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-10591/UKB-b-10591_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10591/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10591/UKB-b-10591_data.vcf.gz ...
Read summary statistics for 8757015 SNPs.
Dropped 7746 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, 1286196 SNPs remain.
After merging with regression SNP LD, 1286196 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0323 (0.0017)
Lambda GC: 1.28
Mean Chi^2: 1.3237
Intercept: 1.0337 (0.0075)
Ratio: 0.1042 (0.0233)
Analysis finished at Thu Oct 17 14:41:55 2019
Total time elapsed: 1.0m:36.27s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9467,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 7,
    "n_p_sig": 72,
    "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": 85789,
    "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": 1286196,
    "ldsc_nsnp_merge_regression_ld": 1286196,
    "ldsc_observed_scale_h2_beta": 0.0323,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.0337,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.28,
    "ldsc_mean_chisq": 1.3237,
    "ldsc_ratio": 0.1041
}

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 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 8749306 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 8757015 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 8.649485e+00 5.760663e+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 7.877245e+07 5.635519e+07 828.0000000 3.239918e+07 6.931602e+07 1.145581e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.480000e-05 2.441200e-03 -0.0247565 -1.047100e-03 7.100000e-06 1.060700e-03 2.683320e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.911600e-03 1.335500e-03 0.0007365 8.713000e-04 1.301500e-03 2.599900e-03 1.310800e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.697052e-01 2.971676e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.697065e-01 2.971429e-01 0.0000000 2.041874e-01 4.594257e-01 7.272656e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.259183e-01 2.591704e-01 0.0047910 2.348700e-02 1.094270e-01 3.570765e-01 9.952090e-01 ▇▂▁▁▁
numeric AF_reference 85789 0.9902034 NA NA NA NA NA NA NA 2.257986e-01 2.511318e-01 0.0000000 2.096650e-02 1.261980e-01 3.544330e-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 -0.0007750 0.0013551 0.5700002 0.5674106 0.623747 0.7821490 NA
1 54676 rs2462492 C T -0.0010397 0.0013423 0.4400003 0.4385966 0.400443 NA NA
1 86028 rs114608975 T C 0.0015719 0.0021460 0.4600002 0.4638721 0.103552 0.0277556 NA
1 91536 rs6702460 G T -0.0018053 0.0013218 0.1700000 0.1720205 0.456920 0.4207270 NA
1 234313 rs8179466 C T 0.0029580 0.0026068 0.2599998 0.2564935 0.074503 NA NA
1 534192 rs6680723 C T 0.0017583 0.0015100 0.2399999 0.2442701 0.240956 NA NA
1 546697 rs12025928 A G 0.0007198 0.0018834 0.6999999 0.7023119 0.913464 NA NA
1 693731 rs12238997 A G -0.0013176 0.0012654 0.2999998 0.2977737 0.116322 0.1417730 NA
1 705882 rs72631875 G A -0.0020222 0.0018540 0.2800000 0.2753819 0.067283 0.0315495 NA
1 706368 rs55727773 A G -0.0007285 0.0009373 0.4400003 0.4370462 0.515665 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0000398 0.0011312 0.9699999 0.9719485 0.137911 0.2052720 NA
22 51219387 rs9616832 T C 0.0007334 0.0014687 0.6200004 0.6175287 0.073690 0.0654952 NA
22 51219704 rs147475742 G A -0.0012952 0.0019679 0.5099998 0.5104253 0.041926 0.0473243 NA
22 51221190 rs369304721 G A 0.0014927 0.0019651 0.4500005 0.4474905 0.049689 NA NA
22 51221731 rs115055839 T C 0.0008428 0.0014696 0.5700002 0.5663190 0.073177 0.0625000 NA
22 51222100 rs114553188 G T -0.0008814 0.0017293 0.6100002 0.6102820 0.054491 0.0880591 NA
22 51223637 rs375798137 G A -0.0009449 0.0017376 0.5900000 0.5865901 0.054121 0.0788738 NA
22 51229805 rs9616985 T C 0.0010085 0.0014749 0.4899999 0.4941329 0.073014 0.0730831 NA
22 51232488 rs376461333 A G -0.0032755 0.0034731 0.3500000 0.3456211 0.020050 NA NA
22 51237063 rs3896457 T C 0.0025070 0.0009019 0.0054000 0.0054421 0.297899 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623747 ES:SE:LP:AF:ID  -0.000774957:0.00135513:0.244125:0.623747:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400443 ES:SE:LP:AF:ID  -0.00103973:0.00134234:0.356547:0.400443:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103552 ES:SE:LP:AF:ID  0.0015719:0.00214598:0.337242:0.103552:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45692  ES:SE:LP:AF:ID  -0.00180529:0.00132184:0.769551:0.45692:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074503 ES:SE:LP:AF:ID  0.00295796:0.00260678:0.585027:0.074503:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  0.00175826:0.00151004:0.619789:0.240956:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913464 ES:SE:LP:AF:ID  0.000719846:0.00188342:0.154902:0.913464:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116322 ES:SE:LP:AF:ID  -0.00131758:0.00126542:0.522879:0.116322:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067283 ES:SE:LP:AF:ID  -0.0020222:0.00185395:0.552842:0.067283:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515665 ES:SE:LP:AF:ID  -0.000728461:0.0009373:0.356547:0.515665:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033001 ES:SE:LP:AF:ID  0.00102082:0.00236314:0.173925:0.033001:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03662  ES:SE:LP:AF:ID  0.00130062:0.00214638:0.267606:0.03662:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036738 ES:SE:LP:AF:ID  0.00131542:0.00213821:0.267606:0.036738:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036436 ES:SE:LP:AF:ID  0.00134643:0.00215365:0.275724:0.036436:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016376 ES:SE:LP:AF:ID  0.000679348:0.00332017:0.0757207:0.016376:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036978 ES:SE:LP:AF:ID  0.00138096:0.00212967:0.283997:0.036978:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037074 ES:SE:LP:AF:ID  0.00148194:0.00212243:0.309804:0.037074:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  -0.00206001:0.00154624:0.744727:0.101206:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959101 ES:SE:LP:AF:ID  -0.00087368:0.00204724:0.173925:0.959101:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031444 ES:SE:LP:AF:ID  0.000787343:0.00371645:0.0809219:0.031444:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053261 ES:SE:LP:AF:ID  -0.00509851:0.00295533:1.07572:0.053261:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036589 ES:SE:LP:AF:ID  0.00133124:0.00213625:0.275724:0.036589:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036909 ES:SE:LP:AF:ID  0.00126444:0.00211668:0.259637:0.036909:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843224 ES:SE:LP:AF:ID  0.00107082:0.00109666:0.481486:0.843224:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055914 ES:SE:LP:AF:ID  -0.00156775:0.0017754:0.420216:0.055914:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122298 ES:SE:LP:AF:ID  -0.00150687:0.00120036:0.677781:0.122298:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025704 ES:SE:LP:AF:ID  0.00104594:0.00295305:0.142668:0.025704:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121538 ES:SE:LP:AF:ID  -0.00144405:0.00120089:0.638272:0.121538:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132351 ES:SE:LP:AF:ID  -0.00164691:0.00118346:0.79588:0.132351:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011126 ES:SE:LP:AF:ID  0.00191487:0.0043048:0.180456:0.011126:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005705 ES:SE:LP:AF:ID  -0.0116999:0.00555256:1.45593:0.005705:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036823 ES:SE:LP:AF:ID  0.000701353:0.00209531:0.130768:0.036823:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838957 ES:SE:LP:AF:ID  0.00073906:0.00106202:0.309804:0.838957:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838584 ES:SE:LP:AF:ID  0.000740465:0.00106087:0.309804:0.838584:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869794 ES:SE:LP:AF:ID  0.000994592:0.00113837:0.420216:0.869794:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129857 ES:SE:LP:AF:ID  -0.00108469:0.00114071:0.468521:0.129857:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037333 ES:SE:LP:AF:ID  0.000834434:0.00205981:0.161151:0.037333:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037576 ES:SE:LP:AF:ID  0.00086744:0.00204683:0.173925:0.037576:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869136 ES:SE:LP:AF:ID  0.00108567:0.00113616:0.468521:0.869136:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869235 ES:SE:LP:AF:ID  0.00109016:0.00113662:0.468521:0.869235:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  0.000954437:0.00205566:0.19382:0.037535:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869139 ES:SE:LP:AF:ID  0.00107972:0.00113614:0.468521:0.869139:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00512  ES:SE:LP:AF:ID  0.00357406:0.00583721:0.267606:0.00512:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005086 ES:SE:LP:AF:ID  0.00380654:0.00585251:0.283997:0.005086:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838041 ES:SE:LP:AF:ID  0.000773066:0.00105795:0.337242:0.838041:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037548 ES:SE:LP:AF:ID  0.00103866:0.00205854:0.21467:0.037548:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838673 ES:SE:LP:AF:ID  0.000732889:0.00106093:0.309804:0.838673:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013799 ES:SE:LP:AF:ID  0.00400773:0.00369901:0.552842:0.013799:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005548 ES:SE:LP:AF:ID  -0.00443982:0.00571248:0.356547:0.005548:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839786 ES:SE:LP:AF:ID  0.000815598:0.00107529:0.346787:0.839786:rs3131965