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-8121/UKB-b-8121_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8121/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:21 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8121/UKB-b-8121_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: 0.0788 (0.0032)
Lambda GC: 1.571
Mean Chi^2: 1.7881
Intercept: 1.0661 (0.0101)
Ratio: 0.0839 (0.0128)
Analysis finished at Thu Oct 17 14:43:02 2019
Total time elapsed: 1.0m:40.75s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.369,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 106,
    "n_p_sig": 9322,
    "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": 0.0788,
    "ldsc_observed_scale_h2_se": 0.0032,
    "ldsc_intercept_beta": 1.0661,
    "ldsc_intercept_se": 0.0101,
    "ldsc_lambda_gc": 1.571,
    "ldsc_mean_chisq": 1.7881,
    "ldsc_ratio": 0.0839
}

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 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 1.467000e-04 8.944000e-03 -0.2977880 -2.979900e-03 5.400000e-05 3.097500e-03 1.538230e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.074400e-03 5.749500e-03 0.0017002 2.080900e-03 3.489400e-03 8.051200e-03 8.934520e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.465451e-01 3.027415e-01 0.0000000 1.700000e-01 4.299995e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.465469e-01 3.027177e-01 0.0000000 1.707044e-01 4.267709e-01 7.082905e-01 9.999998e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035076e-01 2.568616e-01 0.0009940 1.316900e-02 7.791300e-02 3.164550e-01 9.990030e-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 -0.0004971 0.0031266 0.8700001 0.8736636 0.623769 0.7821490 NA
1 54676 rs2462492 C T 0.0041172 0.0030973 0.1800002 0.1837601 0.400406 NA NA
1 86028 rs114608975 T C -0.0079619 0.0049523 0.1100001 0.1078952 0.103551 0.0277556 NA
1 91536 rs6702460 G T 0.0011472 0.0030498 0.7099994 0.7068007 0.456859 0.4207270 NA
1 234313 rs8179466 C T 0.0029226 0.0060132 0.6300007 0.6269430 0.074509 NA NA
1 534192 rs6680723 C T 0.0057227 0.0034838 0.1000000 0.1004479 0.240958 NA NA
1 546697 rs12025928 A G -0.0009318 0.0043457 0.8300000 0.8302194 0.913469 NA NA
1 693731 rs12238997 A G -0.0035829 0.0029192 0.2200002 0.2196917 0.116340 0.1417730 NA
1 705882 rs72631875 G A -0.0075894 0.0042780 0.0759994 0.0760521 0.067284 0.0315495 NA
1 706368 rs55727773 A G -0.0029020 0.0021626 0.1800002 0.1796209 0.515644 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0002752 0.0045436 0.9500000 0.9517046 0.041947 0.0473243 NA
22 51219766 rs182321900 C T -0.0148941 0.0211888 0.4799997 0.4821036 0.001933 NA NA
22 51220146 rs868950473 C T -0.0149831 0.0209861 0.4799997 0.4752559 0.001983 NA NA
22 51221190 rs369304721 G A -0.0000667 0.0045361 0.9900000 0.9882616 0.049722 NA NA
22 51221731 rs115055839 T C -0.0018842 0.0033928 0.5800000 0.5786594 0.073223 0.0625000 NA
22 51222100 rs114553188 G T -0.0048895 0.0039937 0.2200002 0.2208332 0.054466 0.0880591 NA
22 51223637 rs375798137 G A -0.0048889 0.0040130 0.2200002 0.2231200 0.054095 0.0788738 NA
22 51229805 rs9616985 T C -0.0021065 0.0034051 0.5400003 0.5361586 0.073058 0.0730831 NA
22 51232488 rs376461333 A G -0.0051623 0.0080204 0.5199996 0.5198062 0.020044 NA NA
22 51237063 rs3896457 T C -0.0007612 0.0020824 0.7099994 0.7147294 0.297965 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623769 ES:SE:LP:AF:ID  -0.000497147:0.00312658:0.0604807:0.623769:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  0.00411715:0.00309731:0.744727:0.400406:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103551 ES:SE:LP:AF:ID  -0.00796191:0.00495228:0.958607:0.103551:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  0.00114719:0.00304977:0.148742:0.456859:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074509 ES:SE:LP:AF:ID  0.00292262:0.0060132:0.200659:0.074509:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240958 ES:SE:LP:AF:ID  0.00572274:0.00348377:1:0.240958:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913469 ES:SE:LP:AF:ID  -0.000931795:0.00434565:0.0809219:0.913469:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11634  ES:SE:LP:AF:ID  -0.0035829:0.00291922:0.657577:0.11634:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067284 ES:SE:LP:AF:ID  -0.00758944:0.00427799:1.11919:0.067284:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515644 ES:SE:LP:AF:ID  -0.00290203:0.00216259:0.744727:0.515644:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033002 