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-10011/UKB-b-10011_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10011/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:20 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10011/UKB-b-10011_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: 0.0323 (0.0017)
Lambda GC: 1.3902
Mean Chi^2: 1.4284
Intercept: 1.1371 (0.0082)
Ratio: 0.3201 (0.0191)
Analysis finished at Thu Oct 17 14:42:14 2019
Total time elapsed: 1.0m:53.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0.0005,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 18,
    "n_p_sig": 372,
    "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": 0.0323,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.1371,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.3902,
    "ldsc_mean_chisq": 1.4284,
    "ldsc_ratio": 0.32
}

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 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 4.821000e-04 1.055760e-02 -0.2636510 -3.101600e-03 1.324000e-04 3.511700e-03 1.596220e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.983700e-03 6.609400e-03 0.0019546 2.392400e-03 4.011800e-03 9.256700e-03 1.028730e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.576623e-01 2.993623e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.576638e-01 2.993374e-01 0.0000000 1.875304e-01 4.419015e-01 7.164605e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035078e-01 2.568609e-01 0.0009970 1.317000e-02 7.791500e-02 3.164540e-01 9.990030e-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 -0.0070293 0.0035949 0.0510000 0.0505423 0.623769 0.7821490 NA
1 54676 rs2462492 C T 0.0013313 0.0035614 0.7099994 0.7085369 0.400403 NA NA
1 86028 rs114608975 T C 0.0115716 0.0056934 0.0420001 0.0421062 0.103564 0.0277556 NA
1 91536 rs6702460 G T -0.0005324 0.0035066 0.8800001 0.8793270 0.456859 0.4207270 NA
1 234313 rs8179466 C T -0.0028079 0.0069157 0.6800001 0.6847258 0.074497 NA NA
1 534192 rs6680723 C T 0.0009632 0.0040058 0.8100000 0.8099755 0.240957 NA NA
1 546697 rs12025928 A G 0.0094117 0.0049974 0.0599998 0.0596573 0.913488 NA NA
1 693731 rs12238997 A G 0.0032246 0.0033569 0.3400001 0.3367607 0.116328 0.1417730 NA
1 705882 rs72631875 G A -0.0001113 0.0049192 0.9800000 0.9819481 0.067283 0.0315495 NA
1 706368 rs55727773 A G -0.0067264 0.0024865 0.0068000 0.0068269 0.515647 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0041590 0.0052221 0.4299995 0.4257867 0.041952 0.0473243 NA
22 51219766 rs182321900 C T -0.0384199 0.0243178 0.1100001 0.1141278 0.001939 NA NA
22 51220146 rs868950473 C T -0.0425791 0.0240915 0.0769999 0.0771628 0.001987 NA NA
22 51221190 rs369304721 G A -0.0006272 0.0052134 0.9000000 0.9042435 0.049732 NA NA
22 51221731 rs115055839 T C 0.0015005 0.0038992 0.6999999 0.7003660 0.073235 0.0625000 NA
22 51222100 rs114553188 G T 0.0053878 0.0045902 0.2399999 0.2404821 0.054471 0.0880591 NA
22 51223637 rs375798137 G A 0.0049158 0.0046124 0.2900000 0.2865165 0.054100 0.0788738 NA
22 51229805 rs9616985 T C 0.0016864 0.0039133 0.6700003 0.6665118 0.073071 0.0730831 NA
22 51232488 rs376461333 A G -0.0026334 0.0092173 0.7800007 0.7751044 0.020047 NA NA
22 51237063 rs3896457 T C 0.0001616 0.0023933 0.9500000 0.9461619 0.297978 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623769 ES:SE:LP:AF:ID  -0.00702931:0.00359492:1.29243:0.623769:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400403 ES:SE:LP:AF:ID  0.00133134:0.00356143:0.148742:0.400403:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103564 ES:SE:LP:AF:ID  0.0115716:0.00569337:1.37675:0.103564:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  -0.000532379:0.00350659:0.0555173:0.456859:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074497 ES:SE:LP:AF:ID  -0.00280794:0.00691572:0.167491:0.074497:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240957 ES:SE:LP:AF:ID  0.000963237:0.00400585:0.091515:0.240957:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913488 ES:SE:LP:AF:ID  0.00941171:0.00499741:1.22185:0.913488:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116328 ES:SE:LP:AF:ID  0.00322457:0.00335688:0.468521:0.116328:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067283 ES:SE:LP:AF:ID  -0.000111306:0.00491925:0.00877392:0.067283:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515647 ES:SE:LP:AF:ID  -0.00672638:0.00248649:2.16749:0.515647:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033006 