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-11348/UKB-b-11348_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11348/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11348/UKB-b-11348_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0475 (0.0022)
Lambda GC: 1.3894
Mean Chi^2: 1.471
Intercept: 1.0481 (0.008)
Ratio: 0.1021 (0.0169)
Analysis finished at Thu Oct 17 14:42:08 2019
Total time elapsed: 1.0m:50.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 32,
    "n_p_sig": 2708,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.0475,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0481,
    "ldsc_intercept_se": 0.008,
    "ldsc_lambda_gc": 1.3894,
    "ldsc_mean_chisq": 1.471,
    "ldsc_ratio": 0.1021
}

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 1.0000000 3 58 0 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.230000e-05 9.950100e-03 -0.1594640 -3.251500e-03 -4.700000e-06 3.233200e-03 1.407550e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.859400e-03 6.494900e-03 0.0019196 2.349300e-03 3.939600e-03 9.090400e-03 1.007670e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.602917e-01 2.988129e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.602927e-01 2.987894e-01 0.0000000 1.922196e-01 4.459201e-01 7.188315e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035072e-01 2.568634e-01 0.0009790 1.316800e-02 7.791100e-02 3.164500e-01 9.990190e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 -0.0037035 0.0035316 0.2900000 0.2943264 0.623774 0.7821490 NA
1 54676 rs2462492 C T -0.0000015 0.0034977 1.0000000 0.9996630 0.400419 NA NA
1 86028 rs114608975 T C 0.0068955 0.0055951 0.2200002 0.2177971 0.103556 0.0277556 NA
1 91536 rs6702460 G T -0.0006292 0.0034441 0.8600001 0.8550319 0.456879 0.4207270 NA
1 234313 rs8179466 C T 0.0016037 0.0067894 0.8100000 0.8132666 0.074522 NA NA
1 534192 rs6680723 C T 0.0047169 0.0039348 0.2300001 0.2306184 0.240966 NA NA
1 546697 rs12025928 A G -0.0005142 0.0049091 0.9199999 0.9165712 0.913495 NA NA
1 693731 rs12238997 A G -0.0032768 0.0032970 0.3200000 0.3202846 0.116315 0.1417730 NA
1 705882 rs72631875 G A -0.0054188 0.0048313 0.2599998 0.2620329 0.067280 0.0315495 NA
1 706368 rs55727773 A G -0.0035951 0.0024425 0.1400000 0.1410409 0.515587 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0068978 0.0051278 0.1800002 0.1785676 0.041953 0.0473243 NA
22 51219766 rs182321900 C T 0.0032267 0.0239446 0.8900000 0.8928028 0.001929 NA NA
22 51220146 rs868950473 C T -0.0008152 0.0237251 0.9699999 0.9725885 0.001977 NA NA
22 51221190 rs369304721 G A -0.0058879 0.0051189 0.2500000 0.2500511 0.049734 NA NA
22 51221731 rs115055839 T C -0.0030077 0.0038290 0.4299995 0.4321603 0.073224 0.0625000 NA
22 51222100 rs114553188 G T 0.0091720 0.0045081 0.0420001 0.0418951 0.054455 0.0880591 NA
22 51223637 rs375798137 G A 0.0097034 0.0045300 0.0320000 0.0321904 0.054083 0.0788738 NA
22 51229805 rs9616985 T C -0.0029110 0.0038428 0.4500005 0.4487455 0.073059 0.0730831 NA
22 51232488 rs376461333 A G 0.0149447 0.0090515 0.0990011 0.0987234 0.020043 NA NA
22 51237063 rs3896457 T C 0.0025866 0.0023502 0.2700001 0.2710712 0.297953 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623774 ES:SE:LP:AF:ID  -0.0037035:0.00353159:0.537602:0.623774:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400419 ES:SE:LP:AF:ID  -1.47726e-06:0.00349774:-0:0.400419:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  0.00689549:0.00559514:0.657577:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456879 ES:SE:LP:AF:ID  -0.00062924:0.00344408:0.0655015:0.456879:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074522 ES:SE:LP:AF:ID  0.00160374:0.00678935:0.091515:0.074522:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240966 ES:SE:LP:AF:ID  0.00471691:0.0039348:0.638272:0.240966:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913495 ES:SE:LP:AF:ID  -0.000514249:0.00490912:0.0362122:0.913495:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116315 ES:SE:LP:AF:ID  -0.0032768:0.003297:0.49485:0.116315:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06728  ES:SE:LP:AF:ID  -0.00541876:0.00483128:0.585027:0.06728:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515587 ES:SE:LP:AF:ID  -0.00359512:0.00244246:0.853872:0.515587:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032964 ES:SE:LP:AF:ID  -0.005274:0.00615959:0.408935:0.032964:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036581 