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-16878/UKB-b-16878_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16878/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16878/UKB-b-16878_data.vcf.gz ...
Read summary statistics for 9349000 SNPs.
Dropped 10594 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, 1288045 SNPs remain.
After merging with regression SNP LD, 1288045 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1002 (0.0044)
Lambda GC: 1.466
Mean Chi^2: 1.5551
Intercept: 1.097 (0.009)
Ratio: 0.1748 (0.0161)
Analysis finished at Thu Oct 17 14:46:49 2019
Total time elapsed: 1.0m:30.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 35,
    "n_p_sig": 1759,
    "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": 116872,
    "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": 1288045,
    "ldsc_nsnp_merge_regression_ld": 1288045,
    "ldsc_observed_scale_h2_beta": 0.1002,
    "ldsc_observed_scale_h2_se": 0.0044,
    "ldsc_intercept_beta": 1.097,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.466,
    "ldsc_mean_chisq": 1.5551,
    "ldsc_ratio": 0.1747
}

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 1.000000 3 58 0 9338460 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9349000 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.633074e+00 5.753489e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.881905e+07 5.630759e+07 828.0000000 3.250983e+07 6.940287e+07 1.145482e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -3.580000e-05 5.277200e-03 -0.0836675 -2.090600e-03 -2.460000e-05 2.034600e-03 6.518730e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 3.827900e-03 3.063200e-03 0.0012673 1.526600e-03 2.422200e-03 5.239700e-03 4.324070e-02 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.529408e-01 3.009911e-01 0.0000000 1.800002e-01 4.400003e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.529420e-01 3.009672e-01 0.0000000 1.800036e-01 4.358903e-01 7.134630e-01 9.999999e-01 ▇▆▆▅▅
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.128399e-01 2.576816e-01 0.0022000 1.707900e-02 9.117200e-02 3.339682e-01 9.978000e-01 ▇▂▁▁▁
numeric AF_reference 116872 0.987499 NA NA NA NA NA NA NA 2.139643e-01 2.494694e-01 0.0000000 1.437700e-02 1.098240e-01 3.342650e-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 0.0048455 0.0023320 0.0379997 0.0377217 0.623723 0.7821490 NA
1 54676 rs2462492 C T 0.0006846 0.0023085 0.7700005 0.7668199 0.400268 NA NA
1 86028 rs114608975 T C -0.0089785 0.0036910 0.0150000 0.0149924 0.103598 0.0277556 NA
1 91536 rs6702460 G T 0.0015681 0.0022778 0.4899999 0.4911837 0.456676 0.4207270 NA
1 234313 rs8179466 C T -0.0000882 0.0044803 0.9800000 0.9842950 0.074618 NA NA
1 534192 rs6680723 C T -0.0013672 0.0026044 0.5999997 0.5996176 0.240565 NA NA
1 546697 rs12025928 A G -0.0040478 0.0032353 0.2099999 0.2108903 0.913210 NA NA
1 693731 rs12238997 A G -0.0015021 0.0021752 0.4899999 0.4898445 0.116419 0.1417730 NA
1 705882 rs72631875 G A 0.0013934 0.0031781 0.6600001 0.6610760 0.067652 0.0315495 NA
1 706368 rs55727773 A G 0.0033989 0.0016134 0.0350002 0.0351418 0.515988 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0011316 0.0019519 0.5600000 0.5620999 0.137231 0.2052720 NA
22 51219387 rs9616832 T C 0.0015771 0.0025330 0.5300002 0.5335450 0.073341 0.0654952 NA
22 51219704 rs147475742 G A -0.0013464 0.0033948 0.6899999 0.6916494 0.041747 0.0473243 NA
22 51221190 rs369304721 G A 0.0002820 0.0033902 0.9299999 0.9337164 0.049391 NA NA
22 51221731 rs115055839 T C 0.0018310 0.0025344 0.4700002 0.4700150 0.072855 0.0625000 NA
22 51222100 rs114553188 G T -0.0039875 0.0029877 0.1800002 0.1819950 0.054081 0.0880591 NA
22 51223637 rs375798137 G A -0.0040254 0.0030025 0.1800002 0.1800249 0.053708 0.0788738 NA
22 51229805 rs9616985 T C 0.0017946 0.0025432 0.4799997 0.4804014 0.072710 0.0730831 NA
22 51232488 rs376461333 A G 0.0000327 0.0060235 1.0000000 0.9956697 0.019811 NA NA
22 51237063 rs3896457 T C 0.0015569 0.0015538 0.3200000 0.3163646 0.298087 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623723 ES:SE:LP:AF:ID  0.00484552:0.00233197:1.42022:0.623723:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400268 ES:SE:LP:AF:ID  0.000684553:0.00230849:0.113509:0.400268:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103598 ES:SE:LP:AF:ID  -0.00897854:0.00369098:1.82391:0.103598:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456676 ES:SE:LP:AF:ID  0.0015681:0.0022778:0.309804:0.456676:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074618 ES:SE:LP:AF:ID  -8.81924e-05:0.00448028:0.00877392:0.074618:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240565 ES:SE:LP:AF:ID  -0.00136716:0.00260436:0.221849:0.240565:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91321  ES:SE:LP:AF:ID  -0.00404779:0.00323533:0.677781:0.91321:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116419 ES:SE:LP:AF:ID  -0.00150207:0.00217516:0.309804:0.116419:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067652 ES:SE:LP:AF:ID  0.00139339:0.00317815:0.180456:0.067652:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515988 ES:SE:LP:AF:ID  0.00339892:0.00161337:1.45593:0.515988:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033222 ES:SE:LP:AF:ID  0.0021451:0.00404852:0.221849:0.033222:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03689  ES:SE:LP:AF:ID  0.00173026:0.0036766:0.19382:0.03689:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037016 ES:SE:LP:AF:ID  0.00201007:0.0036622:0.236572:0.037016:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036718 ES:SE:LP:AF:ID  0.00197343:0.0036886:0.229148:0.036718:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016347 ES:SE:LP:AF:ID  0.00295162:0.00571448:0.21467:0.016347:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03726  ES:SE:LP:AF:ID  0.0015723:0.0036473:0.173925:0.03726:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037335 ES:SE:LP:AF:ID  0.00173436:0.00363658:0.200659:0.037335:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101216 ES:SE:LP:AF:ID  -0.00270457:0.00265944:0.508638:0.101216:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958896 ES:SE:LP:AF:ID  -0.0015098:0.00351323:0.173925:0.958896:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031582 ES:SE:LP:AF:ID  0.00131349:0.0063676:0.0757207:0.031582:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052953 ES:SE:LP:AF:ID  0.0023786:0.00510749:0.19382:0.052953:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036857 ES:SE:LP:AF:ID  0.00144398:0.00366024:0.161151:0.036857:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037206 ES:SE:LP:AF:ID  0.00128958:0.00362565:0.142668:0.037206:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842996 ES:SE:LP:AF:ID  0.00148067:0.00188427:0.366532:0.842996:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056088 ES:SE:LP:AF:ID  -0.00246687:0.00304896:0.376751:0.056088:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122295 ES:SE:LP:AF:ID  -0.00193063:0.00206502:0.455932:0.122295:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025682 ES:SE:LP:AF:ID  0.00610598:0.00508396:0.638272:0.025682:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121545 ES:SE:LP:AF:ID  -0.00181514:0.00206597:0.420216:0.121545:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132719 ES:SE:LP:AF:ID  -0.00181506:0.00203235:0.431798:0.132719:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011039 ES:SE:LP:AF:ID  0.00669154:0.00744137:0.431798:0.011039:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005677 ES:SE:LP:AF:ID  -0.000164232:0.00956079:0.00436481:0.005677:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037165 ES:SE:LP:AF:ID  0.00140817:0.00358612:0.161151:0.037165:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838853 ES:SE:LP:AF:ID  0.00229814:0.00182593:0.677781:0.838853:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838498 ES:SE:LP:AF:ID  0.00237437:0.00182427:0.721246:0.838498:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869938 ES:SE:LP:AF:ID  0.00261642:0.00195893:0.744727:0.869938:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129735 ES:SE:LP:AF:ID  -0.00277851:0.00196319:0.79588:0.129735:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037677 ES:SE:LP:AF:ID  0.00199813:0.00352672:0.244125:0.037677:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037914 ES:SE:LP:AF:ID  0.00207753:0.00350498:0.259637:0.037914:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869307 ES:SE:LP:AF:ID  0.00268122:0.00195533:0.769551:0.869307:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869414 ES:SE:LP:AF:ID  0.00273573:0.00195621:0.79588:0.869414:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037863 ES:SE:LP:AF:ID  0.00228164:0.00352035:0.283997:0.037863:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869311 ES:SE:LP:AF:ID  0.00266729:0.00195536:0.769551:0.869311:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005108 ES:SE:LP:AF:ID  -0.0173235:0.0100306:1.07572:0.005108:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00507  ES:SE:LP:AF:ID  -0.0170956:0.0100587:1.05061:0.00507:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83797  ES:SE:LP:AF:ID  0.00231666:0.00181942:0.69897:0.83797:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037864 ES:SE:LP:AF:ID  0.00235439:0.00352578:0.30103:0.037864:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83861  ES:SE:LP:AF:ID  0.00234553:0.00182467:0.69897:0.83861:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013769 ES:SE:LP:AF:ID  0.0063764:0.00635983:0.49485:0.013769:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005512 ES:SE:LP:AF:ID  0.0059876:0.00983437:0.267606:0.005512:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839761 ES:SE:LP:AF:ID  0.00246906:0.00184908:0.744727:0.839761:rs3131965