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-2209/UKB-b-2209_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2209/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:20 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2209/UKB-b-2209_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: 0.0615 (0.0028)
Lambda GC: 1.4522
Mean Chi^2: 1.6113
Intercept: 1.0389 (0.0098)
Ratio: 0.0637 (0.0161)
Analysis finished at Thu Oct 17 14:44:07 2019
Total time elapsed: 1.0m:46.84s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 63,
    "n_p_sig": 10383,
    "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": 0.0615,
    "ldsc_observed_scale_h2_se": 0.0028,
    "ldsc_intercept_beta": 1.0389,
    "ldsc_intercept_se": 0.0098,
    "ldsc_lambda_gc": 1.4522,
    "ldsc_mean_chisq": 1.6113,
    "ldsc_ratio": 0.0636
}

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 -2.040000e-05 9.533400e-03 -0.1274620 -3.216800e-03 -3.090000e-05 3.168700e-03 1.397590e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.592000e-03 6.240000e-03 0.0018446 2.258000e-03 3.786500e-03 8.736800e-03 9.692920e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.551436e-01 3.008014e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.551467e-01 3.007784e-01 0.0000000 1.831577e-01 4.395339e-01 7.151553e-01 9.999997e-01 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035075e-01 2.568622e-01 0.0009880 1.316900e-02 7.791200e-02 3.164600e-01 9.990070e-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 0.0008651 0.0033932 0.8000000 0.7987546 0.623736 0.7821490 NA
1 54676 rs2462492 C T -0.0039698 0.0033611 0.2399999 0.2375704 0.400446 NA NA
1 86028 rs114608975 T C 0.0052208 0.0053753 0.3300000 0.3314220 0.103546 0.0277556 NA
1 91536 rs6702460 G T -0.0049957 0.0033098 0.1299999 0.1312099 0.456900 0.4207270 NA
1 234313 rs8179466 C T -0.0137617 0.0065252 0.0350002 0.0349442 0.074517 NA NA
1 534192 rs6680723 C T 0.0008625 0.0037809 0.8200001 0.8195604 0.240962 NA NA
1 546697 rs12025928 A G -0.0026602 0.0047168 0.5700002 0.5727746 0.913485 NA NA
1 693731 rs12238997 A G 0.0037050 0.0031678 0.2399999 0.2421777 0.116361 0.1417730 NA
1 705882 rs72631875 G A 0.0014786 0.0046436 0.7499995 0.7501780 0.067259 0.0315495 NA
1 706368 rs55727773 A G -0.0019202 0.0023471 0.4100001 0.4132972 0.515610 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0088453 0.0049298 0.0729995 0.0727738 0.041935 0.0473243 NA
22 51219766 rs182321900 C T 0.0588179 0.0229796 0.0100000 0.0104802 0.001934 NA NA
22 51220146 rs868950473 C T 0.0548497 0.0227600 0.0160000 0.0159562 0.001983 NA NA
22 51221190 rs369304721 G A 0.0090550 0.0049216 0.0659994 0.0657930 0.049705 NA NA
22 51221731 rs115055839 T C 0.0051787 0.0036816 0.1600000 0.1595419 0.073184 0.0625000 NA
22 51222100 rs114553188 G T -0.0082683 0.0043336 0.0560003 0.0563980 0.054442 0.0880591 NA
22 51223637 rs375798137 G A -0.0082436 0.0043546 0.0580003 0.0583483 0.054071 0.0788738 NA
22 51229805 rs9616985 T C 0.0050647 0.0036948 0.1700000 0.1704515 0.073023 0.0730831 NA
22 51232488 rs376461333 A G -0.0054567 0.0087009 0.5300002 0.5305658 0.020040 NA NA
22 51237063 rs3896457 T C 0.0025741 0.0022591 0.2500000 0.2545248 0.298014 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623736 ES:SE:LP:AF:ID  0.00086512:0.00339317:0.09691:0.623736:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400446 ES:SE:LP:AF:ID  -0.00396978:0.00336114:0.619789:0.400446:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103546 ES:SE:LP:AF:ID  0.00522075:0.00537527:0.481486:0.103546:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.4569   ES:SE:LP:AF:ID  -0.00499567:0.00330982:0.886057:0.4569:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074517 ES:SE:LP:AF:ID  -0.0137617:0.00652521:1.45593:0.074517:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240962 ES:SE:LP:AF:ID  0.000862458:0.00378088:0.0861861:0.240962:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913485 ES:SE:LP:AF:ID  -0.00266015:0.00471683:0.244125:0.913485:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116361 ES:SE:LP:AF:ID  0.00370497:0.00316783:0.619789:0.116361:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067259 ES:SE:LP:AF:ID  0.00147855:0.00464362:0.124939:0.067259:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51561  ES:SE:LP:AF:ID  -0.00192015:0.00234707:0.387216:0.51561:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033014 ES:SE:LP:AF:ID  0.00683992:0.0059161:0.60206:0.033014:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036634 