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-7135/UKB-b-7135_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7135/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7135/UKB-b-7135_data.vcf.gz ...
Read summary statistics for 9092466 SNPs.
Dropped 9148 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, 1287407 SNPs remain.
After merging with regression SNP LD, 1287407 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0209 (0.0016)
Lambda GC: 1.2294
Mean Chi^2: 1.2522
Intercept: 1.0693 (0.0076)
Ratio: 0.2749 (0.0301)
Analysis finished at Thu Oct 17 14:42:45 2019
Total time elapsed: 2.0m:28.48s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.948,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -1.1444e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 6,
    "n_p_sig": 212,
    "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": 97833,
    "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": 1287407,
    "ldsc_nsnp_merge_regression_ld": 1287407,
    "ldsc_observed_scale_h2_beta": 0.0209,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0693,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.2294,
    "ldsc_mean_chisq": 1.2522,
    "ldsc_ratio": 0.2748
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
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 9083361 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 9092466 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 8.641036e+00 5.757300e+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 7.879275e+07 5.632886e+07 828.0000000 3.245028e+07 6.936241e+07 1.145277e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.100000e-06 3.213600e-03 -0.0340370 -1.276700e-03 -2.500000e-06 1.276300e-03 3.544780e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.456800e-03 1.837000e-03 0.0008733 1.043600e-03 1.612300e-03 3.371600e-03 2.020670e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.733506e-01 2.955597e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.733517e-01 2.955344e-01 0.0000000 2.107049e-01 4.637130e-01 7.292505e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.182916e-01 2.583345e-01 0.0031750 1.955900e-02 9.881400e-02 3.439960e-01 9.968250e-01 ▇▂▁▁▁
numeric AF_reference 97833 0.9892402 NA NA NA NA NA NA NA 2.187433e-01 2.502071e-01 0.0000000 1.677320e-02 1.166130e-01 3.426520e-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 0.0000848 0.0016063 0.9599999 0.9579120 0.623742 0.7821490 NA
1 54676 rs2462492 C T 0.0008050 0.0015917 0.6100002 0.6130323 0.400377 NA NA
1 86028 rs114608975 T C 0.0017382 0.0025440 0.4899999 0.4944618 0.103568 0.0277556 NA
1 91536 rs6702460 G T 0.0009551 0.0015669 0.5400003 0.5421523 0.456844 0.4207270 NA
1 234313 rs8179466 C T -0.0025407 0.0030903 0.4100001 0.4109983 0.074480 NA NA
1 534192 rs6680723 C T -0.0009679 0.0017903 0.5900000 0.5887701 0.240910 NA NA
1 546697 rs12025928 A G 0.0006449 0.0022336 0.7700005 0.7728008 0.913515 NA NA
1 693731 rs12238997 A G 0.0002075 0.0015002 0.8900000 0.8899821 0.116362 0.1417730 NA
1 705882 rs72631875 G A -0.0031691 0.0021984 0.1499999 0.1494204 0.067309 0.0315495 NA
1 706368 rs55727773 A G -0.0017688 0.0011113 0.1100001 0.1114603 0.515747 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0010668 0.0013406 0.4299995 0.4261603 0.138038 0.2052720 NA
22 51219387 rs9616832 T C 0.0028728 0.0017395 0.0990011 0.0986386 0.073837 0.0654952 NA
22 51219704 rs147475742 G A 0.0017752 0.0023311 0.4500005 0.4463385 0.042009 0.0473243 NA
22 51221190 rs369304721 G A 0.0028454 0.0023266 0.2200002 0.2213370 0.049801 NA NA
22 51221731 rs115055839 T C 0.0028627 0.0017406 0.1000000 0.1000383 0.073327 0.0625000 NA
22 51222100 rs114553188 G T 0.0003307 0.0020502 0.8700001 0.8718672 0.054488 0.0880591 NA
22 51223637 rs375798137 G A 0.0002354 0.0020601 0.9100000 0.9090330 0.054116 0.0788738 NA
22 51229805 rs9616985 T C 0.0027246 0.0017469 0.1199999 0.1188410 0.073165 0.0730831 NA
22 51232488 rs376461333 A G 0.0004612 0.0041158 0.9100000 0.9107844 0.020061 NA NA
22 51237063 rs3896457 T C 0.0007548 0.0010692 0.4799997 0.4801835 0.298069 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623742 ES:SE:LP:AF:ID  8.47687e-05:0.00160626:0.0177288:0.623742:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400377 ES:SE:LP:AF:ID  0.000805012:0.00159172:0.21467:0.400377:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103568 ES:SE:LP:AF:ID  0.00173817:0.00254405:0.309804:0.103568:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456844 ES:SE:LP:AF:ID  0.000955128:0.00156691:0.267606:0.456844:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07448  ES:SE:LP:AF:ID  -0.00254067:0.00309032:0.387216:0.07448:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24091  ES:SE:LP:AF:ID  -0.000967876:0.00179031:0.229148:0.24091:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913515 ES:SE:LP:AF:ID  0.000644873:0.00223361:0.113509:0.913515:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116362 