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/dev/folkersen-pqtl-gwas-import/processed/PROT-b-80/PROT-b-80.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/folkersen-pqtl-gwas-import/processed/PROT-b-80/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Oct 28 22:10:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/folkersen-pqtl-gwas-import/processed/PROT-b-80/PROT-b-80.vcf.gz ...
Read summary statistics for 5135036 SNPs.
Dropped 1 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 759193 SNPs remain.
After merging with regression SNP LD, 759193 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0056 (0.1611)
Lambda GC: 0.9922
Mean Chi^2: 0.9982
Intercept: 0.9978 (0.0099)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Oct 28 22:11:07 2019
Total time elapsed: 49.37s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9563,
    "inflation_factor": 0.9884,
    "mean_EFFECT": 0.0023,
    "n": "-Inf",
    "n_snps": 5135036,
    "n_clumped_hits": 2,
    "n_p_sig": 129,
    "n_mono": 545,
    "n_ns": 317497,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 377170,
    "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": 759193,
    "ldsc_nsnp_merge_regression_ld": 759193,
    "ldsc_observed_scale_h2_beta": 0.0056,
    "ldsc_observed_scale_h2_se": 0.1611,
    "ldsc_intercept_beta": 0.9978,
    "ldsc_intercept_se": 0.0099,
    "ldsc_lambda_gc": 0.9922,
    "ldsc_mean_chisq": 0.9982,
    "ldsc_ratio": 1.2222
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
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 5135032 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 3 0 80 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 3 0 80 0 NA NA NA NA NA NA NA NA NA NA
logical N 5135036 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 8.356760e+00 5.629048e+00 1.0000 3.000000e+00 7.000000e+00 1.200000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.977423e+07 5.495317e+07 29422.0000 3.532730e+07 7.050636e+07 1.143548e+08 2.492183e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.347700e-03 2.727767e-01 -7.6018 -3.650000e-02 2.000000e-04 3.680000e-02 1.010990e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.362155e-01 2.479565e-01 0.0233 3.380000e-02 4.730000e-02 1.088000e-01 3.865400e+00 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.022502e-01 2.880176e-01 0.0000 2.539002e-01 5.024999e-01 7.515000e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 5.020877e-01 2.881174e-01 0.0000 2.536732e-01 5.023814e-01 7.514650e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.781589e-01 2.817943e-01 0.0000 3.560000e-02 1.762000e-01 4.617000e-01 1.000000e+00 ▇▃▂▂▁
numeric AF_reference 377170 0.9265497 NA NA NA NA NA NA NA 2.522964e-01 2.538675e-01 0.0000 3.654150e-02 1.659350e-01 4.039540e-01 1.000000e+00 ▇▃▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 780785 rs2977612 T A 0.0262 0.0464 0.5724994 0.5723083 0.8252 0.669329 NA
1 782981 rs6594026 C T -0.0258 0.0457 0.5724005 0.5723789 0.1534 0.297923 NA
1 783318 rs6686696 A G -0.0404 0.0716 0.5724994 0.5725869 0.0799 0.183107 NA
1 785050 rs2905062 G A 0.0192 0.0340 0.5724994 0.5722738 0.8365 0.626997 NA
1 785989 rs2980300 T C 0.0212 0.0376 0.5724994 0.5728700 0.8083 0.626997 NA
1 787121 rs12077234 T A -0.0336 0.0596 0.5724005 0.5729186 0.1319 NA NA
1 787399 rs2905055 G T 0.0260 0.0461 0.5724994 0.5727600 0.8001 0.646366 NA
