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-7408/UKB-b-7408_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7408/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-7408/UKB-b-7408_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: 0.0678 (0.003)
Lambda GC: 1.499
Mean Chi^2: 1.6195
Intercept: 1.0931 (0.0089)
Ratio: 0.1502 (0.0144)
Analysis finished at Thu Oct 17 14:43:00 2019
Total time elapsed: 2.0m:41.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.369,
    "mean_EFFECT": -0.0003,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 48,
    "n_p_sig": 5627,
    "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": 0.0678,
    "ldsc_observed_scale_h2_se": 0.003,
    "ldsc_intercept_beta": 1.0931,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.499,
    "ldsc_mean_chisq": 1.6195,
    "ldsc_ratio": 0.1503
}

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 -3.390000e-04 1.351960e-02 -0.1857900 -4.639700e-03 -1.274000e-04 4.298600e-03 2.183070e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.121000e-03 8.645200e-03 0.0025506 3.122400e-03 5.236300e-03 1.208260e-02 1.344430e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.507851e-01 3.014136e-01 0.0000000 1.800002e-01 4.299995e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.507862e-01 3.013893e-01 0.0000000 1.772802e-01 4.326970e-01 7.118210e-01 9.999999e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035070e-01 2.568703e-01 0.0009440 1.316900e-02 7.790300e-02 3.164500e-01 9.990490e-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 0.0061369 0.0046894 0.1900002 0.1906495 0.623844 0.7821490 NA
1 54676 rs2462492 C T 0.0012390 0.0046460 0.7899998 0.7897196 0.400238 NA NA
1 86028 rs114608975 T C -0.0044351 0.0074248 0.5500004 0.5502826 0.103621 0.0277556 NA
1 91536 rs6702460 G T -0.0021641 0.0045771 0.6400000 0.6363439 0.456852 0.4207270 NA
1 234313 rs8179466 C T 0.0100054 0.0090300 0.2700001 0.2678547 0.074437 NA NA
1 534192 rs6680723 C T -0.0030045 0.0052279 0.5700002 0.5654955 0.240936 NA NA
1 546697 rs12025928 A G 0.0052087 0.0065163 0.4199997 0.4240998 0.913384 NA NA
1 693731 rs12238997 A G -0.0068732 0.0043764 0.1199999 0.1162985 0.116381 0.1417730 NA
1 705882 rs72631875 G A -0.0073126 0.0064181 0.2500000 0.2545447 0.067301 0.0315495 NA
1 706368 rs55727773 A G 0.0062508 0.0032435 0.0539995 0.0539571 0.515890 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0031335 0.0068142 0.6499995 0.6456240 0.041959 0.0473243 NA
22 51219766 rs182321900 C T -0.0062844 0.0318547 0.8400000 0.8436046 0.001928 NA NA
22 51220146 rs868950473 C T -0.0044365 0.0315334 0.8900000 0.8881142 0.001980 NA NA
22 51221190 rs369304721 G A 0.0100511 0.0068051 0.1400000 0.1396775 0.049719 NA NA
22 51221731 rs115055839 T C 0.0058087 0.0050883 0.2500000 0.2536286 0.073267 0.0625000 NA
22 51222100 rs114553188 G T -0.0025287 0.0059970 0.6700003 0.6732724 0.054360 0.0880591 NA
22 51223637 rs375798137 G A -0.0019646 0.0060261 0.7400005 0.7444062 0.053991 0.0788738 NA
22 51229805 rs9616985 T C 0.0058654 0.0051058 0.2500000 0.2506570 0.073114 0.0730831 NA
22 51232488 rs376461333 A G 0.0003849 0.0120517 0.9699999 0.9745236 0.019981 NA NA
22 51237063 rs3896457 T C -0.0036622 0.0031268 0.2399999 0.2415205 0.297733 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623844 ES:SE:LP:AF:ID  0.00613687:0.00468943:0.721246:0.623844:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400238 ES:SE:LP:AF:ID  0.00123896:0.00464596:0.102373:0.400238:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103621 ES:SE:LP:AF:ID  -0.00443513:0.00742484:0.259637:0.103621:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456852 ES:SE:LP:AF:ID  -0.00216412:0.00457708:0.19382:0.456852:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074437 ES:SE:LP:AF:ID  0.0100054:0.00903001:0.568636:0.074437:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240936 ES:SE:LP:AF:ID  -0.00300447:0.00522791:0.244125:0.240936:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913384 ES:SE:LP:AF:ID  0.00520865:0.00651628:0.376751:0.913384:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116381 ES:SE:LP:AF:ID  -0.00687319:0.00437643:0.920819:0.116381:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067301 ES:SE:LP:AF:ID  -0.00731262:0.00641807:0.60206:0.067301:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51589  ES:SE:LP:AF:ID  0.00625083:0.00324351:1.26761:0.51589:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033025 ES:SE:LP:AF:ID  -0.00540138:0.0081727:0.29243:0.033025:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036638 ES:SE:LP:AF:ID  -0.00392033:0.00742538:0.221849:0.036638:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036752 ES:SE:LP:AF:ID  -0.00454586:0.00739751:0.267606:0.036752:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036449 ES:SE:LP:AF:ID  -0.00411049:0.00745105:0.236572:0.036449:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016466 ES:SE:LP:AF:ID  -0.0194147:0.011456:1.04576:0.016466:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036987 ES:SE:LP:AF:ID  -0.00381508:0.00736916:0.221849:0.036987:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037087 ES:SE:LP:AF:ID  -0.00383713:0.00734366:0.221849:0.037087:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101165 ES:SE:LP:AF:ID  -0.000731154:0.0053514:0.05061:0.101165:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959122 ES:SE:LP:AF:ID  0.00521217:0.00708587:0.337242:0.959122:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031422 ES:SE:LP:AF:ID  0.00903173:0.0128691:0.318759:0.031422:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053276 ES:SE:LP:AF:ID  0.00387295:0.0102269:0.154902:0.053276:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036601 ES:SE:LP:AF:ID  -0.00491271:0.00739146:0.29243:0.036601:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03693  ES:SE:LP:AF:ID  -0.00570268:0.0073225:0.356547:0.03693:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843206 ES:SE:LP:AF:ID  0.00790276:0.00379478:1.4318:0.843206:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055997 ES:SE:LP:AF:ID  -0.0012009:0.0061416:0.0757207:0.055997:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122353 ES:SE:LP:AF:ID  -0.00734589:0.00415216:1.11351:0.122353:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02579  ES:SE:LP:AF:ID  -0.00621252:0.0101995:0.267606:0.02579:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121598 ES:SE:LP:AF:ID  -0.00759826:0.00415386:1.17393:0.121598:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132323 ES:SE:LP:AF:ID  -0.00516327:0.00409529:0.677781:0.132323:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011128 ES:SE:LP:AF:ID  0.0204751:0.014904:0.769551:0.011128:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005711 ES:SE:LP:AF:ID  -0.0132649:0.0191939:0.309804:0.005711:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002257 ES:SE:LP:AF:ID  -0.0545949:0.0324512:1.03621:0.002257:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001031 ES:SE:LP:AF:ID  -0.0488537:0.0527726:0.455932:0.001031:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036838 ES:SE:LP:AF:ID  -0.00528746:0.00724939:0.327902:0.036838:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838963 ES:SE:LP:AF:ID  0.00599662:0.00367487:1:0.838963:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838609 ES:SE:LP:AF:ID  0.00572395:0.00367128:0.920819:0.838609:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869784 ES:SE:LP:AF:ID  0.00562827:0.00393823:0.823909:0.869784:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129857 ES:SE:LP:AF:ID  -0.00510657:0.00394628:0.69897:0.129857:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037332 ES:SE:LP:AF:ID  -0.00541257:0.00712891:0.346787:0.037332:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037574 ES:SE:LP:AF:ID  -0.00572338:0.00708417:0.376751:0.037574:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869137 ES:SE:LP:AF:ID  0.00549965:0.00393077:0.79588:0.869137:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869233 ES:SE:LP:AF:ID  0.0056685:0.00393224:0.823909:0.869233:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.00577205:0.00711361:0.376751:0.037545:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869139 ES:SE:LP:AF:ID  0.00550448:0.0039307:0.79588:0.869139:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005128 ES:SE:LP:AF:ID  0.0150455:0.0201641:0.337242:0.005128:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005093 ES:SE:LP:AF:ID  0.015975:0.0202183:0.366532:0.005093:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838044 ES:SE:LP:AF:ID  0.00571952:0.00366079:0.920819:0.838044:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037556 ES:SE:LP:AF:ID  -0.00557681:0.00712375:0.366532:0.037556:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838676 ES:SE:LP:AF:ID  0.00597466:0.00367104:1:0.838676:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013801 ES:SE:LP:AF:ID  -0.0016769:0.012805:0.0457575:0.013801:rs181660517