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-6891/UKB-b-6891_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6891/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6891/UKB-b-6891_data.vcf.gz ...
Read summary statistics for 9319157 SNPs.
Dropped 10387 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, 1287984 SNPs remain.
After merging with regression SNP LD, 1287984 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0023 (0.0029)
Lambda GC: 1.0354
Mean Chi^2: 1.0355
Intercept: 1.0423 (0.006)
Ratio: 1.1913 (0.1688)
Analysis finished at Thu Oct 17 14:41:51 2019
Total time elapsed: 1.0m:33.79s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 3,
    "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": 113167,
    "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": 1287984,
    "ldsc_nsnp_merge_regression_ld": 1287984,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0423,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0354,
    "ldsc_mean_chisq": 1.0355,
    "ldsc_ratio": 1.1915
}

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 1.0000000 3 58 0 9308822 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 9319157 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 8.634541e+00 5.753887e+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 7.881267e+07 5.630817e+07 828.0000000 3.250428e+07 6.939519e+07 1.145425e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.420000e-05 2.770870e-02 -0.3814840 -9.719600e-03 1.832000e-04 1.008050e-02 2.749120e-01 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.138360e-02 1.693910e-02 0.0071482 8.602200e-03 1.360570e-02 2.930620e-02 2.473430e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.949991e-01 2.905309e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.949992e-01 2.905052e-01 0.0000000 2.413745e-01 4.935884e-01 7.470601e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.135172e-01 2.577838e-01 0.0023320 1.737700e-02 9.215200e-02 3.352140e-01 9.976680e-01 ▇▂▁▁▁
numeric AF_reference 113167 0.9878565 NA NA NA NA NA NA NA 2.145633e-01 2.495697e-01 0.0000000 1.477640e-02 1.106230e-01 3.352640e-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 -0.0060296 0.0131739 0.6499995 0.6471758 0.623776 0.7821490 NA
1 54676 rs2462492 C T -0.0201332 0.0130868 0.1199999 0.1239421 0.399305 NA NA
1 86028 rs114608975 T C 0.0129896 0.0208644 0.5300002 0.5335655 0.103727 0.0277556 NA
1 91536 rs6702460 G T 0.0055948 0.0128960 0.6600001 0.6644019 0.456247 0.4207270 NA
1 234313 rs8179466 C T 0.0194934 0.0254233 0.4400003 0.4432282 0.074557 NA NA
1 534192 rs6680723 C T -0.0030080 0.0147435 0.8400000 0.8383357 0.241134 NA NA
1 546697 rs12025928 A G 0.0029256 0.0182840 0.8700001 0.8728738 0.913070 NA NA
1 693731 rs12238997 A G 0.0086650 0.0122837 0.4799997 0.4805559 0.116946 0.1417730 NA
1 705882 rs72631875 G A 0.0189477 0.0179800 0.2900000 0.2919649 0.067518 0.0315495 NA
1 706368 rs55727773 A G 0.0005001 0.0090968 0.9599999 0.9561590 0.514847 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0081056 0.0110153 0.4600002 0.4618208 0.137166 0.2052720 NA
22 51219387 rs9616832 T C -0.0047309 0.0143316 0.7400005 0.7413213 0.072746 0.0654952 NA
22 51219704 rs147475742 G A 0.0128001 0.0191221 0.5000000 0.5032481 0.041693 0.0473243 NA
22 51221190 rs369304721 G A 0.0065826 0.0191760 0.7300002 0.7313948 0.049119 NA NA
22 51221731 rs115055839 T C -0.0039864 0.0143428 0.7800007 0.7810626 0.072216 0.0625000 NA
22 51222100 rs114553188 G T -0.0076304 0.0167708 0.6499995 0.6491231 0.054532 0.0880591 NA
22 51223637 rs375798137 G A -0.0066962 0.0168568 0.6899999 0.6911903 0.054144 0.0788738 NA
22 51229805 rs9616985 T C -0.0062883 0.0143958 0.6600001 0.6622461 0.072075 0.0730831 NA
22 51232488 rs376461333 A G -0.0554305 0.0336499 0.1000000 0.0995024 0.020212 NA NA
22 51237063 rs3896457 T C -0.0032367 0.0087529 0.7099994 0.7115397 0.297533 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623776 ES:SE:LP:AF:ID  -0.00602955:0.0131739:0.187087:0.623776:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399305 ES:SE:LP:AF:ID  -0.0201332:0.0130868:0.920819:0.399305:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103727 ES:SE:LP:AF:ID  0.0129896:0.0208644:0.275724:0.103727:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456247 ES:SE:LP:AF:ID  0.00559485:0.012896:0.180456:0.456247:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074557 ES:SE:LP:AF:ID  0.0194934:0.0254233:0.356547:0.074557:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241134 ES:SE:LP:AF:ID  -0.00300801:0.0147435:0.0757207:0.241134:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91307  ES:SE:LP:AF:ID  0.00292561:0.018284:0.0604807:0.91307:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116946 ES:SE:LP:AF:ID  0.00866503:0.0122837:0.318759:0.116946:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067518 