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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}

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-20498/UKB-b-20498_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20498/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20498/UKB-b-20498_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: 0.0516 (0.0024)
Lambda GC: 1.398
Mean Chi^2: 1.4883
Intercept: 1.0249 (0.01)
Ratio: 0.051 (0.0204)
Analysis finished at Thu Oct 17 14:43:57 2019
Total time elapsed: 1.0m:47.88s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 33,
    "n_p_sig": 1810,
    "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": 0.0516,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0249,
    "ldsc_intercept_se": 0.01,
    "ldsc_lambda_gc": 1.398,
    "ldsc_mean_chisq": 1.4883,
    "ldsc_ratio": 0.051
}

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 6.320000e-05 1.009560e-02 -0.1472520 -3.286400e-03 2.680000e-05 3.346400e-03 2.307100e-01 ▁▇▂▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.013800e-03 6.638500e-03 0.0019628 2.402700e-03 4.029000e-03 9.296500e-03 1.031730e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.609659e-01 2.990969e-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 4.609666e-01 2.990706e-01 0.0000000 1.927250e-01 4.466619e-01 7.199809e-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 7.791500e-02 3.164560e-01 9.990040e-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 -0.0034471 0.0036110 0.3400001 0.3397716 0.623765 0.7821490 NA
1 54676 rs2462492 C T -0.0005437 0.0035774 0.8800001 0.8792066 0.400420 NA NA
1 86028 rs114608975 T C 0.0042234 0.0057198 0.4600002 0.4602863 0.103552 0.0277556 NA
1 91536 rs6702460 G T -0.0064792 0.0035224 0.0659994 0.0658531 0.456858 0.4207270 NA
1 234313 rs8179466 C T 0.0057781 0.0069447 0.4100001 0.4054002 0.074512 NA NA
1 534192 rs6680723 C T -0.0004741 0.0040238 0.9100000 0.9062126 0.240953 NA NA
1 546697 rs12025928 A G -0.0029636 0.0050198 0.5500004 0.5549383 0.913478 NA NA
1 693731 rs12238997 A G 0.0019788 0.0033716 0.5600000 0.5572665 0.116327 0.1417730 NA
1 705882 rs72631875 G A 0.0043468 0.0049412 0.3800004 0.3790161 0.067283 0.0315495 NA
1 706368 rs55727773 A G 0.0023702 0.0024977 0.3400001 0.3426367 0.515623 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0006366 0.0052438 0.9000000 0.9033791 0.041946 0.0473243 NA
22 51219766 rs182321900 C T 0.0185765 0.0244408 0.4500005 0.4472181 0.001935 NA NA
22 51220146 rs868950473 C T 0.0198975 0.0242071 0.4100001 0.4110942 0.001984 NA NA
22 51221190 rs369304721 G A -0.0008589 0.0052353 0.8700001 0.8696819 0.049721 NA NA
22 51221731 rs115055839 T C -0.0018228 0.0039157 0.6400000 0.6415697 0.073221 0.0625000 NA
22 51222100 rs114553188 G T -0.0009866 0.0046091 0.8300000 0.8305089 0.054462 0.0880591 NA
22 51223637 rs375798137 G A -0.0011436 0.0046315 0.8000000 0.8049735 0.054090 0.0788738 NA
22 51229805 rs9616985 T C -0.0017039 0.0039298 0.6600001 0.6645887 0.073056 0.0730831 NA
22 51232488 rs376461333 A G 0.0025252 0.0092559 0.7800007 0.7849905 0.020046 NA NA
22 51237063 rs3896457 T C 0.0019370 0.0024033 0.4199997 0.4202471 0.297962 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  -0.00344714:0.00361102:0.468521:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40042  ES:SE:LP:AF:ID  -0.000543677:0.00357741:0.0555173:0.40042:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103552 ES:SE:LP:AF:ID  0.00422339:0.00571984:0.337242:0.103552:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456858 ES:SE:LP:AF:ID  -0.00647918:0.0035224:1.18046:0.456858:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074512 ES:SE:LP:AF:ID  0.00577809:0.00694469:0.387216:0.074512:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240953 ES:SE:LP:AF:ID  -0.000474071:0.00402379:0.0409586:0.240953:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913478 ES:SE:LP:AF:ID  -0.00296356:0.00501978:0.259637:0.913478:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116327 ES:SE:LP:AF:ID  0.00197882:0.00337161:0.251812:0.116327:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067283 ES:SE:LP:AF:ID  0.0043468:0.00494117:0.420216:0.067283:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515623 ES:SE:LP:AF:ID  0.00237021:0.00249767:0.468521:0.515623:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032992 ES:SE:LP:AF:ID  