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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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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-1996/UKB-b-1996_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1996/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1996/UKB-b-1996_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: 0.0445 (0.0021)
Lambda GC: 1.3337
Mean Chi^2: 1.4176
Intercept: 1.0416 (0.0078)
Ratio: 0.0995 (0.0188)
Analysis finished at Thu Oct 17 14:43:57 2019
Total time elapsed: 1.0m:56.66s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 22,
    "n_p_sig": 2525,
    "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": 0.0445,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.0416,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.3337,
    "ldsc_mean_chisq": 1.4176,
    "ldsc_ratio": 0.0996
}

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 4.080000e-05 6.984700e-03 -0.1037110 -2.257200e-03 2.110000e-05 2.316700e-03 1.018280e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.908300e-03 4.644800e-03 0.0013733 1.681500e-03 2.819700e-03 6.506000e-03 7.196820e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.651568e-01 2.985604e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.651589e-01 2.985344e-01 0.0000000 1.979421e-01 4.531869e-01 7.237399e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035079e-01 2.568605e-01 0.0009760 1.316900e-02 7.791900e-02 3.164550e-01 9.990170e-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 -0.0019029 0.0025272 0.4500005 0.4514711 0.623731 0.7821490 NA
1 54676 rs2462492 C T -0.0002959 0.0025034 0.9100000 0.9059217 0.400372 NA NA
1 86028 rs114608975 T C -0.0033475 0.0040043 0.4000000 0.4031713 0.103555 0.0277556 NA
1 91536 rs6702460 G T 0.0022360 0.0024644 0.3599996 0.3642394 0.456825 0.4207270 NA
1 234313 rs8179466 C T 0.0010209 0.0048578 0.8300000 0.8335491 0.074556 NA NA
1 534192 rs6680723 C T -0.0017520 0.0028150 0.5300002 0.5336885 0.241104 NA NA
1 546697 rs12025928 A G -0.0069804 0.0035131 0.0470002 0.0469278 0.913505 NA NA
1 693731 rs12238997 A G -0.0012615 0.0023582 0.5900000 0.5926844 0.116504 0.1417730 NA
1 705882 rs72631875 G A 0.0048281 0.0034582 0.1600000 0.1626792 0.067269 0.0315495 NA
1 706368 rs55727773 A G 0.0008071 0.0017478 0.6400000 0.6442305 0.515401 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0012392 0.0036706 0.7400005 0.7356553 0.041929 0.0473243 NA
22 51219766 rs182321900 C T 0.0256482 0.0171685 0.1400000 0.1351991 0.001924 NA NA
22 51220146 rs868950473 C T 0.0171935 0.0169958 0.3100002 0.3117139 0.001975 NA NA
22 51221190 rs369304721 G A -0.0009973 0.0036628 0.7899998 0.7854070 0.049736 NA NA
22 51221731 rs115055839 T C -0.0001805 0.0027392 0.9500000 0.9474617 0.073248 0.0625000 NA
22 51222100 rs114553188 G T -0.0013843 0.0032275 0.6700003 0.6679964 0.054364 0.0880591 NA
22 51223637 rs375798137 G A -0.0012829 0.0032429 0.6899999 0.6923963 0.053997 0.0788738 NA
22 51229805 rs9616985 T C -0.0001214 0.0027493 0.9599999 0.9647659 0.073083 0.0730831 NA
22 51232488 rs376461333 A G -0.0009293 0.0064891 0.8900000 0.8861313 0.019980 NA NA
22 51237063 rs3896457 T C -0.0003558 0.0016819 0.8300000 0.8324671 0.298033 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623731 ES:SE:LP:AF:ID  -0.0019029:0.00252721:0.346787:0.623731:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400372 ES:SE:LP:AF:ID  -0.000295866:0.00250343:0.0409586:0.400372:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103555 ES:SE:LP:AF:ID  -0.00334747:0.00400429:0.39794:0.103555:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456825 ES:SE:LP:AF:ID  0.002236:0.00246441:0.443698:0.456825:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074556 ES:SE:LP:AF:ID  0.00102088:0.00485782:0.0809219:0.074556:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241104 ES:SE:LP:AF:ID  -0.00175199:0.00281496:0.275724:0.241104:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913505 ES:SE:LP:AF:ID  -0.00698036:0.0035131:1.3279:0.913505:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116504 ES:SE:LP:AF:ID  -0.00126153:0.00235822:0.229148:0.116504:rs12238997
