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-3822/UKB-b-3822_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3822/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:47 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3822/UKB-b-3822_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: 0.0425 (0.0023)
Lambda GC: 1.3384
Mean Chi^2: 1.4116
Intercept: 1.0387 (0.0083)
Ratio: 0.094 (0.0201)
Analysis finished at Thu Oct 17 14:45:38 2019
Total time elapsed: 1.0m:51.58s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 14,
    "n_p_sig": 1049,
    "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": 0.0425,
    "ldsc_observed_scale_h2_se": 0.0023,
    "ldsc_intercept_beta": 1.0387,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.3384,
    "ldsc_mean_chisq": 1.4116,
    "ldsc_ratio": 0.094
}

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 2.147000e-04 6.517700e-03 -0.0885811 -1.999700e-03 5.140000e-05 2.164800e-03 1.224440e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.471700e-03 4.234700e-03 0.0012510 1.531400e-03 2.568000e-03 5.925400e-03 6.575000e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.648159e-01 2.982259e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.648172e-01 2.982014e-01 0.0000000 1.977370e-01 4.526845e-01 7.230706e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035069e-01 2.568648e-01 0.0009710 1.316800e-02 7.791250e-02 3.164630e-01 9.990300e-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 0.0017247 0.0023019 0.4500005 0.4537120 0.623825 0.7821490 NA
1 54676 rs2462492 C T -0.0025738 0.0022798 0.2599998 0.2589141 0.400352 NA NA
1 86028 rs114608975 T C -0.0015472 0.0036461 0.6700003 0.6713168 0.103538 0.0277556 NA
1 91536 rs6702460 G T 0.0021261 0.0022446 0.3400001 0.3435352 0.456853 0.4207270 NA
1 234313 rs8179466 C T -0.0020578 0.0044242 0.6400000 0.6418438 0.074510 NA NA
1 534192 rs6680723 C T 0.0020241 0.0025645 0.4299995 0.4299477 0.240955 NA NA
1 546697 rs12025928 A G 0.0008117 0.0031988 0.8000000 0.7996742 0.913427 NA NA
1 693731 rs12238997 A G 0.0046713 0.0021494 0.0299999 0.0297574 0.116300 0.1417730 NA
1 705882 rs72631875 G A 0.0018066 0.0031489 0.5700002 0.5661388 0.067293 0.0315495 NA
1 706368 rs55727773 A G -0.0053324 0.0015917 0.0008100 0.0008076 0.515714 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0002329 0.0033434 0.9400001 0.9444764 0.041904 0.0473243 NA
22 51219766 rs182321900 C T -0.0107208 0.0156838 0.4899999 0.4942538 0.001913 NA NA
22 51220146 rs868950473 C T -0.0094968 0.0155365 0.5400003 0.5410305 0.001962 NA NA
22 51221190 rs369304721 G A -0.0008020 0.0033373 0.8100000 0.8100786 0.049684 NA NA
22 51221731 rs115055839 T C -0.0009077 0.0024960 0.7199992 0.7161016 0.073154 0.0625000 NA
22 51222100 rs114553188 G T -0.0031592 0.0029392 0.2800000 0.2824467 0.054411 0.0880591 NA
22 51223637 rs375798137 G A -0.0031383 0.0029534 0.2900000 0.2879480 0.054045 0.0788738 NA
22 51229805 rs9616985 T C -0.0007401 0.0025050 0.7700005 0.7676597 0.072991 0.0730831 NA
22 51232488 rs376461333 A G -0.0080129 0.0059025 0.1700000 0.1746137 0.020025 NA NA
22 51237063 rs3896457 T C 0.0008056 0.0015313 0.5999997 0.5988443 0.297987 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623825 ES:SE:LP:AF:ID  0.0017247:0.00230193:0.346787:0.623825:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400352 ES:SE:LP:AF:ID  -0.00257375:0.00227975:0.585027:0.400352:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103538 ES:SE:LP:AF:ID  -0.0015472:0.00364612:0.173925:0.103538:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456853 ES:SE:LP:AF:ID  0.00212614:0.00224465:0.468521:0.456853:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07451  ES:SE:LP:AF:ID  -0.00205779:0.00442419:0.19382:0.07451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240955 ES:SE:LP:AF:ID  0.00202408:0.00256446:0.366532:0.240955:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913427 ES:SE:LP:AF:ID  0.000811748:0.00319877:0.09691:0.913427:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.1163   ES:SE:LP:AF:ID  0.00467128:0.00214939:1.52288:0.1163:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067293 ES:SE:LP:AF:ID  0.00180665:0.00314886:0.244125:0.067293:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515714 ES:SE:LP:AF:ID  -0.00533236:0.00159167:3.09152:0.515714:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032997 ES:SE:LP:AF:ID  0.000174432:0.00401322:0.0132283:0.032997:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036611 