ES:SE:LP:AF:ID  0.000207518:0.0015002:0.05061:0.116362:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067309 ES:SE:LP:AF:ID  -0.00316913:0.00219837:0.823909:0.067309:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515747 ES:SE:LP:AF:ID  -0.0017688:0.00111129:0.958607:0.515747:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032994 ES:SE:LP:AF:ID  -0.00603526:0.00280215:1.50864:0.032994:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036605 ES:SE:LP:AF:ID  -0.00538475:0.00254541:1.46852:0.036605:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036722 ES:SE:LP:AF:ID  -0.00569657:0.00253577:1.60206:0.036722:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036419 ES:SE:LP:AF:ID  -0.00552471:0.00255415:1.50864:0.036419:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016422 ES:SE:LP:AF:ID  0.00136216:0.00393093:0.136677:0.016422:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036959 ES:SE:LP:AF:ID  -0.00563252:0.00252582:1.58503:0.036959:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037059 ES:SE:LP:AF:ID  -0.00552354:0.00251695:1.55284:0.037059:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101235 ES:SE:LP:AF:ID  0.00244356:0.00183317:0.744727:0.101235:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95913  ES:SE:LP:AF:ID  0.00682904:0.00242818:2.3098:0.95913:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031459 ES:SE:LP:AF:ID  -0.000910043:0.00440351:0.0757207:0.031459:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053297 ES:SE:LP:AF:ID  -0.00203983:0.00350171:0.251812:0.053297:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03657  ES:SE:LP:AF:ID  -0.00565841:0.00253353:1.58503:0.03657:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036886 ES:SE:LP:AF:ID  -0.00548519:0.00251045:1.5376:0.036886:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843193 ES:SE:LP:AF:ID  0.00149795:0.00130023:0.60206:0.843193:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055913 ES:SE:LP:AF:ID  0.00026513:0.00210497:0.0457575:0.055913:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122336 ES:SE:LP:AF:ID  0.000166832:0.00142304:0.0409586:0.122336:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025694 ES:SE:LP:AF:ID  -4.47407e-05:0.00350228:0.00436481:0.025694:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121581 ES:SE:LP:AF:ID  0.000167214:0.00142362:0.0409586:0.121581:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132354 ES:SE:LP:AF:ID  -0.00160705:0.00140306:0.60206:0.132354:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011119 ES:SE:LP:AF:ID  -0.000308896:0.00510601:0.0222764:0.011119:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005702 ES:SE:LP:AF:ID  6.92849e-05:0.00658569:0.00436481:0.005702:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.0368   ES:SE:LP:AF:ID  -0.0053638:0.00248514:1.50864:0.0368:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83889  ES:SE:LP:AF:ID  0.00113261:0.00125893:0.431798:0.83889:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838514 ES:SE:LP:AF:ID  0.001213:0.00125753:0.481486:0.838514:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869719 ES:SE:LP:AF:ID  8.99748e-05:0.00134935:0.0222764:0.869719:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129941 ES:SE:LP:AF:ID  5.1993e-05:0.00135203:0.0132283:0.129941:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037316 ES:SE:LP:AF:ID  -0.00548132:0.00244278:1.60206:0.037316:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037559 ES:SE:LP:AF:ID  -0.00515445:0.00242737:1.46852:0.037559:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869061 ES:SE:LP:AF:ID  0.000186156:0.00134668:0.05061:0.869061:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869162 ES:SE:LP:AF:ID  0.000167991:0.00134723:0.0457575:0.869162:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03752  ES:SE:LP:AF:ID  -0.00540808:0.0024378:1.56864:0.03752:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869065 ES:SE:LP:AF:ID  0.000184833:0.00134665:0.05061:0.869065:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00514  ES:SE:LP:AF:ID  0.00953725:0.00690182:0.769551:0.00514:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005106 ES:SE:LP:AF:ID  0.00940297:0.00691993:0.769551:0.005106:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837964 ES:SE:LP:AF:ID  0.00127595:0.00125404:0.508638:0.837964:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037534 ES:SE:LP:AF:ID  -0.00539526:0.00244116:1.56864:0.037534:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838595 ES:SE:LP:AF:ID  0.00129405:0.00125756:0.522879:0.838595:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013765 ES:SE:LP:AF:ID  -0.00513476:0.0043925:0.619789:0.013765:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005546 ES:SE:LP:AF:ID  -0.00232733:0.00677351:0.136677:0.005546:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839711 ES:SE:LP:AF:ID  0.00122322:0.00127463:0.468521:0.839711:rs3131965