ES:SE:LP:AF:ID  0.00792324:0.00537346:0.853872:0.036634:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03675  ES:SE:LP:AF:ID  0.00815602:0.00535322:0.886057:0.03675:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036449 ES:SE:LP:AF:ID  0.00836803:0.00539178:0.920819:0.036449:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016407 ES:SE:LP:AF:ID  0.00816914:0.00830351:0.481486:0.016407:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03699  ES:SE:LP:AF:ID  0.00780608:0.00533185:0.853872:0.03699:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037087 ES:SE:LP:AF:ID  0.00739332:0.00531361:0.79588:0.037087:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101199 ES:SE:LP:AF:ID  -0.00425201:0.00387215:0.568636:0.101199:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959089 ES:SE:LP:AF:ID  -0.0107317:0.00512533:1.4437:0.959089:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031442 ES:SE:LP:AF:ID  0.00210942:0.00930909:0.0861861:0.031442:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053269 ES:SE:LP:AF:ID  -0.00396105:0.00739876:0.229148:0.053269:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036605 ES:SE:LP:AF:ID  0.00766901:0.00534804:0.823909:0.036605:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036919 ES:SE:LP:AF:ID  0.00699133:0.00529943:0.721246:0.036919:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843172 ES:SE:LP:AF:ID  -0.00566735:0.00274545:1.40894:0.843172:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055934 ES:SE:LP:AF:ID  0.000298488:0.00444487:0.0222764:0.055934:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122346 ES:SE:LP:AF:ID  0.00423345:0.00300503:0.79588:0.122346:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025709 ES:SE:LP:AF:ID  -0.0032817:0.00739478:0.180456:0.025709:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121588 ES:SE:LP:AF:ID  0.00450437:0.00300631:0.886057:0.121588:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132379 ES:SE:LP:AF:ID  0.00426499:0.00296304:0.823909:0.132379:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011127 ES:SE:LP:AF:ID  0.0103855:0.0107789:0.468521:0.011127:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005701 ES:SE:LP:AF:ID  0.00327366:0.013907:0.091515:0.005701:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002264 ES:SE:LP:AF:ID  0.0529965:0.0234151:1.61979:0.002264:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001026 ES:SE:LP:AF:ID  0.0977182:0.0383782:1.95861:0.001026:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036835 ES:SE:LP:AF:ID  0.00815356:0.00524588:0.920819:0.036835:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838906 ES:SE:LP:AF:ID  -0.00582432:0.00265876:1.55284:0.838906:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838533 ES:SE:LP:AF:ID  -0.00610748:0.00265589:1.67778:0.838533:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869744 ES:SE:LP:AF:ID  -0.00540029:0.00284994:1.23657:0.869744:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129906 ES:SE:LP:AF:ID  0.00528641:0.00285575:1.19382:0.129906:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037346 ES:SE:LP:AF:ID  0.00798218:0.00515695:0.920819:0.037346:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037589 ES:SE:LP:AF:ID  0.00805939:0.00512442:0.920819:0.037589:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869085 ES:SE:LP:AF:ID  -0.00572686:0.00284434:1.35655:0.869085:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869184 ES:SE:LP:AF:ID  -0.00566199:0.00284548:1.3279:0.869184:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037547 ES:SE:LP:AF:ID  0.00783805:0.00514661:0.886057:0.037547:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869088 ES:SE:LP:AF:ID  -0.00576651:0.00284429:1.36653:0.869088:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005124 ES:SE:LP:AF:ID  0.0342933:0.0146035:1.72125:0.005124:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509  ES:SE:LP:AF:ID  0.0340895:0.0146418:1.69897:0.00509:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837988 ES:SE:LP:AF:ID  -0.00583166:0.00264853:1.55284:0.837988:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03756  ES:SE:LP:AF:ID  0.00777403:0.00515389:0.886057:0.03756:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838619 ES:SE:LP:AF:ID  -0.00566322:0.00265598:1.48149:0.838619:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01376  ES:SE:LP:AF:ID  -0.00222232:0.00927715:0.091515:0.01376:rs181660517