ES:SE:LP:AF:ID  4.44896e-05:0.00364544:0.00436481:0.036611:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036726 ES:SE:LP:AF:ID  0.000495979:0.00363172:0.05061:0.036726:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036423 ES:SE:LP:AF:ID  0.000880084:0.00365815:0.091515:0.036423:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016422 ES:SE:LP:AF:ID  0.0184511:0.00562999:3:0.016422:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036964 ES:SE:LP:AF:ID  0.000697122:0.0036175:0.0705811:0.036964:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037056 ES:SE:LP:AF:ID  0.000616626:0.00360546:0.0655015:0.037056:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101209 ES:SE:LP:AF:ID  5.03176e-06:0.00262549:-0:0.101209:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959118 ES:SE:LP:AF:ID  -0.00019828:0.00347748:0.0222764:0.959118:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  0.00111921:0.00630977:0.0655015:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.0103088:0.00502042:1.39794:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036578 ES:SE:LP:AF:ID  0.000659718:0.00362854:0.0655015:0.036578:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036893 ES:SE:LP:AF:ID  0.000232563:0.00359551:0.0222764:0.036893:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843284 ES:SE:LP:AF:ID  -0.00380843:0.00186302:1.38722:0.843284:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055935 ES:SE:LP:AF:ID  0.00516603:0.00301437:1.06048:0.055935:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122249 ES:SE:LP:AF:ID  0.00431966:0.00203928:1.46852:0.122249:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02569  ES:SE:LP:AF:ID  -0.00161755:0.00501676:0.124939:0.02569:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12149  ES:SE:LP:AF:ID  0.00436637:0.0020401:1.49485:0.12149:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132281 ES:SE:LP:AF:ID  0.00162955:0.00201051:0.376751:0.132281:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011108 ES:SE:LP:AF:ID  -0.00366433:0.00731606:0.207608:0.011108:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005714 ES:SE:LP:AF:ID  -0.00222149:0.00942252:0.091515:0.005714:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002256 ES:SE:LP:AF:ID  0.0212899:0.0159135:0.744727:0.002256:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001026 ES:SE:LP:AF:ID  0.00576899:0.0260305:0.0861861:0.001026:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036794 ES:SE:LP:AF:ID  0.000220601:0.00356002:0.0222764:0.036794:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83904  ES:SE:LP:AF:ID  -0.00387771:0.0018043:1.49485:0.83904:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838669 ES:SE:LP:AF:ID  -0.0037033:0.00180236:1.39794:0.838669:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86987  ES:SE:LP:AF:ID  -0.004457:0.00193426:1.67778:0.86987:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129771 ES:SE:LP:AF:ID  0.0040713:0.00193828:1.4437:0.129771:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037301 ES:SE:LP:AF:ID  0.000582229:0.00349985:0.0604807:0.037301:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037543 ES:SE:LP:AF:ID  0.000550082:0.0034778:0.0604807:0.037543:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869217 ES:SE:LP:AF:ID  -0.00434934:0.00193049:1.61979:0.869217:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869318 ES:SE:LP:AF:ID  -0.00427737:0.00193129:1.56864:0.869318:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037506 ES:SE:LP:AF:ID  0.000627149:0.00349272:0.0655015:0.037506:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869217 ES:SE:LP:AF:ID  -0.00432684:0.00193043:1.60206:0.869217:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005111 ES:SE:LP:AF:ID  -0.00356095:0.00991924:0.142668:0.005111:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005077 ES:SE:LP:AF:ID  -0.00346837:0.00994547:0.136677:0.005077:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838128 ES:SE:LP:AF:ID  -0.00377991:0.0017974:1.45593:0.838128:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037522 ES:SE:LP:AF:ID  0.000510963:0.00349755:0.0555173:0.037522:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838756 ES:SE:LP:AF:ID  -0.00385158:0.00180246:1.48149:0.838756:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013802 ES:SE:LP:AF:ID  -0.00293475:0.00628175:0.19382:0.013802:rs181660517