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-4711/UKB-b-4711_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4711/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:39 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4711/UKB-b-4711_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: 0.0711 (0.0022)
Lambda GC: 1.5429
Mean Chi^2: 1.6932
Intercept: 1.0563 (0.009)
Ratio: 0.0812 (0.0129)
Analysis finished at Thu Oct 17 14:46:24 2019
Total time elapsed: 1.0m:45.33s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.369,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 57,
    "n_p_sig": 3661,
    "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": 0.0711,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0563,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.5429,
    "ldsc_mean_chisq": 1.6932,
    "ldsc_ratio": 0.0812
}

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 -1.111000e-04 6.339800e-03 -0.1005160 -2.214000e-03 -3.820000e-05 2.104000e-03 1.755050e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.363800e-03 4.131400e-03 0.0012211 1.494700e-03 2.506400e-03 5.783200e-03 6.413760e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.496763e-01 3.019128e-01 0.0000000 1.800002e-01 4.299995e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.496779e-01 3.018892e-01 0.0000000 1.757466e-01 4.311260e-01 7.112835e-01 9.999999e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035074e-01 2.568629e-01 0.0009870 1.316800e-02 7.790800e-02 3.164510e-01 9.990090e-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 -0.0014926 0.0022460 0.5099998 0.5063249 0.623772 0.7821490 NA
1 54676 rs2462492 C T -0.0013906 0.0022244 0.5300002 0.5318608 0.400431 NA NA
1 86028 rs114608975 T C -0.0013025 0.0035569 0.7099994 0.7142254 0.103549 0.0277556 NA
1 91536 rs6702460 G T -0.0040946 0.0021904 0.0619998 0.0615769 0.456852 0.4207270 NA
1 234313 rs8179466 C T -0.0025591 0.0043180 0.5500004 0.5534131 0.074519 NA NA
1 534192 rs6680723 C T 0.0003962 0.0025023 0.8700001 0.8742004 0.240956 NA NA
1 546697 rs12025928 A G 0.0004295 0.0031218 0.8900000 0.8905616 0.913495 NA NA
1 693731 rs12238997 A G -0.0004657 0.0020970 0.8200001 0.8242366 0.116352 0.1417730 NA
1 705882 rs72631875 G A 0.0046724 0.0030730 0.1299999 0.1283940 0.067277 0.0315495 NA
1 706368 rs55727773 A G -0.0000218 0.0015533 0.9900000 0.9888163 0.515625 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0062081 0.0032627 0.0569994 0.0570741 0.041948 0.0473243 NA
22 51219766 rs182321900 C T -0.0078202 0.0151964 0.6100002 0.6068269 0.001938 NA NA
22 51220146 rs868950473 C T -0.0109632 0.0150553 0.4700002 0.4664940 0.001986 NA NA
22 51221190 rs369304721 G A -0.0032313 0.0032573 0.3200000 0.3211917 0.049725 NA NA
22 51221731 rs115055839 T C -0.0025290 0.0024363 0.2999998 0.2992393 0.073228 0.0625000 NA
22 51222100 rs114553188 G T -0.0016512 0.0028674 0.5600000 0.5647225 0.054495 0.0880591 NA
22 51223637 rs375798137 G A -0.0016599 0.0028812 0.5600000 0.5645354 0.054123 0.0788738 NA
22 51229805 rs9616985 T C -0.0025724 0.0024452 0.2900000 0.2927748 0.073061 0.0730831 NA
22 51232488 rs376461333 A G -0.0029173 0.0057570 0.6100002 0.6123351 0.020057 NA NA
22 51237063 rs3896457 T C -0.0015543 0.0014954 0.2999998 0.2986281 0.298005 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  -0.0014926:0.00224596:0.29243:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400431 ES:SE:LP:AF:ID  -0.00139063:0.00222441:0.275724:0.400431:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -0.00130248:0.00355687:0.148742:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456852 ES:SE:LP:AF:ID  -0.00409458:0.0021904:1.20761:0.456852:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  -0.00255906:0.00431797:0.259637:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  0.000396176:0.00250229:0.0604807:0.240956:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913495 ES:SE:LP:AF:ID  0.000429537:0.00312178:0.05061:0.913495:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116352 ES:SE:LP:AF:ID  -0.000465731:0.00209695:0.0861861:0.116352:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067277 ES:SE:LP:AF:ID  0.00467236:0.00307298:0.886057:0.067277:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515625 ES:SE:LP:AF:ID  -2.17733e-05:0.00155334:0.00436481:0.515625:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032975 ES:SE:LP:AF:ID  0.00315108:0.00391779:0.376751:0.032975:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  