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-18099/UKB-b-18099_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18099/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18099/UKB-b-18099_data.vcf.gz ...
Read summary statistics for 9540667 SNPs.
Dropped 11931 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, 1288458 SNPs remain.
After merging with regression SNP LD, 1288458 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.041 (0.0019)
Lambda GC: 1.377
Mean Chi^2: 1.4482
Intercept: 1.077 (0.0089)
Ratio: 0.1717 (0.0199)
Analysis finished at Thu Oct 17 14:42:05 2019
Total time elapsed: 1.0m:46.56s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9492,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 21,
    "n_p_sig": 943,
    "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": 138451,
    "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": 1288458,
    "ldsc_nsnp_merge_regression_ld": 1288458,
    "ldsc_observed_scale_h2_beta": 0.041,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.077,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.377,
    "ldsc_mean_chisq": 1.4482,
    "ldsc_ratio": 0.1718
}

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 9528797 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 9540667 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 8.628322e+00 5.751196e+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 7.883383e+07 5.630447e+07 828.0000000 3.254426e+07 6.942446e+07 1.145673e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -7.250000e-05 4.466700e-03 -0.0625662 -1.659500e-03 -3.320000e-05 1.587600e-03 5.393640e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.201900e-03 2.717400e-03 0.0009995 1.211000e-03 1.962200e-03 4.347400e-03 3.462450e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.599482e-01 2.990644e-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 4.599501e-01 2.990390e-01 0.0000000 1.912061e-01 4.455207e-01 7.187066e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.090404e-01 2.572401e-01 0.0016460 1.546300e-02 8.581700e-02 3.269340e-01 9.983540e-01 ▇▂▁▁▁
numeric AF_reference 138451 0.9854883 NA NA NA NA NA NA NA 2.108852e-01 2.489413e-01 0.0000000 1.317890e-02 1.056310e-01 3.284740e-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 0.0037886 0.0018386 0.0389996 0.0393449 0.623772 0.7821490 NA
1 54676 rs2462492 C T -0.0035127 0.0018213 0.0539995 0.0537789 0.400421 NA NA
1 86028 rs114608975 T C -0.0016210 0.0029117 0.5800000 0.5777152 0.103585 0.0277556 NA
1 91536 rs6702460 G T 0.0032875 0.0017933 0.0669993 0.0667686 0.456816 0.4207270 NA
1 234313 rs8179466 C T 0.0012207 0.0035344 0.7300002 0.7298133 0.074526 NA NA
1 534192 rs6680723 C T 0.0006069 0.0020486 0.7700005 0.7670231 0.240962 NA NA
1 546697 rs12025928 A G -0.0024104 0.0025558 0.3500000 0.3456253 0.913481 NA NA
1 693731 rs12238997 A G 0.0025743 0.0017162 0.1299999 0.1336272 0.116349 0.1417730 NA
1 705882 rs72631875 G A -0.0000039 0.0025158 1.0000000 0.9987697 0.067273 0.0315495 NA
1 706368 rs55727773 A G -0.0003853 0.0012716 0.7600007 0.7619126 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0026531 0.0026707 0.3200000 0.3205084 0.041940 0.0473243 NA
22 51219766 rs182321900 C T -0.0037476 0.0124558 0.7600007 0.7635110 0.001935 NA NA
22 51220146 rs868950473 C T -0.0026526 0.0123354 0.8300000 0.8297377 0.001984 NA NA
22 51221190 rs369304721 G A -0.0045512 0.0026665 0.0879995 0.0878599 0.049710 NA NA
22 51221731 rs115055839 T C -0.0018673 0.0019941 0.3500000 0.3490409 0.073212 0.0625000 NA
22 51222100 rs114553188 G T 0.0001738 0.0023470 0.9400001 0.9409650 0.054457 0.0880591 NA
22 51223637 rs375798137 G A 0.0002001 0.0023584 0.9299999 0.9323697 0.054086 0.0788738 NA
22 51229805 rs9616985 T C -0.0019407 0.0020013 0.3300000 0.3321913 0.073046 0.0730831 NA
22 51232488 rs376461333 A G -0.0031123 0.0047100 0.5099998 0.5087489 0.020058 NA NA
22 51237063 rs3896457 T C -0.0004670 0.0012236 0.6999999 0.7026984 0.297994 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  0.00378863:0.00183864:1.40894:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400421 ES:SE:LP:AF:ID  -0.00351266:0.00182134:1.26761:0.400421:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103585 ES:SE:LP:AF:ID  -0.001621:0.00291167:0.236572:0.103585:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456816 ES:SE:LP:AF:ID  0.00328751:0.00179329:1.17393:0.456816:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074526 ES:SE:LP:AF:ID  0.0012207:0.00353443:0.136677:0.074526:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240962 ES:SE:LP:AF:ID  0.000606929:0.00204856:0.113509:0.240962:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913481 ES:SE:LP:AF:ID  -0.00241035:0.00255575:0.455932:0.913481:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116349 ES:SE:LP:AF:ID  