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-13823/UKB-b-13823_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13823/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:56 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13823/UKB-b-13823_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: 0.079 (0.0029)
Lambda GC: 1.5682
Mean Chi^2: 1.747
Intercept: 1.0441 (0.0111)
Ratio: 0.0591 (0.0148)
Analysis finished at Thu Oct 17 14:44:45 2019
Total time elapsed: 1.0m:48.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.369,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 81,
    "n_p_sig": 10251,
    "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": 0.079,
    "ldsc_observed_scale_h2_se": 0.0029,
    "ldsc_intercept_beta": 1.0441,
    "ldsc_intercept_se": 0.0111,
    "ldsc_lambda_gc": 1.5682,
    "ldsc_mean_chisq": 1.747,
    "ldsc_ratio": 0.059
}

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 9.560000e-05 1.035820e-02 -0.1431900 -3.498400e-03 4.980000e-05 3.608200e-03 1.708160e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.100400e-03 6.725600e-03 0.0019868 2.431400e-03 4.077400e-03 9.408200e-03 1.041990e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.473213e-01 3.026523e-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 4.473214e-01 3.026277e-01 0.0000000 1.720167e-01 4.279646e-01 7.091339e-01 9.999999e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035068e-01 2.568657e-01 0.0009730 1.316700e-02 7.790900e-02 3.164530e-01 9.990200e-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 -0.0053426 0.0036528 0.1400000 0.1435773 0.623766 0.7821490 NA
1 54676 rs2462492 C T -0.0005865 0.0036190 0.8700001 0.8712628 0.400418 NA NA
1 86028 rs114608975 T C 0.0070337 0.0057856 0.2200002 0.2240910 0.103560 0.0277556 NA
1 91536 rs6702460 G T -0.0087328 0.0035635 0.0140001 0.0142614 0.456845 0.4207270 NA
1 234313 rs8179466 C T -0.0021066 0.0070214 0.7600007 0.7641627 0.074555 NA NA
1 534192 rs6680723 C T 0.0041778 0.0040715 0.2999998 0.3048382 0.240994 NA NA
1 546697 rs12025928 A G -0.0058338 0.0050794 0.2500000 0.2507563 0.913519 NA NA
1 693731 rs12238997 A G -0.0005186 0.0034093 0.8800001 0.8790919 0.116430 0.1417730 NA
1 705882 rs72631875 G A 0.0055474 0.0049999 0.2700001 0.2672145 0.067249 0.0315495 NA
1 706368 rs55727773 A G 0.0029114 0.0025269 0.2500000 0.2492533 0.515578 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0066428 0.0053127 0.2099999 0.2111655 0.041874 0.0473243 NA
22 51219766 rs182321900 C T 0.0364570 0.0248282 0.1400000 0.1420036 0.001922 NA NA
22 51220146 rs868950473 C T 0.0392621 0.0245862 0.1100001 0.1102844 0.001971 NA NA
22 51221190 rs369304721 G A 0.0017785 0.0053031 0.7400005 0.7373508 0.049654 NA NA
22 51221731 rs115055839 T C -0.0002795 0.0039662 0.9400001 0.9438144 0.073137 0.0625000 NA
22 51222100 rs114553188 G T -0.0001239 0.0046653 0.9800000 0.9788050 0.054463 0.0880591 NA
22 51223637 rs375798137 G A -0.0002277 0.0046878 0.9599999 0.9612520 0.054093 0.0788738 NA
22 51229805 rs9616985 T C -0.0002540 0.0039804 0.9500000 0.9491238 0.072977 0.0730831 NA
22 51232488 rs376461333 A G 0.0009502 0.0093727 0.9199999 0.9192475 0.020026 NA NA
22 51237063 rs3896457 T C 0.0049594 0.0024327 0.0409996 0.0414897 0.298047 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623766 ES:SE:LP:AF:ID  -0.00534255:0.00365278:0.853872:0.623766:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400418 ES:SE:LP:AF:ID  -0.000586471:0.00361897:0.0604807:0.400418:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10356  ES:SE:LP:AF:ID  0.00703374:0.00578565:0.657577:0.10356:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456845 ES:SE:LP:AF:ID  -0.0087328:0.00356352:1.85387:0.456845:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074555 ES:SE:LP:AF:ID  -0.00210655:0.00702139:0.119186:0.074555:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240994 ES:SE:LP:AF:ID  0.00417782:0.0040715:0.522879:0.240994:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913519 ES:SE:LP:AF:ID  -0.00583381:0.00507944:0.60206:0.913519:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11643  ES:SE:LP:AF:ID  -0.000518626:0.00340931:0.0555173:0.11643:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067249 ES:SE:LP:AF:ID  0.00554739:0.0049999:0.568636:0.067249:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515578 ES:SE:LP:AF:ID  0.00291144:0.00252693:0.60206:0.515578:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032965 ES:SE:LP:AF:ID  