ES:SE:LP:AF:ID  0.0189477:0.01798:0.537602:0.067518:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514847 ES:SE:LP:AF:ID  0.000500088:0.00909678:0.0177288:0.514847:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033505 ES:SE:LP:AF:ID  -0.0251755:0.0227545:0.568636:0.033505:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.0372   ES:SE:LP:AF:ID  -0.0276336:0.0206661:0.744727:0.0372:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037332 ES:SE:LP:AF:ID  -0.027716:0.0205835:0.744727:0.037332:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036987 ES:SE:LP:AF:ID  -0.0268976:0.0207403:0.721246:0.036987:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016372 ES:SE:LP:AF:ID  0.0488821:0.0323444:0.886057:0.016372:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037569 ES:SE:LP:AF:ID  -0.0305148:0.0205028:0.853872:0.037569:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037665 ES:SE:LP:AF:ID  -0.0295432:0.020436:0.823909:0.037665:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101524 ES:SE:LP:AF:ID  0.00567009:0.01498:0.148742:0.101524:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958392 ES:SE:LP:AF:ID  0.0388202:0.0197171:1.3098:0.958392:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031723 ES:SE:LP:AF:ID  0.00206027:0.035977:0.0222764:0.031723:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052629 ES:SE:LP:AF:ID  -0.0169958:0.0290723:0.251812:0.052629:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03714  ES:SE:LP:AF:ID  -0.0296288:0.0205773:0.823909:0.03714:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037467 ES:SE:LP:AF:ID  -0.0262294:0.0203938:0.69897:0.037467:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842001 ES:SE:LP:AF:ID  0.00258078:0.0106342:0.091515:0.842001:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056099 ES:SE:LP:AF:ID  0.0130563:0.0172704:0.346787:0.056099:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12289  ES:SE:LP:AF:ID  0.00711433:0.0116577:0.267606:0.12289:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025764 ES:SE:LP:AF:ID  0.0380924:0.0286661:0.744727:0.025764:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122107 ES:SE:LP:AF:ID  0.00760129:0.0116634:0.29243:0.122107:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133347 ES:SE:LP:AF:ID  -0.00652601:0.011477:0.244125:0.133347:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011263 ES:SE:LP:AF:ID  0.0281499:0.0415687:0.30103:0.011263:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.00587  ES:SE:LP:AF:ID  0.0203509:0.0530562:0.154902:0.00587:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037418 ES:SE:LP:AF:ID  -0.0270173:0.0201829:0.744727:0.037418:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83771  ES:SE:LP:AF:ID  0.00233282:0.0102962:0.0861861:0.83771:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837328 ES:SE:LP:AF:ID  0.00191604:0.0102851:0.0705811:0.837328:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868977 ES:SE:LP:AF:ID  -0.00540907:0.0110378:0.207608:0.868977:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130705 ES:SE:LP:AF:ID  0.0045973:0.0110607:0.167491:0.130705:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037913 ES:SE:LP:AF:ID  -0.0254651:0.0198521:0.69897:0.037913:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038169 ES:SE:LP:AF:ID  -0.02499:0.0197244:0.677781:0.038169:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868306 ES:SE:LP:AF:ID  -0.00523988:0.0110163:0.200659:0.868306:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868412 ES:SE:LP:AF:ID  -0.00527286:0.0110212:0.200659:0.868412:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038102 ES:SE:LP:AF:ID  -0.0244837:0.0198104:0.657577:0.038102:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868303 ES:SE:LP:AF:ID  -0.00520899:0.0110156:0.19382:0.868303:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005167 ES:SE:LP:AF:ID  -0.0601553:0.0565334:0.537602:0.005167:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005137 ES:SE:LP:AF:ID  -0.0589158:0.0566572:0.522879:0.005137:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83681  ES:SE:LP:AF:ID  0.0020748:0.0102584:0.0757207:0.83681:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038114 ES:SE:LP:AF:ID  -0.0247904:0.0198372:0.677781:0.038114:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837438 ES:SE:LP:AF:ID  0.00159787:0.0102867:0.0555173:0.837438:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013295 ES:SE:LP:AF:ID  -0.0626188:0.0367489:1.05552:0.013295:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005465 ES:SE:LP:AF:ID  0.0191192:0.0558344:0.136677:0.005465:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838654 ES:SE:LP:AF:ID  0.0013353:0.0104266:0.0457575:0.838654:rs3131965