ES:SE:LP:AF:ID  -0.00218259:0.00545212:0.161151:0.033002:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036617 ES:SE:LP:AF:ID  -0.00228632:0.00495234:0.19382:0.036617:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036734 ES:SE:LP:AF:ID  -0.00241203:0.00493361:0.207608:0.036734:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036433 ES:SE:LP:AF:ID  -0.00235212:0.00496921:0.19382:0.036433:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016407 ES:SE:LP:AF:ID  -0.00769262:0.007651:0.508638:0.016407:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036972 ES:SE:LP:AF:ID  -0.00220702:0.00491409:0.187087:0.036972:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037068 ES:SE:LP:AF:ID  -0.00268094:0.00489731:0.236572:0.037068:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10121  ES:SE:LP:AF:ID  0.00355228:0.00356769:0.49485:0.10121:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959102 ES:SE:LP:AF:ID  0.00290786:0.00472356:0.267606:0.959102:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  5.55062e-05:0.00857465:0.00436481:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  0.0135466:0.00681984:1.3279:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036587 ES:SE:LP:AF:ID  -0.00225759:0.00492893:0.187087:0.036587:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036903 ES:SE:LP:AF:ID  -0.0021538:0.00488411:0.180456:0.036903:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843206 ES:SE:LP:AF:ID  0.00290502:0.00253006:0.60206:0.843206:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055923 ES:SE:LP:AF:ID  -1.67215e-05:0.00409608:-0:0.055923:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122319 ES:SE:LP:AF:ID  -0.00334205:0.00276922:0.638272:0.122319:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025713 ES:SE:LP:AF:ID  -0.00827652:0.00681173:0.657577:0.025713:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121562 ES:SE:LP:AF:ID  -0.00306453:0.00277039:0.568636:0.121562:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13234  ES:SE:LP:AF:ID  -0.00144626:0.00273057:0.221849:0.13234:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  -0.0100703:0.0099293:0.508638:0.011132:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.0057   ES:SE:LP:AF:ID  -0.0104831:0.0128157:0.387216:0.0057:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002269 ES:SE:LP:AF:ID  -0.00458149:0.021555:0.0809219:0.002269:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001029 ES:SE:LP:AF:ID  0.0487576:0.035311:0.769551:0.001029:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036818 ES:SE:LP:AF:ID  -0.00122072:0.00483475:0.09691:0.036818:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838942 ES:SE:LP:AF:ID  0.00303736:0.00245017:0.657577:0.838942:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83857  ES:SE:LP:AF:ID  0.00305459:0.00244753:0.677781:0.83857:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869767 ES:SE:LP:AF:ID  0.00290397:0.00262626:0.568636:0.869767:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129884 ES:SE:LP:AF:ID  -0.00275339:0.00263161:0.522879:0.129884:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037328 ES:SE:LP:AF:ID  -0.00186641:0.00475282:0.161151:0.037328:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037572 ES:SE:LP:AF:ID  -0.00194404:0.00472279:0.167491:0.037572:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869109 ES:SE:LP:AF:ID  0.00284797:0.00262111:0.552842:0.869109:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869207 ES:SE:LP:AF:ID  0.00280908:0.00262215:0.552842:0.869207:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  -0.00182239:0.00474323:0.154902:0.03753:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  0.00289185:0.00262106:0.568636:0.869112:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005124 ES:SE:LP:AF:ID  0.00143968:0.0134557:0.0409586:0.005124:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509  ES:SE:LP:AF:ID  0.0008811:0.013491:0.0222764:0.00509:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838023 ES:SE:LP:AF:ID  0.00293695:0.00244073:0.638272:0.838023:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037542 ES:SE:LP:AF:ID  -0.00194448:0.00474992:0.167491:0.037542:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838654 ES:SE:LP:AF:ID  0.00302701:0.00244759:0.657577:0.838654:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  0.0113809:0.00854298:0.744727:0.013775:rs181660517