Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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 /data/cromwell-executions/qc/f531b2bd-9f41-4213-af9c-7c8b7b2a437c/call-ldsc/inputs/-261044387/ieu-b-4861.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4861/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Thu Jan  6 17:14:14 2022
Reading summary statistics from /data/cromwell-executions/qc/f531b2bd-9f41-4213-af9c-7c8b7b2a437c/call-ldsc/inputs/-261044387/ieu-b-4861.vcf.gz ...
Read summary statistics for 0 SNPs.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
    sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
  File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
    raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.

Analysis finished at Thu Jan  6 17:15:34 2022
Total time elapsed: 1.0m:19.71s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9547,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 11979082,
    "n_clumped_hits": 65,
    "n_p_sig": 5903,
    "n_mono": 0,
    "n_ns": 0,
    "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": 595296,
    "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": 0,
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq NA
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio NA
ldsc_intercept_beta NA
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 1153 0.9999037 3 64 0 11964275 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 11979082 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 8.645409e+00 5.766933e+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 7.883817e+07 5.624891e+07 173.0000000 3.263114e+07 6.947640e+07 1.145116e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.910000e-05 2.674950e-02 -0.4019150 -7.699500e-03 6.900000e-06 7.695100e-03 3.701550e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.895420e-02 1.796110e-02 0.0036572 4.716300e-03 1.033280e-02 2.943100e-02 1.095700e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.629324e-01 2.991882e-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 4.627631e-01 2.991362e-01 0.0000000 1.944304e-01 4.502404e-01 7.219913e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 1.669836e-01 2.448742e-01 0.0010000 4.475000e-03 3.578400e-02 2.405740e-01 9.990000e-01 ▇▁▁▁▁
numeric AF_reference 595296 0.9503054 NA NA NA NA NA NA NA 1.750751e-01 2.401119e-01 0.0000000 3.194900e-03 5.730830e-02 2.623800e-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 0.0010827 0.0065369 0.8800001 0.8684443 0.623350 0.7821490 NA
1 54676 rs2462492 C T -0.0004807 0.0064628 0.8400000 0.9407038 0.401330 NA NA
1 55326 rs3107975 T C -0.0267982 0.0366237 0.5099998 0.4643410 0.008337 0.0459265 NA
1 70728 rs1259734071 C T -0.0239607 0.0646651 0.8000000 0.7109837 0.002173 NA NA
1 79033 rs2462495 A G -0.0328581 0.0847068 0.7600007 0.6980871 0.998742 NA NA
1 86028 rs114608975 T C -0.0074488 0.0103799 0.6100002 0.4729930 0.103431 0.0277556 NA
1 91536 rs6702460 G T -0.0074833 0.0063686 0.2000000 0.2399792 0.457337 0.4207270 NA
1 234313 rs8179466 C T 0.0076238 0.0125647 0.5500004 0.5440064 0.074531 NA NA
1 534192 rs6680723 C T -0.0056286 0.0072833 0.4000000 0.4396343 0.241043 NA NA
1 534583 rs6683466 C G -0.0073477 0.0417089 0.7800007 0.8601641 0.006643 NA NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51223637 rs375798137 G A -0.0042159 0.0083624 0.5800000 0.6141542 0.054571 0.0788738 NA
