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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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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-10787/UKB-b-10787_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10787/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-10787/UKB-b-10787_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.4492 (0.0193)
Lambda GC: 2.8972
Mean Chi^2: 6.0835
Intercept: 1.6204 (0.0393)
Ratio: 0.122 (0.0077)
Analysis finished at Thu Oct 17 14:42:04 2019
Total time elapsed: 1.0m:45.98s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 2.1738,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 773,
    "n_p_sig": 241558,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.4492,
    "ldsc_observed_scale_h2_se": 0.0193,
    "ldsc_intercept_beta": 1.6204,
    "ldsc_intercept_se": 0.0393,
    "ldsc_lambda_gc": 2.8972,
    "ldsc_mean_chisq": 6.0835,
    "ldsc_ratio": 0.122
}

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 TRUE
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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.230000e-05 8.158700e-03 -0.2050310 -3.027300e-03 -5.000000e-06 3.000100e-03 2.237810e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.499200e-03 4.258100e-03 0.0012533 1.541500e-03 2.584400e-03 5.962800e-03 6.569660e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.737677e-01 3.149368e-01 0.0000000 7.100030e-02 3.200000e-01 6.400000e-01 1.000000e+00 ▇▃▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.737719e-01 3.149180e-01 0.0000000 7.054290e-02 3.153728e-01 6.417057e-01 1.000000e+00 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568615e-01 0.0009930 1.316900e-02 7.791400e-02 3.164530e-01 9.990060e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 0.0013909 0.0023019 0.5500004 0.5456859 0.623778 0.7821490 NA
1 54676 rs2462492 C T 0.0019657 0.0022804 0.3900004 0.3886962 0.400406 NA NA
1 86028 rs114608975 T C -0.0017670 0.0036462 0.6300007 0.6279434 0.103541 0.0277556 NA
1 91536 rs6702460 G T 0.0027113 0.0022453 0.2300001 0.2272335 0.456859 0.4207270 NA
1 234313 rs8179466 C T -0.0025100 0.0044278 0.5700002 0.5708018 0.074491 NA NA
1 534192 rs6680723 C T -0.0032099 0.0025647 0.2099999 0.2107393 0.240949 NA NA
1 546697 rs12025928 A G 0.0052439 0.0031992 0.1000000 0.1011855 0.913454 NA NA
1 693731 rs12238997 A G -0.0032971 0.0021496 0.1299999 0.1250693 0.116295 0.1417730 NA
1 705882 rs72631875 G A -0.0039047 0.0031494 0.2200002 0.2150515 0.067299 0.0315495 NA
1 706368 rs55727773 A G 0.0002094 0.0015921 0.9000000 0.8953582 0.515683 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0069250 0.0033980 0.0420001 0.0415542 0.041958 0.0473243 NA
22 51219766 rs182321900 C T -0.0235685 0.0158247 0.1400000 0.1363955 0.001939 NA NA
22 51220146 rs868950473 C T -0.0244870 0.0156752 0.1199999 0.1182529 0.001987 NA NA
22 51221190 rs369304721 G A 0.0006754 0.0033927 0.8400000 0.8422082 0.049732 NA NA
22 51221731 rs115055839 T C 0.0001391 0.0025375 0.9599999 0.9562726 0.073242 0.0625000 NA
22 51222100 rs114553188 G T 0.0046102 0.0029872 0.1199999 0.1227570 0.054469 0.0880591 NA
22 51223637 rs375798137 G A 0.0045610 0.0030017 0.1299999 0.1286411 0.054098 0.0788738 NA
22 51229805 rs9616985 T C 0.0003073 0.0025467 0.9000000 0.9039448 0.073076 0.0730831 NA
22 51232488 rs376461333 A G 0.0034665 0.0059981 0.5600000 0.5633068 0.020048 NA NA
22 51237063 rs3896457 T C -0.0036974 0.0015576 0.0179999 0.0176116 0.297924 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623778 ES:SE:LP:AF:ID  0.0013909:0.00230191:0.259637:0.623778:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  0.00196566:0.00228039:0.408935:0.400406:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103541 ES:SE:LP:AF:ID  -0.00176701:0.00364615:0.200659:0.103541:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  0.00271126:0.00224532:0.638272:0.456859:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074491 ES:SE:LP:AF:ID  -0.00250998:0.00442778:0.244125:0.074491:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240949 ES:SE:LP:AF:ID  -0.00320985:0.00256473:0.677781:0.240949:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913454 ES:SE:LP:AF:ID  0.00524385:0.00319916:1:0.913454:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116295 ES:SE:LP:AF:ID  -0.00329714:0.0021496:0.886057:0.116295:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067299 ES:SE:LP:AF:ID  -0.00390467:0.00314945:0.657577:0.067299:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515683 ES:SE:LP:AF:ID  