656  ES:SE:LP:AF:ID  -0.00277721:0.00282542:0.481486:0.03656:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036875 ES:SE:LP:AF:ID  -0.00223832:0.00279971:0.376751:0.036875:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843165 ES:SE:LP:AF:ID  -0.000602932:0.0014495:0.167491:0.843165:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055968 ES:SE:LP:AF:ID  -0.00250459:0.00234611:0.537602:0.055968:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12239  ES:SE:LP:AF:ID  0.00161168:0.00158639:0.508638:0.12239:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025718 ES:SE:LP:AF:ID  0.000131417:0.00390242:0.0132283:0.025718:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121632 ES:SE:LP:AF:ID  0.00165139:0.00158707:0.522879:0.121632:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132385 ES:SE:LP:AF:ID  0.000446954:0.00156424:0.107905:0.132385:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011116 ES:SE:LP:AF:ID  0.00676085:0.00569565:0.619789:0.011116:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.0057   ES:SE:LP:AF:ID  -0.002569:0.00734401:0.136677:0.0057:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002269 ES:SE:LP:AF:ID  -0.0182369:0.0123392:0.853872:0.002269:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.03679  ES:SE:LP:AF:ID  -0.00297926:0.00277134:0.552842:0.03679:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838887 ES:SE:LP:AF:ID  -6.07679e-05:0.00140368:0.0132283:0.838887:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838518 ES:SE:LP:AF:ID  0.000100169:0.00140216:0.0268721:0.838518:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869691 ES:SE:LP:AF:ID  -0.000613199:0.00150445:0.167491:0.869691:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129947 ES:SE:LP:AF:ID  0.000529533:0.00150756:0.136677:0.129947:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037295 ES:SE:LP:AF:ID  -0.00273833:0.00272466:0.508638:0.037295:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -0.00262534:0.00270742:0.481486:0.037539:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869039 ES:SE:LP:AF:ID  -0.000362821:0.00150149:0.091515:0.869039:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869138 ES:SE:LP:AF:ID  -0.000377835:0.0015021:0.09691:0.869138:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037495 ES:SE:LP:AF:ID  -0.0028122:0.00271921:0.522879:0.037495:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869041 ES:SE:LP:AF:ID  -0.000349594:0.00150146:0.0861861:0.869041:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00513  ES:SE:LP:AF:ID  -0.00733838:0.00770296:0.468521:0.00513:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005095 ES:SE:LP:AF:ID  -0.00780531:0.0077234:0.508638:0.005095:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837976 ES:SE:LP:AF:ID  0.000119464:0.0013983:0.0315171:0.837976:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037507 ES:SE:LP:AF:ID  -0.00273058:0.00272304:0.49485:0.037507:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838603 ES:SE:LP:AF:ID  4.24092e-05:0.00140223:0.00877392:0.838603:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013782 ES:SE:LP:AF:ID  -0.0057916:0.00489415:0.619789:0.013782:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005541 ES:SE:LP:AF:ID  -0.00172707:0.00755616:0.0861861:0.005541:rs184270342