1 787685 rs2905054 G T 0.0249 0.0441 0.5724994 0.5723283 0.7668 0.622204 NA
1 787844 rs2905053 C T 0.0270 0.0479 0.5724005 0.5729758 0.8114 0.651757 NA
1 790758 1_790758_GTA_G G GTA 0.0287 0.0509 0.5724005 0.5728558 0.7799 NA NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51163039 rs715584 G T -0.0297 0.0300 0.3234998 0.3221741 0.4131 0.4736420 NA
22 51163138 rs715586 C T 0.0044 0.0361 0.9025999 0.9029912 0.1273 0.0902556 NA
22 51163910 rs192700691 C T 0.0361 0.1072 0.7360003 0.7363026 0.0304 0.0295527 NA
22 51164109 rs5770995 G C -0.0346 0.0282 0.2209999 0.2198413 0.4411 0.5109820 NA
22 51164115 rs5770996 C T -0.0353 0.0284 0.2144999 0.2138834 0.4446 0.5147760 NA
22 51164287 rs6009957 T C -0.0408 0.0273 0.1348000 0.1350435 0.3052 0.4155350 NA
22 51165664 rs8137951 G A -0.0404 0.0265 0.1281000 0.1273768 0.2954 0.4063500 NA
22 51171693 rs756638 G A -0.0285 0.0386 0.4606001 0.4603067 0.3046 0.3049120 NA
22 51175626 rs3810648 A G 0.0138 0.0603 0.8194001 0.8189811 0.0735 0.1084270 NA
22 51178090 rs2285395 G A 0.0242 0.0572 0.6724996 0.6722391 0.0481 0.0666933 NA

bcf preview

1   780785  rs2977612   T   A   .   PASS    AF=0.8252   ES:SE:LP:AF:ID  0.0262:0.0464:0.242225:0.8252:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.1534   ES:SE:LP:AF:ID  -0.0258:0.0457:0.2423:0.1534:rs6594026
1   783318  rs6686696   A   G   .   PASS    AF=0.0799   ES:SE:LP:AF:ID  -0.0404:0.0716:0.242225:0.0799:rs6686696
1   785050  rs2905062   G   A   .   PASS    AF=0.8365   ES:SE:LP:AF:ID  0.0192:0.034:0.242225:0.8365:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.8083   ES:SE:LP:AF:ID  0.0212:0.0376:0.242225:0.8083:rs2980300
1   787121  rs12077234  T   A   .   PASS    AF=0.1319   ES:SE:LP:AF:ID  -0.0336:0.0596:0.2423:0.1319:rs12077234
1   787399  rs2905055   G   T   .   PASS    AF=0.8001   ES:SE:LP:AF:ID  0.026:0.0461:0.242225:0.8001:rs2905055
1   787685  rs2905054   G   T   .   PASS    AF=0.7668   ES:SE:LP:AF:ID  0.0249:0.0441:0.242225:0.7668:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.8114   ES:SE:LP:AF:ID  0.027:0.0479:0.2423:0.8114:rs2905053
1   790758  1_790758_GTA_G  G   GTA .   PASS    AF=0.7799   ES:SE:LP:AF:ID  0.0287:0.0509:0.2423:0.7799:1_790758_GTA_G
1   1108637 rs4970421   G   A   .   PASS    AF=0.0713   ES:SE:LP:AF:ID  0.0614:0.0757:0.380072:0.0713:rs4970421
1   1112982 rs6671609   C   T   .   PASS    AF=0.1436   ES:SE:LP:AF:ID  0.0056:0.06:0.033389:0.1436:rs6671609
1   1115994 rs13376597  G   A   .   PASS    AF=0.1429   ES:SE:LP:AF:ID  0.0021:0.058:0.012736:0.1429:rs13376597
1   1116231 rs13374146  T   C   .   PASS    AF=0.0678   ES:SE:LP:AF:ID  0.0325:0.0612:0.225191:0.0678:rs13374146
1   1117398 rs12097586  A   G   .   PASS    AF=0.4246   ES:SE:LP:AF:ID  -0.0626:0.0437:0.818728:0.4246:rs12097586
1   1117486 rs13376670  A   G   .   PASS    AF=0.1481   ES:SE:LP:AF:ID  0.0034:0.057:0.0214087:0.1481:rs13376670
1   1118275 rs61733845  C   T   .   PASS    AF=0.05 ES:SE:LP:AF:ID  0.0418:0.0575:0.33059:0.05:rs61733845
1   1118578 rs111290899 G   A   .   PASS    AF=0.0504   ES:SE:LP:AF:ID  0.0429:0.0588:0.331521:0.0504:rs111290899
1   1119657 rs4560982   G   C   .   PASS    AF=0.4012   ES:SE:LP:AF:ID  -0.0548:0.0391:0.790485:0.4012:rs4560982
1   1119858 rs1320565   C   T   .   PASS    AF=0.1126   ES:SE:LP:AF:ID  0.0217:0.0603:0.143513:0.1126:rs1320565
