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-19066/UKB-b-19066_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19066/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19066/UKB-b-19066_data.vcf.gz ...
Read summary statistics for 9668097 SNPs.
Dropped 13136 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, 1288728 SNPs remain.
After merging with regression SNP LD, 1288728 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.014 (0.0017)
Lambda GC: 1.1116
Mean Chi^2: 1.1218
Intercept: 1.0241 (0.0072)
Ratio: 0.198 (0.0589)
Analysis finished at Thu Oct 17 14:42:36 2019
Total time elapsed: 1.0m:41.45s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9493,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 160568,
    "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": 1288728,
    "ldsc_nsnp_merge_regression_ld": 1288728,
    "ldsc_observed_scale_h2_beta": 0.014,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.0241,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.1116,
    "ldsc_mean_chisq": 1.1218,
    "ldsc_ratio": 0.1979
}

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 1.000000 3 58 0 9655024 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 9668097 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 8.625816e+00 5.749956e+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 7.883637e+07 5.628738e+07 828.0000000 3.256392e+07 6.944265e+07 1.145589e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 1.050000e-05 4.220200e-03 -0.0746208 -1.372200e-03 7.900000e-06 1.398300e-03 5.885830e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 3.109900e-03 2.770300e-03 0.0009276 1.128600e-03 1.854600e-03 4.182600e-03 4.899640e-02 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.877029e-01 2.923514e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.877040e-01 2.923259e-01 0.0000000 2.311774e-01 4.841682e-01 7.408275e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.065191e-01 2.568983e-01 0.0012980 1.444800e-02 8.237800e-02 3.224510e-01 9.987020e-01 ▇▂▁▁▁
numeric AF_reference 160568 0.983392 NA NA NA NA NA NA NA 2.089370e-01 2.485864e-01 0.0000000 1.238020e-02 1.030350e-01 3.248800e-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 -0.0003563 0.0017063 0.8300000 0.8346082 0.624025 0.7821490 NA
1 54676 rs2462492 C T -0.0007492 0.0016901 0.6600001 0.6575616 0.400692 NA NA
1 86028 rs114608975 T C 0.0043168 0.0027021 0.1100001 0.1101310 0.103524 0.0277556 NA
1 91536 rs6702460 G T -0.0015027 0.0016642 0.3700002 0.3665554 0.457113 0.4207270 NA
1 234313 rs8179466 C T -0.0033846 0.0032902 0.2999998 0.3036189 0.074356 NA NA
1 534192 rs6680723 C T -0.0000315 0.0019001 0.9900000 0.9867604 0.241112 NA NA
1 546697 rs12025928 A G -0.0021811 0.0023727 0.3599996 0.3579678 0.913454 NA NA
1 693731 rs12238997 A G 0.0021504 0.0015928 0.1800002 0.1769729 0.116533 0.1417730 NA
1 705882 rs72631875 G A 0.0025612 0.0023348 0.2700001 0.2726655 0.067299 0.0315495 NA
1 706368 rs55727773 A G 0.0013001 0.0011802 0.2700001 0.2706494 0.516019 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0022734 0.0024839 0.3599996 0.3600575 0.041720 0.0473243 NA
22 51219766 rs182321900 C T -0.0111131 0.0118508 0.3500000 0.3483724 0.001842 NA NA
22 51220146 rs868950473 C T -0.0110339 0.0117369 0.3500000 0.3471645 0.001892 NA NA
22 51221190 rs369304721 G A 0.0012179 0.0024773 0.6200004 0.6229881 0.049485 NA NA
22 51221731 rs115055839 T C 0.0012387 0.0018532 0.5000000 0.5038503 0.072924 0.0625000 NA
22 51222100 rs114553188 G T -0.0008419 0.0021745 0.6999999 0.6986359 0.054681 0.0880591 NA
22 51223637 rs375798137 G A -0.0008206 0.0021849 0.7099994 0.7072250 0.054322 0.0788738 NA
22 51229805 rs9616985 T C 0.0012375 0.0018600 0.5099998 0.5058591 0.072740 0.0730831 NA
22 51232488 rs376461333 A G -0.0032692 0.0043548 0.4500005 0.4528178 0.020176 NA NA
22 51237063 rs3896457 T C 0.0009280 0.0011360 0.4100001 0.4139903 0.297991 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624025 ES:SE:LP:AF:ID  -0.000356265:0.00170629:0.0809219:0.624025:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400692 ES:SE:LP:AF:ID  -0.000749178:0.00169007:0.180456:0.400692:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103524 ES:SE:LP:AF:ID  0.00431684:0.00270207:0.958607:0.103524:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457113 ES:SE:LP:AF:ID  -0.00150268:0.0016642:0.431798:0.457113:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074356 ES:SE:LP:AF:ID  -0.00338459:0.00329015:0.522879:0.074356:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241112 ES:SE:LP:AF:ID  -3.15308e-05:0.00190012:0.00436481:0.241112:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913454 ES:SE:LP:AF:ID  -0.0021811:0.00237271:0.443698:0.913454:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116533 ES:SE:LP:AF:ID  