ES:SE:LP:AF:ID  0.00613947:0.00626847:0.481486:0.033006:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036622 ES:SE:LP:AF:ID  0.00615861:0.00569386:0.552842:0.036622:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03674  ES:SE:LP:AF:ID  0.00632699:0.00567222:0.585027:0.03674:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036437 ES:SE:LP:AF:ID  0.00604104:0.00571323:0.537602:0.036437:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016414 ES:SE:LP:AF:ID  0.00843634:0.00879517:0.468521:0.016414:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036979 ES:SE:LP:AF:ID  0.00513363:0.00564969:0.443698:0.036979:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037075 ES:SE:LP:AF:ID  0.00559294:0.00563042:0.49485:0.037075:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101204 ES:SE:LP:AF:ID  0.00298488:0.00410228:0.327902:0.101204:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959091 ES:SE:LP:AF:ID  -0.00781189:0.00543041:0.823909:0.959091:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  0.00033802:0.00986007:0.0132283:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053257 ES:SE:LP:AF:ID  -0.0145492:0.00784197:1.19382:0.053257:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036593 ES:SE:LP:AF:ID  0.00615981:0.00566682:0.552842:0.036593:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036908 ES:SE:LP:AF:ID  0.00564305:0.00561539:0.508638:0.036908:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843205 ES:SE:LP:AF:ID  -0.00467821:0.00290912:0.958607:0.843205:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055914 ES:SE:LP:AF:ID  0.00281029:0.00471009:0.259637:0.055914:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:ID  0.00363482:0.00318431:0.60206:0.122311:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  0.00931115:0.00783184:0.638272:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121553 ES:SE:LP:AF:ID  0.00360785:0.00318564:0.585027:0.121553:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132327 ES:SE:LP:AF:ID  0.00361484:0.00313977:0.60206:0.132327:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011131 ES:SE:LP:AF:ID  0.00315498:0.0114168:0.107905:0.011131:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005695 ES:SE:LP:AF:ID  0.00114303:0.0147427:0.0268721:0.005695:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002272 ES:SE:LP:AF:ID  0.00809304:0.0247577:0.130768:0.002272:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001032 ES:SE:LP:AF:ID  0.0376428:0.0405108:0.455932:0.001032:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036823 ES:SE:LP:AF:ID  0.00652505:0.00555849:0.619789:0.036823:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838946 ES:SE:LP:AF:ID  -0.00595973:0.00281727:1.46852:0.838946:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838576 ES:SE:LP:AF:ID  -0.00595925:0.00281425:1.46852:0.838576:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869775 ES:SE:LP:AF:ID  -0.00538944:0.00301981:1.13077:0.869775:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129875 ES:SE:LP:AF:ID  0.00552164:0.00302598:1.16749:0.129875:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037334 ES:SE:LP:AF:ID  0.00631173:0.0054643:0.60206:0.037334:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037578 ES:SE:LP:AF:ID  0.00639443:0.00542977:0.619789:0.037578:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  -0.00540315:0.0030139:1.13668:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  -0.00546131:0.0030151:1.1549:0.869216:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  0.00646027:0.00545327:0.619789:0.037535:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  -0.00546544:0.00301385:1.1549:0.869122:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005123 ES:SE:LP:AF:ID  0.00950192:0.0154721:0.267606:0.005123:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005089 ES:SE:LP:AF:ID  0.00845138:0.0155127:0.229148:0.005089:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838029 ES:SE:LP:AF:ID  -0.0059157:0.00280645:1.45593:0.838029:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037548 ES:SE:LP:AF:ID  0.00658033:0.00546098:0.638272:0.037548:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838661 ES:SE:LP:AF:ID  -0.00618339:0.00281434:1.55284:0.838661:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  -0.00499601:0.00982307:0.21467:0.013772:rs181660517