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-16399/UKB-b-16399_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16399/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:00 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16399/UKB-b-16399_data.vcf.gz ...
Read summary statistics for 8726424 SNPs.
Dropped 7651 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, 1286067 SNPs remain.
After merging with regression SNP LD, 1286067 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0253 (0.0016)
Lambda GC: 1.2817
Mean Chi^2: 1.3074
Intercept: 1.0768 (0.0084)
Ratio: 0.2499 (0.0274)
Analysis finished at Thu Oct 17 14:46:36 2019
Total time elapsed: 1.0m:35.95s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9466,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 271,
    "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": 85126,
    "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": 1286067,
    "ldsc_nsnp_merge_regression_ld": 1286067,
    "ldsc_observed_scale_h2_beta": 0.0253,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0768,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.2817,
    "ldsc_mean_chisq": 1.3074,
    "ldsc_ratio": 0.2498
}

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 1.000000 3 58 0 8718808 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 8726424 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 8.649952e+00 5.761061e+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 7.877398e+07 5.636164e+07 828.0000000 3.239649e+07 6.931060e+07 1.145666e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 1.860000e-05 2.405100e-03 -0.0244118 -1.024000e-03 8.000000e-06 1.042200e-03 2.819560e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.859000e-03 1.292000e-03 0.0007212 8.524000e-04 1.269200e-03 2.524000e-03 1.281120e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.679205e-01 2.974960e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.679199e-01 2.974698e-01 0.0000000 2.018980e-01 4.557798e-01 7.259569e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.266501e-01 2.592477e-01 0.0049540 2.387800e-02 1.104520e-01 3.583200e-01 9.950460e-01 ▇▂▁▁▁
numeric AF_reference 85126 0.990245 NA NA NA NA NA NA NA 2.264862e-01 2.512204e-01 0.0000000 2.156550e-02 1.271960e-01 3.556310e-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 0.0010600 0.0013266 0.4199997 0.4242866 0.623772 0.7821490 NA
1 54676 rs2462492 C T 0.0007423 0.0013145 0.5700002 0.5722589 0.400419 NA NA
1 86028 rs114608975 T C -0.0024530 0.0021017 0.2399999 0.2431580 0.103548 0.0277556 NA
1 91536 rs6702460 G T 0.0018443 0.0012941 0.1499999 0.1541153 0.456874 0.4207270 NA
1 234313 rs8179466 C T 0.0027419 0.0025516 0.2800000 0.2825680 0.074513 NA NA
1 534192 rs6680723 C T 0.0005784 0.0014784 0.6999999 0.6956548 0.240932 NA NA
1 546697 rs12025928 A G -0.0012973 0.0018442 0.4799997 0.4817857 0.913477 NA NA
1 693731 rs12238997 A G 0.0000391 0.0012390 0.9699999 0.9748178 0.116331 0.1417730 NA
1 705882 rs72631875 G A -0.0005105 0.0018155 0.7800007 0.7785792 0.067286 0.0315495 NA
1 706368 rs55727773 A G -0.0011552 0.0009178 0.2099999 0.2081514 0.515679 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0003987 0.0011076 0.7199992 0.7189049 0.137956 0.2052720 NA
22 51219387 rs9616832 T C 0.0010803 0.0014377 0.4500005 0.4523974 0.073742 0.0654952 NA
22 51219704 rs147475742 G A 0.0009350 0.0019265 0.6300007 0.6274252 0.041957 0.0473243 NA
22 51221190 rs369304721 G A 0.0015189 0.0019232 0.4299995 0.4296734 0.049736 NA NA
22 51221731 rs115055839 T C 0.0010952 0.0014386 0.4500005 0.4464773 0.073232 0.0625000 NA
22 51222100 rs114553188 G T 0.0001423 0.0016936 0.9299999 0.9330603 0.054464 0.0880591 NA
22 51223637 rs375798137 G A 0.0000534 0.0017018 0.9699999 0.9749900 0.054093 0.0788738 NA
22 51229805 rs9616985 T C 0.0010981 0.0014438 0.4500005 0.4468988 0.073068 0.0730831 NA
22 51232488 rs376461333 A G -0.0013345 0.0034016 0.6899999 0.6948230 0.020040 NA NA
22 51237063 rs3896457 T C 0.0006985 0.0008831 0.4299995 0.4289617 0.297982 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  0.00105997:0.00132661:0.376751:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400419 ES:SE:LP:AF:ID  0.000742329:0.00131449:0.244125:0.400419:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103548 ES:SE:LP:AF:ID  -0.00245298:0.00210172:0.619789:0.103548:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456874 ES:SE:LP:AF:ID  0.00184428:0.0012941:0.823909:0.456874:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074513 ES:SE:LP:AF:ID  0.00274189:0.00255162:0.552842:0.074513:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240932 ES:SE:LP:AF:ID  0.000578355:0.00147844:0.154902:0.240932:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913477 ES:SE:LP:AF:ID  -0.0012973:0.00184424:0.318759:0.913477:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116331 