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-7337/UKB-b-7337_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7337/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7337/UKB-b-7337_data.vcf.gz ...
Read summary statistics for 9819401 SNPs.
Dropped 14340 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, 1289076 SNPs remain.
After merging with regression SNP LD, 1289076 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0362 (0.0019)
Lambda GC: 1.3296
Mean Chi^2: 1.3822
Intercept: 1.0587 (0.0073)
Ratio: 0.1535 (0.019)
Analysis finished at Thu Oct 17 14:41:55 2019
Total time elapsed: 1.0m:35.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9498,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 20,
    "n_p_sig": 503,
    "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": 181811,
    "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": 1289076,
    "ldsc_nsnp_merge_regression_ld": 1289076,
    "ldsc_observed_scale_h2_beta": 0.0362,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.0587,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.3296,
    "ldsc_mean_chisq": 1.3822,
    "ldsc_ratio": 0.1536
}

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 9805128 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 9819401 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 8.622879e+00 5.748516e+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 7.885963e+07 5.628550e+07 828.0000000 3.258631e+07 6.948836e+07 1.145941e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.038000e-04 4.545300e-03 -0.0672204 -1.517900e-03 -2.990000e-05 1.439000e-03 6.670310e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.187100e-03 2.981300e-03 0.0009027 1.103800e-03 1.844200e-03 4.238600e-03 4.743170e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.672942e-01 2.977247e-01 0.0000000 2.000000e-01 4.500005e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.672954e-01 2.977003e-01 0.0000000 2.013120e-01 4.549275e-01 7.258265e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.040338e-01 2.568669e-01 0.0010620 1.338800e-02 7.873100e-02 3.174960e-01 9.989380e-01 ▇▂▁▁▁
numeric AF_reference 181811 0.9814845 NA NA NA NA NA NA NA 2.072225e-01 2.483588e-01 0.0000000 1.198080e-02 1.004390e-01 3.210860e-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 -0.0012279 0.0016607 0.4600002 0.4596830 0.623782 0.7821490 NA
1 54676 rs2462492 C T -0.0011391 0.0016450 0.4899999 0.4886358 0.400397 NA NA
1 86028 rs114608975 T C 0.0006094 0.0026296 0.8200001 0.8167359 0.103566 0.0277556 NA
1 91536 rs6702460 G T -0.0013880 0.0016198 0.3900004 0.3915034 0.456836 0.4207270 NA
1 234313 rs8179466 C T 0.0023589 0.0031930 0.4600002 0.4600344 0.074517 NA NA
1 534192 rs6680723 C T 0.0028650 0.0018504 0.1199999 0.1215600 0.240936 NA NA
1 546697 rs12025928 A G -0.0025336 0.0023087 0.2700001 0.2724561 0.913502 NA NA
1 693731 rs12238997 A G -0.0001184 0.0015504 0.9400001 0.9391304 0.116349 0.1417730 NA
1 705882 rs72631875 G A 0.0029345 0.0022724 0.2000000 0.1965742 0.067272 0.0315495 NA
1 706368 rs55727773 A G 0.0004991 0.0011486 0.6600001 0.6638750 0.515605 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0011963 0.0024118 0.6200004 0.6198792 0.041939 0.0473243 NA
22 51219766 rs182321900 C T 0.0148033 0.0112297 0.1900002 0.1874275 0.001938 NA NA
22 51220146 rs868950473 C T 0.0173663 0.0111255 0.1199999 0.1185366 0.001986 NA NA
22 51221190 rs369304721 G A -0.0002955 0.0024079 0.9000000 0.9023438 0.049715 NA NA
22 51221731 rs115055839 T C -0.0006920 0.0018007 0.6999999 0.7007626 0.073221 0.0625000 NA
22 51222100 rs114553188 G T -0.0003358 0.0021196 0.8700001 0.8741133 0.054465 0.0880591 NA
22 51223637 rs375798137 G A -0.0003345 0.0021298 0.8800001 0.8751945 0.054096 0.0788738 NA
22 51229805 rs9616985 T C -0.0005557 0.0018073 0.7600007 0.7584744 0.073053 0.0730831 NA
22 51232488 rs376461333 A G -0.0017508 0.0042554 0.6800001 0.6807464 0.020051 NA NA
22 51237063 rs3896457 T C 0.0005167 0.0011053 0.6400000 0.6401679 0.297957 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623782 ES:SE:LP:AF:ID  -0.00122787:0.0016607:0.337242:0.623782:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400397 ES:SE:LP:AF:ID  -0.00113913:0.001645:0.309804:0.400397:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103566 ES:SE:LP:AF:ID  0.000609402:0.00262962:0.0861861:0.103566:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456836 ES:SE:LP:AF:ID  -0.00138798:0.00161978:0.408935:0.456836:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074517 ES:SE:LP:AF:ID  0.00235892:0.00319295:0.337242:0.074517:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240936 ES:SE:LP:AF:ID  0.00286496:0.00185044:0.920819:0.240936:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913502 ES:SE:LP:AF:ID  -0.00253359:0.00230867:0.568636:0.913502:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116349 