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-18994/UKB-b-18994_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18994/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18994/UKB-b-18994_data.vcf.gz ...
Read summary statistics for 9486712 SNPs.
Dropped 11500 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, 1288331 SNPs remain.
After merging with regression SNP LD, 1288331 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0604 (0.0027)
Lambda GC: 1.4388
Mean Chi^2: 1.5827
Intercept: 1.031 (0.01)
Ratio: 0.0532 (0.0172)
Analysis finished at Thu Oct 17 14:42:35 2019
Total time elapsed: 1.0m:41.63s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9491,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 48,
    "n_p_sig": 6535,
    "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": 131505,
    "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": 1288331,
    "ldsc_nsnp_merge_regression_ld": 1288331,
    "ldsc_observed_scale_h2_beta": 0.0604,
    "ldsc_observed_scale_h2_se": 0.0027,
    "ldsc_intercept_beta": 1.031,
    "ldsc_intercept_se": 0.01,
    "ldsc_lambda_gc": 1.4388,
    "ldsc_mean_chisq": 1.5827,
    "ldsc_ratio": 0.0532
}

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 1.000000 3 58 0 9475272 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 9486712 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 8.629579e+00 5.752135e+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 7.883494e+07 5.631074e+07 828.0000000 3.253758e+07 6.941591e+07 1.145689e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 2.930000e-05 4.272600e-03 -0.0536827 -1.604900e-03 1.780000e-05 1.641300e-03 5.365010e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 3.114300e-03 2.597400e-03 0.0009891 1.196400e-03 1.927000e-03 4.240200e-03 3.434270e-02 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.564869e-01 3.009122e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.564872e-01 3.008889e-01 0.0000000 1.848852e-01 4.405492e-01 7.177646e-01 1.000000e+00 ▇▆▆▆▅
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.100895e-01 2.573591e-01 0.0017910 1.589200e-02 8.724500e-02 3.288750e-01 9.982090e-01 ▇▂▁▁▁
numeric AF_reference 131505 0.986138 NA NA NA NA NA NA NA 2.117166e-01 2.490842e-01 0.0000000 1.357830e-02 1.068290e-01 3.300720e-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 0.0013960 0.0018194 0.4400003 0.4429198 0.623772 0.7821490 NA
1 54676 rs2462492 C T -0.0011379 0.0018020 0.5300002 0.5277355 0.400416 NA NA
1 86028 rs114608975 T C -0.0023385 0.0028807 0.4199997 0.4169060 0.103582 0.0277556 NA
1 91536 rs6702460 G T -0.0018214 0.0017744 0.2999998 0.3046592 0.456877 0.4207270 NA
1 234313 rs8179466 C T -0.0006020 0.0034984 0.8600001 0.8633858 0.074512 NA NA
1 534192 rs6680723 C T 0.0027290 0.0020268 0.1800002 0.1781534 0.240979 NA NA
1 546697 rs12025928 A G 0.0020046 0.0025287 0.4299995 0.4279237 0.913465 NA NA
1 693731 rs12238997 A G 0.0015829 0.0016983 0.3500000 0.3513167 0.116363 0.1417730 NA
1 705882 rs72631875 G A 0.0003577 0.0024893 0.8900000 0.8857371 0.067272 0.0315495 NA
1 706368 rs55727773 A G -0.0029511 0.0012581 0.0189998 0.0189890 0.515763 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0019498 0.0026429 0.4600002 0.4606617 0.041947 0.0473243 NA
22 51219766 rs182321900 C T -0.0122418 0.0123594 0.3200000 0.3219371 0.001926 NA NA
22 51220146 rs868950473 C T -0.0122224 0.0122390 0.3200000 0.3179673 0.001976 NA NA
22 51221190 rs369304721 G A -0.0026874 0.0026394 0.3100002 0.3085932 0.049703 NA NA
22 51221731 rs115055839 T C -0.0021397 0.0019736 0.2800000 0.2782863 0.073211 0.0625000 NA
22 51222100 rs114553188 G T 0.0051814 0.0023228 0.0259998 0.0257035 0.054459 0.0880591 NA
22 51223637 rs375798137 G A 0.0050677 0.0023341 0.0299999 0.0299198 0.054088 0.0788738 NA
22 51229805 rs9616985 T C -0.0020748 0.0019807 0.2900000 0.2948721 0.073050 0.0730831 NA
22 51232488 rs376461333 A G 0.0075567 0.0046645 0.1100001 0.1052187 0.020047 NA NA
22 51237063 rs3896457 T C 0.0001619 0.0012110 0.8900000 0.8936740 0.297965 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  0.00139599:0.00181942:0.356547:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400416 ES:SE:LP:AF:ID  -0.00113789:0.00180198:0.275724:0.400416:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103582 ES:SE:LP:AF:ID  -0.00233853:0.00288067:0.376751:0.103582:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456877 ES:SE:LP:AF:ID  -0.00182143:0.00177442:0.522879:0.456877:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074512 ES:SE:LP:AF:ID  -0.000601962:0.00349844:0.0655015:0.074512:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240979 ES:SE:LP:AF:ID  0.00272897:0.00202677:0.744727:0.240979:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913465 ES:SE:LP:AF:ID  0.00200461:0.00252868:0.366532:0.913465:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116363 ES:SE:LP:AF:ID  