0.00215044:0.00159276:0.744727:0.116533:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067299 ES:SE:LP:AF:ID  0.00256118:0.00233483:0.568636:0.067299:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516019 ES:SE:LP:AF:ID  0.00130006:0.00118019:0.568636:0.516019:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032932 ES:SE:LP:AF:ID  -0.0018548:0.00298009:0.275724:0.032932:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036539 ES:SE:LP:AF:ID  -0.00160921:0.00270631:0.259637:0.036539:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036647 ES:SE:LP:AF:ID  -0.00139789:0.00269644:0.221849:0.036647:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036358 ES:SE:LP:AF:ID  -0.00146748:0.00271528:0.229148:0.036358:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016417 ES:SE:LP:AF:ID  -0.00149795:0.0041752:0.142668:0.016417:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036878 ES:SE:LP:AF:ID  -0.00166417:0.00268595:0.267606:0.036878:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036975 ES:SE:LP:AF:ID  -0.00165323:0.00267669:0.267606:0.036975:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101341 ES:SE:LP:AF:ID  0.00112451:0.00194485:0.251812:0.101341:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959496 ES:SE:LP:AF:ID  0.00105378:0.00259114:0.167491:0.959496:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031474 ES:SE:LP:AF:ID  -0.00749329:0.00467732:0.958607:0.031474:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053151 ES:SE:LP:AF:ID  -0.00813483:0.00372531:1.5376:0.053151:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036509 ES:SE:LP:AF:ID  -0.00104315:0.00269345:0.154902:0.036509:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036799 ES:SE:LP:AF:ID  -0.0013649:0.00266947:0.21467:0.036799:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843356 ES:SE:LP:AF:ID  -0.00111506:0.00138232:0.376751:0.843356:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056236 ES:SE:LP:AF:ID  0.0005124:0.00223138:0.0861861:0.056236:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12255  ES:SE:LP:AF:ID  0.00196277:0.00151082:0.721246:0.12255:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025757 ES:SE:LP:AF:ID  0.00378463:0.00371424:0.508638:0.025757:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121808 ES:SE:LP:AF:ID  0.00196745:0.00151134:0.721246:0.121808:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132564 ES:SE:LP:AF:ID  0.00167103:0.0014897:0.585027:0.132564:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011115 ES:SE:LP:AF:ID  -0.00289376:0.0054251:0.229148:0.011115:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  0.0136769:0.00700447:1.29243:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002088 ES:SE:LP:AF:ID  0.00661852:0.0123352:0.229148:0.002088:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036726 ES:SE:LP:AF:ID  -0.00144283:0.00264243:0.229148:0.036726:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838977 ES:SE:LP:AF:ID  -0.000821089:0.00133817:0.267606:0.838977:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838692 ES:SE:LP:AF:ID  -0.000913782:0.00133709:0.309804:0.838692:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869721 ES:SE:LP:AF:ID  -0.00154985:0.00143433:0.552842:0.869721:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129867 ES:SE:LP:AF:ID  0.00159418:0.0014374:0.568636:0.129867:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037242 ES:SE:LP:AF:ID  -0.00239035:0.00259748:0.443698:0.037242:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037481 ES:SE:LP:AF:ID  -0.00229888:0.00258116:0.431798:0.037481:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  -0.0016231:0.0014319:0.585027:0.869154:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869251 ES:SE:LP:AF:ID  -0.00162731:0.00143241:0.585027:0.869251:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037446 ES:SE:LP:AF:ID  -0.00234341:0.00259222:0.431798:0.037446:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869155 ES:SE:LP:AF:ID  -0.00163591:0.00143186:0.60206:0.869155:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005109 ES:SE:LP:AF:ID  0.00371849:0.00735869:0.21467:0.005109:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005075 ES:SE:LP:AF:ID  0.00361357:0.00737773:0.207608:0.005075:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838133 ES:SE:LP:AF:ID  -0.000852662:0.00133332:0.283997:0.838133:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037464 ES:SE:LP:AF:ID  -0.00220146:0.00259563:0.39794:0.037464:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838766 ES:SE:LP:AF:ID  -0.00088709:0.00133709:0.29243:0.838766:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  -0.0025875:0.00466215:0.236572:0.013775:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005547 ES:SE:LP:AF:ID  -0.00875773:0.00719082:0.657577:0.005547:rs184270342