0.00257426:0.00171623:0.886057:0.116349:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067273 ES:SE:LP:AF:ID  -3.8792e-06:0.00251582:-0:0.067273:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000385266:0.00127163:0.119186:0.515645:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032976 ES:SE:LP:AF:ID  0.00178995:0.00320723:0.236572:0.032976:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  0.00200124:0.00291315:0.309804:0.03659:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036705 ES:SE:LP:AF:ID  0.00177677:0.00290217:0.267606:0.036705:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036407 ES:SE:LP:AF:ID  0.00222802:0.00292299:0.346787:0.036407:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016397 ES:SE:LP:AF:ID  0.00513607:0.00450093:0.60206:0.016397:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036944 ES:SE:LP:AF:ID  0.0023217:0.00289068:0.376751:0.036944:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037043 ES:SE:LP:AF:ID  0.00209103:0.0028807:0.327902:0.037043:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101233 ES:SE:LP:AF:ID  0.00193896:0.00209755:0.443698:0.101233:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959133 ES:SE:LP:AF:ID  -0.00257954:0.0027785:0.455932:0.959133:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031452 ES:SE:LP:AF:ID  0.00753799:0.00504074:0.886057:0.031452:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053268 ES:SE:LP:AF:ID  0.0015804:0.00400915:0.161151:0.053268:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036561 ES:SE:LP:AF:ID  0.00183749:0.00289931:0.275724:0.036561:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036873 ES:SE:LP:AF:ID  0.00201045:0.00287309:0.318759:0.036873:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84323  ES:SE:LP:AF:ID  -0.00229603:0.00148763:0.920819:0.84323:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055944 ES:SE:LP:AF:ID  0.00177955:0.00240804:0.337242:0.055944:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122334 ES:SE:LP:AF:ID  0.00253474:0.00162804:0.920819:0.122334:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025728 ES:SE:LP:AF:ID  -0.00807076:0.00400407:1.35655:0.025728:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121576 ES:SE:LP:AF:ID  0.00244574:0.00162872:0.886057:0.121576:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132332 ES:SE:LP:AF:ID  0.0018841:0.0016054:0.619789:0.132332:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011138 ES:SE:LP:AF:ID  -0.00979807:0.00583617:1.03152:0.011138:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005701 ES:SE:LP:AF:ID  -0.00251904:0.00753428:0.130768:0.005701:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002265 ES:SE:LP:AF:ID  -0.000184917:0.0126771:0.00436481:0.002265:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036789 ES:SE:LP:AF:ID  0.0016549:0.002844:0.251812:0.036789:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838985 ES:SE:LP:AF:ID  -0.00217803:0.00144072:0.886057:0.838985:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838616 ES:SE:LP:AF:ID  -0.00219191:0.00143921:0.886057:0.838616:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869779 ES:SE:LP:AF:ID  -0.00255145:0.00154416:1.00877:0.869779:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129873 ES:SE:LP:AF:ID  0.00242376:0.00154731:0.920819:0.129873:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037298 ES:SE:LP:AF:ID  0.00189274:0.00279587:0.30103:0.037298:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037541 ES:SE:LP:AF:ID  0.00175967:0.00277821:0.275724:0.037541:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  -0.00259424:0.00154118:1.03621:0.869122:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869218 ES:SE:LP:AF:ID  -0.00257109:0.00154179:1.02228:0.869218:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.0375   ES:SE:LP:AF:ID  0.00195333:0.00279019:0.318759:0.0375:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869125 ES:SE:LP:AF:ID  -0.00259754:0.00154115:1.03621:0.869125:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005119 ES:SE:LP:AF:ID  0.0101764:0.00791615:0.69897:0.005119:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005085 ES:SE:LP:AF:ID  0.0106419:0.00793699:0.744727:0.005085:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838068 ES:SE:LP:AF:ID  -0.00223404:0.00143522:0.920819:0.838068:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  0.00177707:0.0027941:0.283997:0.037514:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838697 ES:SE:LP:AF:ID  -0.00221198:0.00143924:0.920819:0.838697:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013781 ES:SE:LP:AF:ID  -0.00304682:0.00502152:0.267606:0.013781:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005531 ES:SE:LP:AF:ID  -0.0101449:0.00776386:0.721246:0.005531:rs184270342