0.00158289:0.00169831:0.455932:0.116363:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067272 ES:SE:LP:AF:ID  0.000357709:0.00248927:0.05061:0.067272:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515763 ES:SE:LP:AF:ID  -0.00295109:0.00125806:1.72125:0.515763:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032988 ES:SE:LP:AF:ID  -9.88176e-07:0.00317269:-0:0.032988:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036598 ES:SE:LP:AF:ID  -0.000663195:0.00288218:0.0861861:0.036598:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036711 ES:SE:LP:AF:ID  -0.000487338:0.0028714:0.0604807:0.036711:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03641  ES:SE:LP:AF:ID  -0.000532261:0.00289215:0.0705811:0.03641:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016439 ES:SE:LP:AF:ID  0.00460514:0.0044471:0.522879:0.016439:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036953 ES:SE:LP:AF:ID  -0.000400668:0.00285996:0.05061:0.036953:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037046 ES:SE:LP:AF:ID  -0.000623121:0.00285028:0.0809219:0.037046:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101178 ES:SE:LP:AF:ID  0.00025207:0.00207606:0.0457575:0.101178:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959125 ES:SE:LP:AF:ID  0.000892958:0.00274915:0.124939:0.959125:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031453 ES:SE:LP:AF:ID  -0.00172861:0.0049888:0.136677:0.031453:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053299 ES:SE:LP:AF:ID  0.00198366:0.00396407:0.207608:0.053299:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036566 ES:SE:LP:AF:ID  -0.000537432:0.00286863:0.0705811:0.036566:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036883 ES:SE:LP:AF:ID  -0.000632272:0.0028425:0.0861861:0.036883:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  -0.00113759:0.00147203:0.356547:0.843204:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055895 ES:SE:LP:AF:ID  0.00236996:0.00238359:0.49485:0.055895:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122337 ES:SE:LP:AF:ID  0.00168017:0.00161107:0.522879:0.122337:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025718 ES:SE:LP:AF:ID  -0.00385396:0.00396442:0.481486:0.025718:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121581 ES:SE:LP:AF:ID  0.00170955:0.00161174:0.537602:0.121581:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132309 ES:SE:LP:AF:ID  0.000430201:0.00158883:0.102373:0.132309:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  0.00129642:0.00577502:0.0861861:0.011135:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005719 ES:SE:LP:AF:ID  0.00104595:0.00744268:0.05061:0.005719:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002271 ES:SE:LP:AF:ID  0.00313353:0.0125317:0.09691:0.002271:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036796 ES:SE:LP:AF:ID  -0.000151296:0.00281388:0.0177288:0.036796:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838952 ES:SE:LP:AF:ID  -0.00175834:0.00142559:0.657577:0.838952:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838581 ES:SE:LP:AF:ID  -0.00147709:0.00142403:0.522879:0.838581:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869762 ES:SE:LP:AF:ID  -0.00252887:0.00152801:1.00877:0.869762:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129881 ES:SE:LP:AF:ID  0.00230345:0.00153114:0.886057:0.129881:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037298 ES:SE:LP:AF:ID  -0.000151993:0.00276647:0.0177288:0.037298:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037543 ES:SE:LP:AF:ID  -0.000150292:0.00274899:0.0177288:0.037543:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869107 ES:SE:LP:AF:ID  -0.00234038:0.001525:0.920819:0.869107:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869204 ES:SE:LP:AF:ID  -0.00226684:0.0015256:0.853872:0.869204:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037501 ES:SE:LP:AF:ID  -0.000202444:0.00276085:0.0268721:0.037501:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869109 ES:SE:LP:AF:ID  -0.00232489:0.00152497:0.886057:0.869109:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005105 ES:SE:LP:AF:ID  0.00901763:0.00784489:0.60206:0.005105:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005071 ES:SE:LP:AF:ID  0.00920553:0.00786533:0.619789:0.005071:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838044 ES:SE:LP:AF:ID  -0.00163012:0.00142017:0.60206:0.838044:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037515 ES:SE:LP:AF:ID  -0.000388465:0.00276473:0.05061:0.037515:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838675 ES:SE:LP:AF:ID  -0.00163507:0.00142418:0.60206:0.838675:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013777 ES:SE:LP:AF:ID  0.00369699:0.00497141:0.337242:0.013777:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005545 ES:SE:LP:AF:ID  0.00334615:0.00767046:0.180456:0.005545:rs184270342