ES:SE:LP:AF:ID  3.91095e-05:0.00123896:0.0132283:0.116331:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067286 ES:SE:LP:AF:ID  -0.000510466:0.0018155:0.107905:0.067286:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515679 ES:SE:LP:AF:ID  -0.00115518:0.000917782:0.677781:0.515679:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033016 ES:SE:LP:AF:ID  0.00413719:0.00231318:1.13077:0.033016:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036632 ES:SE:LP:AF:ID  0.00381488:0.00210119:1.16115:0.036632:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036749 ES:SE:LP:AF:ID  0.00350669:0.00209325:1.02687:0.036749:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036447 ES:SE:LP:AF:ID  0.00320051:0.00210836:0.886057:0.036447:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016416 ES:SE:LP:AF:ID  0.000143432:0.00324579:0.0177288:0.016416:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036987 ES:SE:LP:AF:ID  0.00348:0.00208499:1.02228:0.036987:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037084 ES:SE:LP:AF:ID  0.00345382:0.00207782:1.01773:0.037084:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101201 ES:SE:LP:AF:ID  0.000348949:0.00151418:0.0861861:0.101201:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959083 ES:SE:LP:AF:ID  -0.00363257:0.002004:1.1549:0.959083:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031442 ES:SE:LP:AF:ID  -0.0010436:0.00363986:0.113509:0.031442:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053265 ES:SE:LP:AF:ID  -0.00481038:0.00289372:1.01773:0.053265:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036602 ES:SE:LP:AF:ID  0.003144:0.00209127:0.886057:0.036602:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036918 ES:SE:LP:AF:ID  0.00333069:0.00207226:0.958607:0.036918:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843192 ES:SE:LP:AF:ID  -0.00109289:0.00107368:0.508638:0.843192:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055915 ES:SE:LP:AF:ID  0.000109434:0.00173844:0.0222764:0.055915:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122316 ES:SE:LP:AF:ID  7.61269e-05:0.00117527:0.0222764:0.122316:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02571  ES:SE:LP:AF:ID  -0.0022754:0.00289092:0.366532:0.02571:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121559 ES:SE:LP:AF:ID  0.000188007:0.00117576:0.0604807:0.121559:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132341 ES:SE:LP:AF:ID  0.00103278:0.00115882:0.431798:0.132341:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  -0.00107756:0.00421411:0.09691:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005704 ES:SE:LP:AF:ID  -0.000414091:0.00543629:0.0268721:0.005704:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036833 ES:SE:LP:AF:ID  0.0034185:0.00205128:1.01773:0.036833:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838938 ES:SE:LP:AF:ID  -0.00119355:0.00103981:0.60206:0.838938:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838565 ES:SE:LP:AF:ID  -0.00120078:0.00103868:0.60206:0.838565:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869775 ES:SE:LP:AF:ID  -0.000366359:0.00111457:0.130768:0.869775:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129875 ES:SE:LP:AF:ID  0.000366093:0.00111685:0.130768:0.129875:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037345 ES:SE:LP:AF:ID  0.00317893:0.00201648:0.958607:0.037345:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037589 ES:SE:LP:AF:ID  0.00304118:0.00200376:0.886057:0.037589:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.000375575:0.00111239:0.130768:0.869117:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  -0.000333143:0.00111282:0.119186:0.869215:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037547 ES:SE:LP:AF:ID  0.00333512:0.0020124:1.01323:0.037547:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86912  ES:SE:LP:AF:ID  -0.000405837:0.00111237:0.142668:0.86912:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005118 ES:SE:LP:AF:ID  0.00303345:0.0057141:0.221849:0.005118:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005084 ES:SE:LP:AF:ID  0.00304396:0.00572905:0.221849:0.005084:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838019 ES:SE:LP:AF:ID  -0.00111304:0.0010358:0.552842:0.838019:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03756  ES:SE:LP:AF:ID  0.00334081:0.00201524:1.01323:0.03756:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83865  ES:SE:LP:AF:ID  -0.00105394:0.00103872:0.508638:0.83865:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013768 ES:SE:LP:AF:ID  0.000930208:0.00362657:0.09691:0.013768:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005542 ES:SE:LP:AF:ID  -0.000771302:0.00559597:0.05061:0.005542:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839765 ES:SE:LP:AF:ID  -0.00119855:0.00105277:0.60206:0.839765:rs3131965