0.00285772:0.00629799:0.187087:0.032992:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036607 ES:SE:LP:AF:ID  0.00265021:0.00572066:0.19382:0.036607:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  0.00276396:0.00569902:0.200659:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036422 ES:SE:LP:AF:ID  0.0030296:0.00574007:0.221849:0.036422:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016398 ES:SE:LP:AF:ID  0.0166723:0.00883958:1.22915:0.016398:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036962 ES:SE:LP:AF:ID  0.00294501:0.00567647:0.221849:0.036962:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037058 ES:SE:LP:AF:ID  0.00248677:0.00565702:0.180456:0.037058:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101227 ES:SE:LP:AF:ID  -0.00656645:0.00412029:0.958607:0.101227:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959111 ES:SE:LP:AF:ID  -0.00321881:0.00545615:0.251812:0.959111:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03145  ES:SE:LP:AF:ID  -0.0102924:0.00990209:0.522879:0.03145:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053266 ES:SE:LP:AF:ID  0.00488613:0.00787586:0.275724:0.053266:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036577 ES:SE:LP:AF:ID  0.00258315:0.00569358:0.187087:0.036577:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036893 ES:SE:LP:AF:ID  0.00280457:0.00564176:0.207608:0.036893:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843228 ES:SE:LP:AF:ID  -0.00143405:0.00292217:0.207608:0.843228:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055921 ES:SE:LP:AF:ID  -0.00583228:0.00473085:0.657577:0.055921:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122305 ES:SE:LP:AF:ID  0.000955109:0.00319834:0.113509:0.122305:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025712 ES:SE:LP:AF:ID  0.00804666:0.00786725:0.508638:0.025712:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  0.000914507:0.00319968:0.107905:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132322 ES:SE:LP:AF:ID  -0.000782624:0.00315381:0.09691:0.132322:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011138 ES:SE:LP:AF:ID  -0.0092644:0.0114643:0.376751:0.011138:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005701 ES:SE:LP:AF:ID  0.0174203:0.0148009:0.619789:0.005701:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002269 ES:SE:LP:AF:ID  0.0637626:0.0248904:2:0.002269:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.00103  ES:SE:LP:AF:ID  -0.0106776:0.0407562:0.102373:0.00103:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036807 ES:SE:LP:AF:ID  0.0023484:0.00558477:0.173925:0.036807:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838966 ES:SE:LP:AF:ID  -0.00261927:0.00282995:0.455932:0.838966:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838594 ES:SE:LP:AF:ID  -0.0026081:0.0028269:0.443698:0.838594:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  -0.00300195:0.0030333:0.49485:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12987  ES:SE:LP:AF:ID  0.00245785:0.00303945:0.376751:0.12987:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037318 ES:SE:LP:AF:ID  0.00241171:0.00549006:0.180456:0.037318:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037562 ES:SE:LP:AF:ID  0.00253806:0.00545536:0.19382:0.037562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  -0.00302373:0.00302735:0.49485:0.869123:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86922  ES:SE:LP:AF:ID  -0.00329016:0.00302855:0.552842:0.86922:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03752  ES:SE:LP:AF:ID  0.00263102:0.00547897:0.200659:0.03752:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869125 ES:SE:LP:AF:ID  -0.00302556:0.00302729:0.49485:0.869125:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005125 ES:SE:LP:AF:ID  0.00341183:0.0155381:0.0809219:0.005125:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005091 ES:SE:LP:AF:ID  0.00367189:0.0155789:0.091515:0.005091:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838046 ES:SE:LP:AF:ID  -0.00276453:0.00281904:0.481486:0.838046:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037532 ES:SE:LP:AF:ID  0.00282414:0.00548669:0.21467:0.037532:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838677 ES:SE:LP:AF:ID  -0.00281541:0.00282697:0.49485:0.838677:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01378  ES:SE:LP:AF:ID  0.0106607:0.00986492:0.552842:0.01378:rs181660517