0.00244356:0.00355859:0.309804:0.03659:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036706 ES:SE:LP:AF:ID  0.0024736:0.00354513:0.309804:0.036706:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036405 ES:SE:LP:AF:ID  0.00245105:0.00357065:0.309804:0.036405:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016402 ES:SE:LP:AF:ID  0.00948466:0.00549649:1.07572:0.016402:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036944 ES:SE:LP:AF:ID  0.00238303:0.00353111:0.30103:0.036944:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037039 ES:SE:LP:AF:ID  0.00248142:0.00351913:0.318759:0.037039:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101237 ES:SE:LP:AF:ID  0.00339771:0.00256243:0.744727:0.101237:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959139 ES:SE:LP:AF:ID  -0.0018562:0.00339442:0.236572:0.959139:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031443 ES:SE:LP:AF:ID  -0.0065105:0.00616:0.537602:0.031443:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05327  ES:SE:LP:AF:ID  -0.000676939:0.00489777:0.05061:0.05327:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036558 ES:SE:LP:AF:ID  0.00269316:0.00354184:0.346787:0.036558:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036872 ES:SE:LP:AF:ID  0.00263177:0.00350972:0.346787:0.036872:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84324  ES:SE:LP:AF:ID  0.000295963:0.00181757:0.0604807:0.84324:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055943 ES:SE:LP:AF:ID  -0.00285664:0.00294163:0.481486:0.055943:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122324 ES:SE:LP:AF:ID  -0.000839593:0.00198925:0.173925:0.122324:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025698 ES:SE:LP:AF:ID  -0.0080687:0.00489411:1.00436:0.025698:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121568 ES:SE:LP:AF:ID  -0.000862026:0.00199009:0.180456:0.121568:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132323 ES:SE:LP:AF:ID  -0.00149564:0.0019615:0.346787:0.132323:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011142 ES:SE:LP:AF:ID  0.00732106:0.00712815:0.522879:0.011142:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005706 ES:SE:LP:AF:ID  0.000882697:0.00919974:0.0362122:0.005706:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002266 ES:SE:LP:AF:ID  0.00461553:0.0154867:0.113509:0.002266:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001026 ES:SE:LP:AF:ID  0.00848328:0.0254456:0.130768:0.001026:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036788 ES:SE:LP:AF:ID  0.00233424:0.00347411:0.30103:0.036788:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838968 ES:SE:LP:AF:ID  -0.000381967:0.00176009:0.0809219:0.838968:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8386   ES:SE:LP:AF:ID  -0.000395359:0.00175823:0.0861861:0.8386:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869764 ES:SE:LP:AF:ID  -9.84989e-05:0.00188656:0.0177288:0.869764:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12988  ES:SE:LP:AF:ID  2.98734e-05:0.00189044:0.00436481:0.12988:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037298 ES:SE:LP:AF:ID  0.00255947:0.00341528:0.346787:0.037298:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037541 ES:SE:LP:AF:ID  0.00233621:0.0033937:0.309804:0.037541:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869111 ES:SE:LP:AF:ID  -0.00019077:0.00188289:0.0362122:0.869111:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86921  ES:SE:LP:AF:ID  -0.000250586:0.00188364:0.05061:0.86921:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037499 ES:SE:LP:AF:ID  0.00271216:0.00340838:0.366532:0.037499:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  -0.00015334:0.00188285:0.0268721:0.869114:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005122 ES:SE:LP:AF:ID  0.0145007:0.00966553:0.886057:0.005122:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005089 ES:SE:LP:AF:ID  0.0147528:0.00969045:0.886057:0.005089:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838055 ES:SE:LP:AF:ID  -0.000566489:0.00175337:0.124939:0.838055:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037512 ES:SE:LP:AF:ID  0.00278482:0.00341319:0.387216:0.037512:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838685 ES:SE:LP:AF:ID  -0.000580455:0.0017583:0.130768:0.838685:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  0.0055218:0.00613634:0.431798:0.013772:rs181660517