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-11749/UKB-b-11749_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11749/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11749/UKB-b-11749_data.vcf.gz ...
Read summary statistics for 9756963 SNPs.
Dropped 13802 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, 1288925 SNPs remain.
After merging with regression SNP LD, 1288925 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0231 (0.0017)
Lambda GC: 1.337
Mean Chi^2: 1.3628
Intercept: 1.1556 (0.0083)
Ratio: 0.429 (0.0229)
Analysis finished at Thu Oct 17 14:42:54 2019
Total time elapsed: 1.0m:47.87s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9497,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 7,
    "n_p_sig": 61,
    "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": 171256,
    "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": 1288925,
    "ldsc_nsnp_merge_regression_ld": 1288925,
    "ldsc_observed_scale_h2_beta": 0.0231,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.1556,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.337,
    "ldsc_mean_chisq": 1.3628,
    "ldsc_ratio": 0.4289
}

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 FALSE
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 9743226 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 9756963 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 8.623662e+00 5.749243e+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 7.885795e+07 5.629300e+07 828.0000000 3.257823e+07 6.947606e+07 1.145917e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.730000e-05 4.808300e-03 -0.0953848 -1.541400e-03 1.350000e-05 1.587300e-03 9.156420e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.283500e-03 3.002800e-03 0.0009518 1.161200e-03 1.926600e-03 4.393200e-03 5.003510e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.616788e-01 2.986794e-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 4.616806e-01 2.986572e-01 0.0000000 1.930004e-01 4.470720e-01 7.208341e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.051168e-01 2.569363e-01 0.0011700 1.383000e-02 8.026700e-02 3.195570e-01 9.988300e-01 ▇▂▁▁▁
numeric AF_reference 171256 0.9824478 NA NA NA NA NA NA NA 2.079815e-01 2.484780e-01 0.0000000 1.218050e-02 1.016370e-01 3.226840e-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 -0.0013876 0.0017504 0.4299995 0.4279406 0.623767 0.7821490 NA
1 54676 rs2462492 C T 0.0008695 0.0017342 0.6200004 0.6161078 0.400389 NA NA
1 86028 rs114608975 T C -0.0011359 0.0027725 0.6800001 0.6820339 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0019293 0.0017075 0.2599998 0.2585123 0.456834 0.4207270 NA
1 234313 rs8179466 C T -0.0007741 0.0033666 0.8200001 0.8181292 0.074509 NA NA
1 534192 rs6680723 C T -0.0008025 0.0019504 0.6800001 0.6807425 0.240956 NA NA
1 546697 rs12025928 A G -0.0021915 0.0024332 0.3700002 0.3677641 0.913476 NA NA
1 693731 rs12238997 A G -0.0000247 0.0016345 0.9900000 0.9879198 0.116323 0.1417730 NA
1 705882 rs72631875 G A -0.0001756 0.0023952 0.9400001 0.9415574 0.067284 0.0315495 NA
1 706368 rs55727773 A G -0.0005789 0.0012107 0.6300007 0.6325357 0.515643 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0024762 0.0025428 0.3300000 0.3301480 0.041950 0.0473243 NA
22 51219766 rs182321900 C T 0.0017287 0.0118527 0.8800001 0.8840416 0.001936 NA NA
22 51220146 rs868950473 C T -0.0009121 0.0117407 0.9400001 0.9380795 0.001984 NA NA
22 51221190 rs369304721 G A 0.0030225 0.0025386 0.2300001 0.2337972 0.049726 NA NA
22 51221731 rs115055839 T C 0.0017746 0.0018987 0.3500000 0.3499667 0.073229 0.0625000 NA
22 51222100 rs114553188 G T 0.0002974 0.0022352 0.8900000 0.8941704 0.054458 0.0880591 NA
22 51223637 rs375798137 G A 0.0002216 0.0022461 0.9199999 0.9214150 0.054087 0.0788738 NA
22 51229805 rs9616985 T C 0.0017876 0.0019055 0.3500000 0.3481761 0.073064 0.0730831 NA
22 51232488 rs376461333 A G -0.0058302 0.0044889 0.1900002 0.1940121 0.020042 NA NA
22 51237063 rs3896457 T C 0.0020401 0.0011654 0.0800000 0.0800277 0.297958 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623767 ES:SE:LP:AF:ID  -0.00138761:0.00175044:0.366532:0.623767:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400389 ES:SE:LP:AF:ID  0.000869473:0.00173418:0.207608:0.400389:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  -0.00113588:0.00277254:0.167491:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456834 ES:SE:LP:AF:ID  0.00192934:0.00170751:0.585027:0.456834:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074509 ES:SE:LP:AF:ID  -0.000774149:0.00336657:0.0861861:0.074509:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  -0.000802484:0.00195038:0.167491:0.240956:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -0.0021915:0.00243319:0.431798:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116323 ES:SE:LP:AF:ID  -2.47475e-05:0.00163448:0.00436481:0.116323:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067284 ES:SE:LP:AF:ID  -0.000175596:0.00239517:0.0268721:0.067284:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515643 ES:SE:LP:AF:ID  -0.000578919:0.00121072:0.200659:0.515643:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033008 ES:SE:LP:AF:ID  0.000916596:0.00305225:0.119186:0.033008:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036624 ES:SE:LP:AF:ID  0.000703201:0.00277249:0.09691:0.036624:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03674  ES:SE:LP:AF:ID  0.000237999:0.002762:0.0315171:0.03674:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036439 ES:SE:LP:AF:ID  0.000419314:0.00278193:0.0555173:0.036439:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016406 ES:SE:LP:AF:ID  0.00771555:0.00428368:1.14267:0.016406:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03698  ES:SE:LP:AF:ID  0.000356598:0.00275105:0.0457575:0.03698:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037077 ES:SE:LP:AF:ID  0.000351606:0.00274161:0.0457575:0.037077:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  0.00262164:0.00199761:0.721246:0.101206:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959092 ES:SE:LP:AF:ID  0.00031574:0.00264427:0.0457575:0.959092:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031454 ES:SE:LP:AF:ID  0.00214434:0.00480015:0.180456:0.031454:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  -0.0090269:0.00381869:1.74473:0.053255:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036593 ES:SE:LP:AF:ID  4.33093e-05:0.00275941:0.00436481:0.036593:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03691  ES:SE:LP:AF:ID  0.000558919:0.00273429:0.0757207:0.03691:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84321  ES:SE:LP:AF:ID  -0.000113562:0.00141647:0.0268721:0.84321:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055908 ES:SE:LP:AF:ID  -0.00102003:0.00229356:0.180456:0.055908:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122306 ES:SE:LP:AF:ID  -0.000193678:0.00155047:0.0457575:0.122306:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025713 ES:SE:LP:AF:ID  -0.000534518:0.00381378:0.05061:0.025713:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121547 ES:SE:LP:AF:ID  -9.55043e-05:0.00155112:0.0222764:0.121547:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132332 ES:SE:LP:AF:ID  -0.000772852:0.00152877:0.21467:0.132332:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011136 ES:SE:LP:AF:ID  -0.00410769:0.00555785:0.337242:0.011136:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005698 ES:SE:LP:AF:ID  -0.00499498:0.00717662:0.309804:0.005698:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002271 ES:SE:LP:AF:ID  -0.0114924:0.0120608:0.468521:0.002271:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036825 ES:SE:LP:AF:ID  0.00107363:0.00270663:0.161151:0.036825:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838948 ES:SE:LP:AF:ID  -0.000243117:0.00137175:0.0655015:0.838948:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838577 ES:SE:LP:AF:ID  -0.000231229:0.00137028:0.0604807:0.838577:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869779 ES:SE:LP:AF:ID  0.000349247:0.00147036:0.091515:0.869779:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129873 ES:SE:LP:AF:ID  -0.000126095:0.00147337:0.0315171:0.129873:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  0.000431544:0.00266073:0.0604807:0.037336:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03758  ES:SE:LP:AF:ID  0.000672372:0.00264391:0.09691:0.03758:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86912  ES:SE:LP:AF:ID  0.000393184:0.00146748:0.102373:0.86912:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869218 ES:SE:LP:AF:ID  0.000330589:0.00146806:0.0861861:0.869218:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037537 ES:SE:LP:AF:ID  0.000439872:0.00265535:0.0604807:0.037537:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869124 ES:SE:LP:AF:ID  0.000394494:0.00146745:0.102373:0.869124:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005123 ES:SE:LP:AF:ID  0.00601355:0.00753401:0.376751:0.005123:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005089 ES:SE:LP:AF:ID  0.00610334:0.00755377:0.376751:0.005089:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83803  ES:SE:LP:AF:ID  -0.00013911:0.00136647:0.0362122:0.83803:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  0.0003763:0.00265911:0.05061:0.03755:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838661 ES:SE:LP:AF:ID  -9.63658e-05:0.00137031:0.0268721:0.838661:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  0.000857104:0.00478369:0.0655015:0.013772:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005548 ES:SE:LP:AF:ID  0.00183487:0.00737975:0.09691:0.005548:rs184270342