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-15041/UKB-b-15041_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15041/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15041/UKB-b-15041_data.vcf.gz ...
Read summary statistics for 9509592 SNPs.
Dropped 11687 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, 1288397 SNPs remain.
After merging with regression SNP LD, 1288397 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0068 (0.0021)
Lambda GC: 1.0879
Mean Chi^2: 1.0889
Intercept: 1.0546 (0.0067)
Ratio: 0.614 (0.0754)
Analysis finished at Thu Oct 17 14:45:37 2019
Total time elapsed: 1.0m:44.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9491,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 134133,
    "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": 1288397,
    "ldsc_nsnp_merge_regression_ld": 1288397,
    "ldsc_observed_scale_h2_beta": 0.0068,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.0546,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0879,
    "ldsc_mean_chisq": 1.0889,
    "ldsc_ratio": 0.6142
}

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 TRUE
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 9497965 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 9509592 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 8.629398e+00 5.751748e+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 7.883462e+07 5.630817e+07 828.0000000 3.254206e+07 6.942009e+07 1.145666e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -1.178000e-04 4.643100e-03 -0.0639324 -1.606900e-03 -2.710000e-05 1.512200e-03 6.048800e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 3.412800e-03 2.866700e-03 0.0010745 1.302600e-03 2.103500e-03 4.641700e-03 3.814100e-02 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.887143e-01 2.918511e-01 0.0000001 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.887151e-01 2.918262e-01 0.0000001 2.326620e-01 4.852950e-01 7.415860e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.096471e-01 2.573115e-01 0.0017310 1.571100e-02 8.666200e-02 3.280700e-01 9.982690e-01 ▇▂▁▁▁
numeric AF_reference 134133 0.985895 NA NA NA NA NA NA NA 2.113649e-01 2.490208e-01 0.0000000 1.337860e-02 1.062300e-01 3.294730e-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 0.0005081 0.0019810 0.8000000 0.7975861 0.623372 0.7821490 NA
1 54676 rs2462492 C T -0.0012370 0.0019582 0.5300002 0.5275670 0.400997 NA NA
1 86028 rs114608975 T C 0.0005520 0.0031420 0.8600001 0.8605424 0.103457 0.0277556 NA
1 91536 rs6702460 G T -0.0021808 0.0019295 0.2599998 0.2583670 0.457076 0.4207270 NA
1 234313 rs8179466 C T 0.0010630 0.0038112 0.7800007 0.7802994 0.074436 NA NA
1 534192 rs6680723 C T 0.0005094 0.0022051 0.8200001 0.8173125 0.241184 NA NA
1 546697 rs12025928 A G -0.0018581 0.0027509 0.5000000 0.4993850 0.913542 NA NA
1 693731 rs12238997 A G 0.0010367 0.0018457 0.5700002 0.5743487 0.116696 0.1417730 NA
1 705882 rs72631875 G A -0.0000794 0.0027096 0.9800000 0.9766339 0.067083 0.0315495 NA
1 706368 rs55727773 A G -0.0013570 0.0013685 0.3200000 0.3214049 0.515076 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0034388 0.0028756 0.2300001 0.2317478 0.041868 0.0473243 NA
22 51219766 rs182321900 C T 0.0006965 0.0136013 0.9599999 0.9591597 0.001885 NA NA
22 51220146 rs868950473 C T -0.0037288 0.0134734 0.7800007 0.7819717 0.001928 NA NA
22 51221190 rs369304721 G A -0.0004632 0.0028725 0.8700001 0.8718915 0.049619 NA NA
22 51221731 rs115055839 T C -0.0018374 0.0021468 0.3900004 0.3920701 0.073181 0.0625000 NA
22 51222100 rs114553188 G T -0.0026367 0.0025230 0.2999998 0.2959983 0.054661 0.0880591 NA
22 51223637 rs375798137 G A -0.0027964 0.0025351 0.2700001 0.2699845 0.054296 0.0788738 NA
22 51229805 rs9616985 T C -0.0016639 0.0021544 0.4400003 0.4399233 0.073048 0.0730831 NA
22 51232488 rs376461333 A G -0.0063271 0.0050714 0.2099999 0.2121762 0.020055 NA NA
22 51237063 rs3896457 T C 0.0030477 0.0013163 0.0210000 0.0205991 0.297921 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623372 ES:SE:LP:AF:ID  0.000508077:0.00198102:0.09691:0.623372:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400997 ES:SE:LP:AF:ID  -0.00123703:0.00195818:0.275724:0.400997:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103457 ES:SE:LP:AF:ID  0.000552002:0.00314202:0.0655015:0.103457:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457076 ES:SE:LP:AF:ID  -0.00218079:0.00192946:0.585027:0.457076:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074436 ES:SE:LP:AF:ID  0.00106304:0.00381115:0.107905:0.074436:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241184 ES:SE:LP:AF:ID  0.000509387:0.00220511:0.0861861:0.241184:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913542 ES:SE:LP:AF:ID  -0.00185813:0.00275092:0.30103:0.913542:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116696 ES:SE:LP:AF:ID  