ES:SE:LP:AF:ID  -0.00011839:0.00155036:0.0268721:0.116349:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067272 ES:SE:LP:AF:ID  0.00293453:0.00227241:0.69897:0.067272:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515605 ES:SE:LP:AF:ID  0.000499129:0.00114856:0.180456:0.515605:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032986 ES:SE:LP:AF:ID  0.0014456:0.00289661:0.207608:0.032986:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036602 ES:SE:LP:AF:ID  0.00186209:0.00263099:0.318759:0.036602:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036718 ES:SE:LP:AF:ID  0.00201411:0.00262101:0.356547:0.036718:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036419 ES:SE:LP:AF:ID  0.00186049:0.00263982:0.318759:0.036419:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016401 ES:SE:LP:AF:ID  0.000583929:0.00406469:0.05061:0.016401:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036957 ES:SE:LP:AF:ID  0.00202415:0.00261065:0.356547:0.036957:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037053 ES:SE:LP:AF:ID  0.00216924:0.00260173:0.39794:0.037053:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101242 ES:SE:LP:AF:ID  0.00358938:0.00189462:1.23657:0.101242:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959112 ES:SE:LP:AF:ID  -0.00135557:0.00250913:0.229148:0.959112:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  -0.00081938:0.00455418:0.0655015:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053275 ES:SE:LP:AF:ID  -0.00328988:0.00362157:0.443698:0.053275:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036574 ES:SE:LP:AF:ID  0.00201944:0.00261843:0.356547:0.036574:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036886 ES:SE:LP:AF:ID  0.00212281:0.00259475:0.387216:0.036886:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843211 ES:SE:LP:AF:ID  0.00050621:0.00134376:0.148742:0.843211:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055936 ES:SE:LP:AF:ID  -0.00193723:0.00217523:0.431798:0.055936:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122327 ES:SE:LP:AF:ID  -0.00116064:0.00147068:0.366532:0.122327:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025679 ES:SE:LP:AF:ID  -0.00992286:0.00362022:2.21467:0.025679:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12157  ES:SE:LP:AF:ID  -0.00121657:0.0014713:0.387216:0.12157:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132338 ES:SE:LP:AF:ID  -0.000384737:0.00145028:0.102373:0.132338:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011143 ES:SE:LP:AF:ID  -0.00238783:0.00526987:0.187087:0.011143:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005705 ES:SE:LP:AF:ID  -0.0040793:0.0068036:0.259637:0.005705:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002272 ES:SE:LP:AF:ID  0.00716824:0.0114376:0.275724:0.002272:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036802 ES:SE:LP:AF:ID  0.00158345:0.00256848:0.267606:0.036802:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83895  ES:SE:LP:AF:ID  -0.000175602:0.00130131:0.05061:0.83895:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838577 ES:SE:LP:AF:ID  -0.0002105:0.0012999:0.0604807:0.838577:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869761 ES:SE:LP:AF:ID  0.000578336:0.00139479:0.167491:0.869761:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129886 ES:SE:LP:AF:ID  -0.000770886:0.00139762:0.236572:0.129886:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037312 ES:SE:LP:AF:ID  0.00188981:0.00252495:0.346787:0.037312:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037556 ES:SE:LP:AF:ID  0.0016745:0.00250899:0.30103:0.037556:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  0.000577648:0.00139205:0.167491:0.869103:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869201 ES:SE:LP:AF:ID  0.000515715:0.0013926:0.148742:0.869201:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  0.00181702:0.00251986:0.327902:0.037514:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  0.000587224:0.00139202:0.173925:0.869106:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005126 ES:SE:LP:AF:ID  0.00753719:0.00714367:0.537602:0.005126:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005092 ES:SE:LP:AF:ID  0.0072244:0.00716243:0.508638:0.005092:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838032 ES:SE:LP:AF:ID  -0.00017209:0.0012963:0.05061:0.838032:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  0.00193921:0.00252342:0.356547:0.037527:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838663 ES:SE:LP:AF:ID  -0.000203179:0.00129995:0.0555173:0.838663:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013783 ES:SE:LP:AF:ID  0.00213291:0.00453575:0.19382:0.013783:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005546 ES:SE:LP:AF:ID  0.00321973:0.00700165:0.187087:0.005546:rs184270342