ES:SE:LP:AF:ID  -0.00454187:0.00559454:0.376751:0.036581:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036698 ES:SE:LP:AF:ID  -0.00466353:0.00557334:0.39794:0.036698:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036398 ES:SE:LP:AF:ID  -0.0035993:0.00561352:0.283997:0.036398:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016389 ES:SE:LP:AF:ID  -0.00635139:0.00864694:0.337242:0.016389:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036934 ES:SE:LP:AF:ID  -0.00427174:0.00555156:0.356547:0.036934:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037031 ES:SE:LP:AF:ID  -0.00398337:0.00553258:0.327902:0.037031:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101208 ES:SE:LP:AF:ID  0.00552958:0.00402916:0.769551:0.101208:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959138 ES:SE:LP:AF:ID  0.00426703:0.00533593:0.376751:0.959138:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031435 ES:SE:LP:AF:ID  -0.00648893:0.00968754:0.30103:0.031435:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.0533   ES:SE:LP:AF:ID  -0.0015419:0.0076967:0.0757207:0.0533:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036552 ES:SE:LP:AF:ID  -0.00493355:0.00556813:0.420216:0.036552:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036863 ES:SE:LP:AF:ID  -0.00391888:0.0055177:0.318759:0.036863:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84324  ES:SE:LP:AF:ID  0.00450848:0.00285713:0.958607:0.84324:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055942 ES:SE:LP:AF:ID  -0.00522974:0.00462464:0.585027:0.055942:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122317 ES:SE:LP:AF:ID  -0.00383841:0.00312711:0.657577:0.122317:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025719 ES:SE:LP:AF:ID  -0.00906658:0.0076909:0.619789:0.025719:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121557 ES:SE:LP:AF:ID  -0.0035629:0.00312845:0.60206:0.121557:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132315 ES:SE:LP:AF:ID  -0.0034537:0.00308345:0.585027:0.132315:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011142 ES:SE:LP:AF:ID  -0.00373853:0.0112018:0.130768:0.011142:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.0057   ES:SE:LP:AF:ID  4.97859e-05:0.0144763:-0:0.0057:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002269 ES:SE:LP:AF:ID  0.0103158:0.0243196:0.173925:0.002269:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001025 ES:SE:LP:AF:ID  -0.0505518:0.0399852:0.677781:0.001025:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036779 ES:SE:LP:AF:ID  -0.00354486:0.00546186:0.283997:0.036779:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838992 ES:SE:LP:AF:ID  0.00400096:0.00276707:0.823909:0.838992:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838625 ES:SE:LP:AF:ID  0.00436933:0.00276412:0.958607:0.838625:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869786 ES:SE:LP:AF:ID  0.00359047:0.00296585:0.638272:0.869786:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129857 ES:SE:LP:AF:ID  -0.00420921:0.00297188:0.79588:0.129857:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037284 ES:SE:LP:AF:ID  -0.00340262:0.00536972:0.275724:0.037284:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037529 ES:SE:LP:AF:ID  -0.00322472:0.00533567:0.259637:0.037529:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869134 ES:SE:LP:AF:ID  0.00385955:0.00296008:0.721246:0.869134:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869231 ES:SE:LP:AF:ID  0.00374764:0.00296126:0.677781:0.869231:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037486 ES:SE:LP:AF:ID  -0.0040311:0.00535882:0.346787:0.037486:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869137 ES:SE:LP:AF:ID  0.00388602:0.00296002:0.721246:0.869137:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005131 ES:SE:LP:AF:ID  -0.00974488:0.0151876:0.283997:0.005131:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005096 ES:SE:LP:AF:ID  -0.0084123:0.015227:0.236572:0.005096:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838076 ES:SE:LP:AF:ID  0.00428445:0.00275643:0.920819:0.838076:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037498 ES:SE:LP:AF:ID  -0.00379357:0.00536654:0.318759:0.037498:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838709 ES:SE:LP:AF:ID  0.0042647:0.0027642:0.920819:0.838709:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013778 ES:SE:LP:AF:ID  -0.000613276:0.00964434:0.0222764:0.013778:rs181660517