22 51226692 rs150189434 G A 0.0188552 0.0493725 0.6100002 0.7025379 0.001640 0.0155751 NA
22 51227766 rs186062720 T C -0.0106943 0.0466822 0.8300000 0.8188011 0.002287 0.0005990 NA
22 51229805 rs9616985 T C -0.0128722 0.0071187 0.0819993 0.0705725 0.073199 0.0730831 NA
22 51230673 rs555680442 G C 0.0412904 0.0488080 0.3800004 0.3975661 0.002190 0.0017971 NA
22 51231424 rs539541647 A G -0.0467274 0.0579794 0.3400001 0.4202826 0.001269 0.0011981 NA
22 51232488 rs376461333 A G -0.0037478 0.0167314 0.7800007 0.8227575 0.020171 NA NA
22 51234033 rs764597437 C T -0.0316329 0.0644473 0.6999999 0.6235441 0.001167 NA NA
22 51237063 rs3896457 T C 0.0006851 0.0043508 0.9100000 0.8748785 0.298369 0.2050720 NA
22 51239586 rs535432390 T G -0.0107326 0.0380729 0.7400005 0.7780232 0.003152 0.0001997 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62335  ES:SE:LP:AF:ID  0.00108274:0.00653691:0.0555173:0.62335:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40133  ES:SE:LP:AF:ID  -0.000480737:0.00646279:0.0757207:0.40133:rs2462492
1   55326   rs3107975   T   C   .   PASS    AF=0.008337 ES:SE:LP:AF:ID  -0.0267982:0.0366237:0.29243:0.008337:rs3107975
1   70728   rs1259734071    C   T   .   PASS    AF=0.002173 ES:SE:LP:AF:ID  -0.0239607:0.0646651:0.09691:0.002173:rs1259734071
1   79033   rs2462495   A   G   .   PASS    AF=0.998742 ES:SE:LP:AF:ID  -0.0328581:0.0847068:0.119186:0.998742:rs2462495
1   86028   rs114608975 T   C   .   PASS    AF=0.103431 ES:SE:LP:AF:ID  -0.0074488:0.0103799:0.21467:0.103431:rs114608975
1   91536   rs1251109649    G   T   .   PASS    AF=0.457337 ES:SE:LP:AF:ID  -0.00748334:0.00636859:0.69897:0.457337:rs1251109649
1   234313  rs8179466   C   T   .   PASS    AF=0.074531 ES:SE:LP:AF:ID  0.00762383:0.0125647:0.259637:0.074531:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241043 ES:SE:LP:AF:ID  -0.00562859:0.00728327:0.39794:0.241043:rs6680723
1   534583  rs6683466   C   G   .   PASS    AF=0.006643 ES:SE:LP:AF:ID  -0.00734766:0.0417089:0.107905:0.006643:rs6683466
1   544584  rs576404767 C   T   .   PASS    AF=0.001862 ES:SE:LP:AF:ID  0.101175:0.0596408:1.06048:0.001862:rs576404767
1   546697  rs12025928  A   G   .   PASS    AF=0.913571 ES:SE:LP:AF:ID  -0.0113363:0.00907081:0.657577:0.913571:rs12025928
1   564862  rs1988726   T   C   .   PASS    AF=0.001291 ES:SE:LP:AF:ID  -0.121255:0.0918934:0.769551:0.001291:rs1988726
1   565111  rs573042692 T   C   .   PASS    AF=0.001617 ES:SE:LP:AF:ID  -0.170992:0.0693572:1.92082:0.001617:rs573042692
1   565130  rs371431021 G   A   .   PASS    AF=0.004482 ES:SE:LP:AF:ID  0.00168012:0.0458244:0.0315171:0.004482:rs371431021
1   565196  rs139723294 T   C   .   PASS    AF=0.002267 ES:SE:LP:AF:ID  -0.0782032:0.0645076:0.585027:0.002267:rs139723294
1   565469  rs554127336 C   T   .   PASS    AF=0.001441 ES:SE:LP:AF:ID  -0.0291771:0.0852285:0.173925:0.001441:rs554127336
1   565470  rs544876160 G   A   .   PASS    AF=0.001021 ES:SE:LP:AF:ID  0.15546:0.0735705:1.40894:0.001021:rs544876160
1   565490  rs7349153   T   C   .   PASS    AF=0.001354 ES:SE:LP:AF:ID  -0.108503:0.0908017:0.69897:0.001354:rs7349153
1   566024  rs6421779   G   A   .   PASS    AF=0.001275 ES:SE:LP:AF:ID  -0.0732196:0.0917979:0.420216:0.001275:rs6421779
1   566933  rs113120793 A   G   .   PASS    AF=0.001287 ES:SE:LP:AF:ID  -0.137481:0.0940114:0.886057:0.001287:rs113120793
1   567006  rs565235853 G   T   .   PASS    AF=0.003047 ES:SE:LP:AF:ID  0.00766036:0.0404359:0.0604807:0.003047:rs565235853