0.00336538:0.00637402:0.221849:0.032965:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036574 ES:SE:LP:AF:ID  0.00242376:0.00578975:0.167491:0.036574:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036689 ES:SE:LP:AF:ID  0.00189225:0.00576787:0.130768:0.036689:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036388 ES:SE:LP:AF:ID  0.00231961:0.00580951:0.161151:0.036388:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016421 ES:SE:LP:AF:ID  0.0114226:0.00893488:0.69897:0.016421:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036926 ES:SE:LP:AF:ID  0.00226306:0.00574519:0.161151:0.036926:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037024 ES:SE:LP:AF:ID  0.00168173:0.00572547:0.113509:0.037024:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101194 ES:SE:LP:AF:ID  -0.00287415:0.00416809:0.309804:0.101194:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959171 ES:SE:LP:AF:ID  -0.00476785:0.00552449:0.408935:0.959171:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031441 ES:SE:LP:AF:ID  -0.00336064:0.0100184:0.130768:0.031441:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053296 ES:SE:LP:AF:ID  0.00296153:0.00796236:0.148742:0.053296:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036542 ES:SE:LP:AF:ID  0.00130883:0.0057626:0.0861861:0.036542:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036862 ES:SE:LP:AF:ID  0.00163644:0.00570971:0.113509:0.036862:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843168 ES:SE:LP:AF:ID  -0.000389907:0.00295594:0.0457575:0.843168:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055973 ES:SE:LP:AF:ID  -0.00777359:0.00478395:1:0.055973:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122413 ES:SE:LP:AF:ID  -0.000896471:0.00323429:0.107905:0.122413:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025702 ES:SE:LP:AF:ID  0.00205771:0.00796024:0.09691:0.025702:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121656 ES:SE:LP:AF:ID  -0.000743268:0.00323569:0.0861861:0.121656:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132386 ES:SE:LP:AF:ID  -0.00130885:0.00318994:0.167491:0.132386:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011104 ES:SE:LP:AF:ID  0.00099937:0.0116222:0.0315171:0.011104:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005702 ES:SE:LP:AF:ID  0.0186321:0.0149717:0.677781:0.005702:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002251 ES:SE:LP:AF:ID  0.0773055:0.0253018:2.65758:0.002251:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.00103  ES:SE:LP:AF:ID  0.0326999:0.0412739:0.366532:0.00103:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036773 ES:SE:LP:AF:ID  0.00151228:0.00565227:0.102373:0.036773:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838892 ES:SE:LP:AF:ID  -0.00138503:0.00286245:0.200659:0.838892:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838525 ES:SE:LP:AF:ID  -0.00131989:0.0028594:0.19382:0.838525:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869678 ES:SE:LP:AF:ID  -0.00139923:0.00306759:0.187087:0.869678:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129975 ES:SE:LP:AF:ID  0.000858642:0.0030738:0.107905:0.129975:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037283 ES:SE:LP:AF:ID  0.00150798:0.00555641:0.102373:0.037283:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037528 ES:SE:LP:AF:ID  0.00174371:0.00552114:0.124939:0.037528:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869024 ES:SE:LP:AF:ID  -0.00134417:0.00306162:0.180456:0.869024:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.00149656:0.00306278:0.200659:0.869117:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037485 ES:SE:LP:AF:ID  0.0016328:0.00554518:0.113509:0.037485:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869029 ES:SE:LP:AF:ID  -0.00137958:0.00306157:0.187087:0.869029:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005141 ES:SE:LP:AF:ID  0.00387432:0.0156909:0.09691:0.005141:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005106 ES:SE:LP:AF:ID  0.00428837:0.0157322:0.102373:0.005106:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837978 ES:SE:LP:AF:ID  -0.00136775:0.00285143:0.200659:0.837978:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037497 ES:SE:LP:AF:ID  0.00178622:0.00555302:0.124939:0.037497:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838611 ES:SE:LP:AF:ID  -0.00143411:0.00285945:0.207608:0.838611:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013795 ES:SE:LP:AF:ID  0.0100607:0.00997229:0.508638:0.013795:rs181660517