1   1120431 rs1320571   G   A   .   PASS    AF=0.0525   ES:SE:LP:AF:ID  0.0615:0.055:0.578232:0.0525:rs1320571
1   1121014 rs3813204   G   A   .   PASS    AF=0.1364   ES:SE:LP:AF:ID  -0.0873:0.057:0.90101:0.1364:rs3813204
1   1121341 rs4297230   C   T   .   PASS    AF=0.1422   ES:SE:LP:AF:ID  -0.0915:0.0556:1.00078:0.1422:rs4297230
1   1121358 rs80057011  A   C   .   PASS    AF=0.0928   ES:SE:LP:AF:ID  -0.0851:0.0655:0.711974:0.0928:rs80057011
1   1121480 rs12063663  T   C   .   PASS    AF=0.0923   ES:SE:LP:AF:ID  -0.0927:0.0653:0.806597:0.0923:rs12063663
1   1121625 rs4081334   C   G   .   PASS    AF=0.1418   ES:SE:LP:AF:ID  -0.089:0.0551:0.973875:0.1418:rs4081334
1   1121657 rs11260548  T   C   .   PASS    AF=0.2302   ES:SE:LP:AF:ID  -0.0704:0.0371:1.23905:0.2302:rs11260548
1   1121715 rs4081333   C   T   .   PASS    AF=0.0882   ES:SE:LP:AF:ID  -0.0864:0.0643:0.747875:0.0882:rs4081333
1   1121794 rs11260549  G   A   .   PASS    AF=0.1326   ES:SE:LP:AF:ID  -0.0824:0.0549:0.875496:0.1326:rs11260549
1   1121835 rs57346441  C   CTG .   PASS    AF=0.2304   ES:SE:LP:AF:ID  -0.0698:0.0363:1.26608:0.2304:1_1121835_C_CTG
1   1122024 rs4314833   T   C   .   PASS    AF=0.1279   ES:SE:LP:AF:ID  -0.0816:0.056:0.838932:0.1279:rs4314833
1   1122196 rs4634847   A   G   .   PASS    AF=0.1342   ES:SE:LP:AF:ID  -0.0881:0.0546:0.970211:0.1342:rs4634847
1   1122283 rs12064046  T   G   .   PASS    AF=0.0862   ES:SE:LP:AF:ID  -0.0856:0.0638:0.746178:0.0862:rs12064046
1   1122319 rs7415847   C   T   .   PASS    AF=0.1199   ES:SE:LP:AF:ID  -0.085:0.0598:0.809388:0.1199:rs7415847
1   1122468 rs7545694   T   C   .   PASS    AF=0.2031   ES:SE:LP:AF:ID  -0.0725:0.0399:1.15827:0.2031:rs7545694
1   1122516 rs11260551  G   A   .   PASS    AF=0.1274   ES:SE:LP:AF:ID  -0.0805:0.0558:0.827105:0.1274:rs11260551
1   1122539 rs12063897  A   G   .   PASS    AF=0.0866   ES:SE:LP:AF:ID  -0.0854:0.063:0.75721:0.0866:rs12063897
1   1122915 rs28595293  A   G   .   PASS    AF=0.2718   ES:SE:LP:AF:ID  -0.0694:0.0319:1.52681:0.2718:rs28595293
1   1122916 rs28460227  A   G   .   PASS    AF=0.0856   ES:SE:LP:AF:ID  -0.0848:0.0631:0.747147:0.0856:rs28460227
1   1122937 rs28648687  G   A   .   PASS    AF=0.0856   ES:SE:LP:AF:ID  -0.0848:0.0631:0.747147:0.0856:rs28648687
1   1123106 rs12401472  G   A   .   PASS    AF=0.128    ES:SE:LP:AF:ID  -0.0799:0.0554:0.826814:0.128:rs12401472
1   1123434 rs12066716  T   A   .   PASS    AF=0.1323   ES:SE:LP:AF:ID  -0.107:0.0536:1.33724:0.1323:rs12066716
1   1124257 rs10907172  A   G   .   PASS    AF=0.1273   ES:SE:LP:AF:ID  -0.0795:0.0551:0.826814:0.1273:rs10907172
1   1124399 rs10907173  C   G   .   PASS    AF=0.1324   ES:SE:LP:AF:ID  -0.083:0.0539:0.90763:0.1324:rs10907173
1   1124663 rs6684820   G   A   .   PASS    AF=0.2737   ES:SE:LP:AF:ID  -0.0686:0.0312:1.55222:0.2737:rs6684820
1   1124819 rs6694487   C   T   .   PASS    AF=0.0867   ES:SE:LP:AF:ID  -0.0868:0.0624:0.784098:0.0867:rs6694487
1   1124891 rs61768485  G   A   .   PASS    AF=0.1266   ES:SE:LP:AF:ID  -0.0792:0.0549:0.825649:0.1266:rs61768485
1   1125110 rs12124436  T   C   .   PASS    AF=0.1248   ES:SE:LP:AF:ID  -0.0781:0.0547:0.813609:0.1248:rs12124436
1   1125220 rs12065129  C   T   .   PASS    AF=0.0864   ES:SE:LP:AF:ID  -0.0863:0.0619:0.787812:0.0864:rs12065129
1   1125348 rs12029885  T   C   .   PASS    AF=0.1261   ES:SE:LP:AF:ID  -0.0839:0.0551:0.892451:0.1261:rs12029885