0.00103667:0.00184573:0.244125:0.116696:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067083 ES:SE:LP:AF:ID  -7.93637e-05:0.00270965:0.00877392:0.067083:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515076 ES:SE:LP:AF:ID  -0.00135701:0.00136854:0.49485:0.515076:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032868 ES:SE:LP:AF:ID  -0.000284446:0.00345769:0.0315171:0.032868:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036447 ES:SE:LP:AF:ID  -0.00124653:0.00314305:0.161151:0.036447:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036555 ES:SE:LP:AF:ID  -0.00114109:0.00313182:0.142668:0.036555:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036246 ES:SE:LP:AF:ID  -0.001568:0.00315495:0.207608:0.036246:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01636  ES:SE:LP:AF:ID  0.00368277:0.00484859:0.346787:0.01636:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036777 ES:SE:LP:AF:ID  -0.000986204:0.00312016:0.124939:0.036777:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03687  ES:SE:LP:AF:ID  -0.00133708:0.0031097:0.173925:0.03687:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101101 ES:SE:LP:AF:ID  0.00340905:0.00225904:0.886057:0.101101:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959316 ES:SE:LP:AF:ID  0.00331322:0.00299872:0.568636:0.959316:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031415 ES:SE:LP:AF:ID  -0.00179651:0.00541257:0.130768:0.031415:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053402 ES:SE:LP:AF:ID  0.000696768:0.00430592:0.0604807:0.053402:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036413 ES:SE:LP:AF:ID  -0.000865736:0.00312794:0.107905:0.036413:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036743 ES:SE:LP:AF:ID  -0.000610317:0.00309944:0.0757207:0.036743:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843044 ES:SE:LP:AF:ID  -0.000443761:0.00160167:0.107905:0.843044:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056035 ES:SE:LP:AF:ID  0.000800384:0.0025914:0.119186:0.056035:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122701 ES:SE:LP:AF:ID  0.00105438:0.00175055:0.259637:0.122701:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025571 ES:SE:LP:AF:ID  0.00219711:0.00432418:0.21467:0.025571:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121926 ES:SE:LP:AF:ID  0.00120294:0.0017513:0.309804:0.121926:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13258  ES:SE:LP:AF:ID  0.000719234:0.00172727:0.167491:0.13258:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011128 ES:SE:LP:AF:ID  -0.000844967:0.00628778:0.05061:0.011128:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005769 ES:SE:LP:AF:ID  0.00465531:0.0080421:0.251812:0.005769:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002236 ES:SE:LP:AF:ID  -0.0195364:0.0137657:0.79588:0.002236:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036649 ES:SE:LP:AF:ID  -0.000515063:0.00306857:0.0604807:0.036649:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838725 ES:SE:LP:AF:ID  -0.000536728:0.00155025:0.136677:0.838725:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838354 ES:SE:LP:AF:ID  -0.00054314:0.00154875:0.136677:0.838354:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869395 ES:SE:LP:AF:ID  -0.000517531:0.00166027:0.119186:0.869395:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130255 ES:SE:LP:AF:ID  0.000483647:0.001664:0.113509:0.130255:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03712  ES:SE:LP:AF:ID  -0.000622766:0.00301781:0.0757207:0.03712:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037383 ES:SE:LP:AF:ID  -0.000520562:0.00299764:0.0655015:0.037383:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86873  ES:SE:LP:AF:ID  -0.000463005:0.00165723:0.107905:0.86873:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868804 ES:SE:LP:AF:ID  -0.000482799:0.00165782:0.113509:0.868804:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037331 ES:SE:LP:AF:ID  -0.000880281:0.003011:0.113509:0.037331:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86873  ES:SE:LP:AF:ID  -0.000465776:0.00165718:0.107905:0.86873:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005084 ES:SE:LP:AF:ID  -0.00787816:0.00856369:0.443698:0.005084:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005053 ES:SE:LP:AF:ID  -0.00764007:0.00858395:0.431798:0.005053:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.8378   ES:SE:LP:AF:ID  -0.000382588:0.00154435:0.09691:0.8378:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037344 ES:SE:LP:AF:ID  -0.000897131:0.00301552:0.113509:0.037344:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  -0.00038606:0.0015487:0.09691:0.838434:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013855 ES:SE:LP:AF:ID  -0.0100418:0.0053907:1.20761:0.013855:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005573 ES:SE:LP:AF:ID  0.00109565:0.00832902:0.0457575:0.005573:rs184270342