1   567092  rs9326622   T   C   .   PASS    AF=0.00134  ES:SE:LP:AF:ID  -0.148281:0.0929402:1:0.00134:rs9326622
1   567486  rs1207788123    T   C   .   PASS    AF=0.001341 ES:SE:LP:AF:ID  -0.159289:0.0929817:1.11919:0.001341:rs1207788123
1   567867  rs2000096   A   G   .   PASS    AF=0.002921 ES:SE:LP:AF:ID  -0.0231762:0.0616583:0.180456:0.002921:rs2000096
1   568072  rs2853820   A   G   .   PASS    AF=0.001506 ES:SE:LP:AF:ID  -0.0410165:0.0843489:0.244125:0.001506:rs2853820
1   568201  rs4098611   T   C   .   PASS    AF=0.001376 ES:SE:LP:AF:ID  -0.110585:0.0913483:0.677781:0.001376:rs4098611
1   568442  rs7419218   T   C   .   PASS    AF=0.001173 ES:SE:LP:AF:ID  -0.118479:0.0988029:0.69897:0.001173:rs7419218
1   568800  rs375217967 G   A   .   PASS    AF=0.016951 ES:SE:LP:AF:ID  0.0236845:0.0248705:0.468521:0.016951:rs375217967
1   569004  rs9285835   T   C   .   PASS    AF=0.015036 ES:SE:LP:AF:ID  0.010807:0.0242571:0.136677:0.015036:rs9285835
1   569543  rs538153094 G   A   .   PASS    AF=0.00155  ES:SE:LP:AF:ID  -0.115095:0.0851727:0.657577:0.00155:rs538153094
1   569604  rs9645429   G   A   .   PASS    AF=0.001644 ES:SE:LP:AF:ID  -0.0688761:0.0744906:0.455932:0.001644:rs9645429
1   570161  rs572999760 G   A   .   PASS    AF=0.001178 ES:SE:LP:AF:ID  -0.00580563:0.0965777:0.0132283:0.001178:rs572999760
1   601550  rs2491328   G   A   .   PASS    AF=0.003596 ES:SE:LP:AF:ID  0.0175845:0.0524529:0.130768:0.003596:rs2491328
1   612758  rs4387125   T   C   .   PASS    AF=0.007036 ES:SE:LP:AF:ID  0.0650374:0.0368273:1.09151:0.007036:rs4387125
1   693731  rs12238997  A   G   .   PASS    AF=0.116508 ES:SE:LP:AF:ID  -0.00500026:0.00608832:0.356547:0.116508:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0668   ES:SE:LP:AF:ID  -0.00640156:0.00895731:0.327902:0.0668:rs72631875
1   705942  rs544671234 A   T   .   PASS    AF=0.003368 ES:SE:LP:AF:ID  -0.00219348:0.0404878:0.0315171:0.003368:rs544671234
1   706368  rs963699400 A   G   .   PASS    AF=0.516349 ES:SE:LP:AF:ID  0.00184812:0.004514:0.113509:0.516349:rs963699400
1   710445  rs1334659872    A   G   .   PASS    AF=0.001129 ES:SE:LP:AF:ID  0.0285828:0.0725896:0.167491:0.001129:rs1334659872
1   713092  rs4565649   G   A   .   PASS    AF=0.001965 ES:SE:LP:AF:ID  0.076403:0.0497606:0.853872:0.001965:rs4565649
1   714277  rs138660747 C   A   .   PASS    AF=0.007583 ES:SE:LP:AF:ID  -0.0297077:0.0283226:0.481486:0.007583:rs138660747
1   715205  rs141090730 C   G   .   PASS    AF=0.00204  ES:SE:LP:AF:ID  0.066971:0.0490873:0.721246:0.00204:rs141090730
1   717474  rs141784362 C   T   .   PASS    AF=0.001962 ES:SE:LP:AF:ID  0.0708494:0.0498418:0.769551:0.001962:rs141784362
1   717587  rs144155419 G   A   .   PASS    AF=0.015849 ES:SE:LP:AF:ID  0.00504027:0.0162861:0.0861861:0.015849:rs144155419
1   718336  rs188996809 T   C   .   PASS    AF=0.001797 ES:SE:LP:AF:ID  -0.0592647:0.0644613:0.443698:0.001797:rs188996809
1   718624  rs777092529 C   G   .   PASS    AF=0.001313 ES:SE:LP:AF:ID  -0.165136:0.0638006:2.09691:0.001313:rs777092529
1   718625  rs762187552 T   G   .   PASS    AF=0.001313 ES:SE:LP:AF:ID  -0.165136:0.0638006:2.09691:0.001313:rs762187552
1   720583  rs551231909 G   A   .   PASS    AF=0.00176  ES:SE:LP:AF:ID  0.0176159:0.0534849:0.113509:0.00176:rs551231909
1   720984  rs564367954 T   G   .   PASS    AF=0.001774 ES:SE:LP:AF:ID  -0.176987:0.0555621:2.85387:0.001774:rs564367954