0.000209406:0.00159211:0.0457575:0.515683:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033003 ES:SE:LP:AF:ID  -0.00397039:0.00401402:0.49485:0.033003:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036619 ES:SE:LP:AF:ID  -0.00323822:0.00364602:0.431798:0.036619:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036737 ES:SE:LP:AF:ID  -0.00334559:0.00363216:0.443698:0.036737:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036436 ES:SE:LP:AF:ID  -0.00355293:0.00365839:0.481486:0.036436:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016399 ES:SE:LP:AF:ID  -0.00136037:0.00563459:0.091515:0.016399:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036974 ES:SE:LP:AF:ID  -0.00348794:0.00361789:0.468521:0.036974:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037071 ES:SE:LP:AF:ID  -0.00342849:0.00360548:0.468521:0.037071:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101197 ES:SE:LP:AF:ID  0.0014516:0.00262694:0.236572:0.101197:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959095 ES:SE:LP:AF:ID  0.00340765:0.00347738:0.481486:0.959095:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031451 ES:SE:LP:AF:ID  -0.00130304:0.00631212:0.0757207:0.031451:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053253 ES:SE:LP:AF:ID  0.00513893:0.005022:0.508638:0.053253:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036593 ES:SE:LP:AF:ID  -0.00376565:0.00362864:0.522879:0.036593:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036907 ES:SE:LP:AF:ID  -0.0033676:0.00359568:0.455932:0.036907:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843245 ES:SE:LP:AF:ID  0.00355797:0.00186282:1.25181:0.843245:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055894 ES:SE:LP:AF:ID  0.000874805:0.00301633:0.113509:0.055894:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12227  ES:SE:LP:AF:ID  -0.00366026:0.00203913:1.13668:0.12227:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025715 ES:SE:LP:AF:ID  0.00317331:0.00501523:0.275724:0.025715:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121513 ES:SE:LP:AF:ID  -0.00370333:0.00203999:1.16115:0.121513:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132308 ES:SE:LP:AF:ID  -0.0038747:0.00201053:1.26761:0.132308:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011134 ES:SE:LP:AF:ID  0.0116207:0.00730996:0.958607:0.011134:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005694 ES:SE:LP:AF:ID  -0.00294855:0.00944046:0.124939:0.005694:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002273 ES:SE:LP:AF:ID  0.000270296:0.0158476:0.00436481:0.002273:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.00103  ES:SE:LP:AF:ID  0.0192543:0.0259639:0.337242:0.00103:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036823 ES:SE:LP:AF:ID  -0.00393614:0.00355927:0.568636:0.036823:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838983 ES:SE:LP:AF:ID  0.00309998:0.00180401:1.0655:0.838983:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838614 ES:SE:LP:AF:ID  0.00311622:0.00180207:1.07572:0.838614:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869816 ES:SE:LP:AF:ID  0.00313894:0.00193378:1:0.869816:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12983  ES:SE:LP:AF:ID  -0.00302146:0.00193777:0.920819:0.12983:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037335 ES:SE:LP:AF:ID  -0.0048698:0.00349892:0.79588:0.037335:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037578 ES:SE:LP:AF:ID  -0.00497185:0.00347687:0.823909:0.037578:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869162 ES:SE:LP:AF:ID  0.00303301:0.00193001:0.920819:0.869162:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86926  ES:SE:LP:AF:ID  0.00306128:0.00193077:0.958607:0.86926:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  -0.00489733:0.00349195:0.79588:0.037535:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869164 ES:SE:LP:AF:ID  0.0030653:0.00192997:0.958607:0.869164:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00512  ES:SE:LP:AF:ID  0.00202336:0.00991006:0.0757207:0.00512:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  0.00184465:0.00993567:0.0705811:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838068 ES:SE:LP:AF:ID  0.0031549:0.00179709:1.10237:0.838068:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037548 ES:SE:LP:AF:ID  -0.00482695:0.00349688:0.769551:0.037548:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.8387   ES:SE:LP:AF:ID  0.00320541:0.00180215:1.12494:0.8387:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01377  ES:SE:LP:AF:ID  0.0223813:0.00629098:3.4318:0.01377:rs181660517