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1   706368  rs12029736  A   G   .   PASS    AF=0.515401 ES:SE:LP:AF:ID  0.000807134:0.00174783:0.19382:0.515401:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033011 ES:SE:LP:AF:ID  0.000389004:0.00440612:0.0315171:0.033011:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036627 ES:SE:LP:AF:ID  0.000306807:0.0040026:0.0268721:0.036627:rs12184267
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1   717485  rs12184279  C   A   .   PASS    AF=0.036443 ES:SE:LP:AF:ID  0.000586567:0.00401624:0.0555173:0.036443:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016376 ES:SE:LP:AF:ID  0.00752766:0.00619087:0.657577:0.016376:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036986 ES:SE:LP:AF:ID  0.000395699:0.00397152:0.0362122:0.036986:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03708  ES:SE:LP:AF:ID  0.000285969:0.00395792:0.0268721:0.03708:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10134  ES:SE:LP:AF:ID  0.00102993:0.00288153:0.142668:0.10134:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959103 ES:SE:LP:AF:ID  -0.000802208:0.00381771:0.0809219:0.959103:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031389 ES:SE:LP:AF:ID  -0.00702286:0.00694323:0.508638:0.031389:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053279 ES:SE:LP:AF:ID  -0.00690251:0.00550841:0.677781:0.053279:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036602 ES:SE:LP:AF:ID  0.000384043:0.00398328:0.0362122:0.036602:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036914 ES:SE:LP:AF:ID  -0.000277246:0.00394734:0.0268721:0.036914:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843065 ES:SE:LP:AF:ID  0.00104581:0.00204415:0.21467:0.843065:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056064 ES:SE:LP:AF:ID  -0.00426262:0.00330543:0.69897:0.056064:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122464 ES:SE:LP:AF:ID  -0.00153846:0.00223707:0.309804:0.122464:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025731 ES:SE:LP:AF:ID  -0.0100461:0.00549878:1.16749:0.025731:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121704 ES:SE:LP:AF:ID  -0.00146695:0.00223797:0.29243:0.121704:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13252  ES:SE:LP:AF:ID  -0.00220511:0.00220546:0.49485:0.13252:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011126 ES:SE:LP:AF:ID  -0.0017524:0.00802743:0.0809219:0.011126:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005733 ES:SE:LP:AF:ID  -0.00145788:0.0103244:0.05061:0.005733:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002269 ES:SE:LP:AF:ID  0.0164731:0.0174244:0.468521:0.002269:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001019 ES:SE:LP:AF:ID  -0.0292974:0.0287621:0.508638:0.001019:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036827 ES:SE:LP:AF:ID  0.000585232:0.00390743:0.0555173:0.036827:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838832 ES:SE:LP:AF:ID  0.000516636:0.00197967:0.102373:0.838832:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838461 ES:SE:LP:AF:ID  0.00056236:0.00197756:0.107905:0.838461:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869664 ES:SE:LP:AF:ID  0.00094826:0.00212187:0.187087:0.869664:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129983 ES:SE:LP:AF:ID  -0.00107316:0.00212626:0.21467:0.129983:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037331 ES:SE:LP:AF:ID  0.00075535:0.00384148:0.0757207:0.037331:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037575 ES:SE:LP:AF:ID  0.000753458:0.00381721:0.0757207:0.037575:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869009 ES:SE:LP:AF:ID  0.000926034:0.00211776:0.180456:0.869009:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  0.000972714:0.00211863:0.187087:0.86911:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  0.000793314:0.00383369:0.0757207:0.037535:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86901  ES:SE:LP:AF:ID  0.000938862:0.00211772:0.180456:0.86901:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005126 ES:SE:LP:AF:ID  0.00491295:0.0108712:0.187087:0.005126:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005092 ES:SE:LP:AF:ID  0.00501852:0.0109001:0.187087:0.005092:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83791  ES:SE:LP:AF:ID  0.000398211:0.00197211:0.0757207:0.83791:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037548 ES:SE:LP:AF:ID  0.000727017:0.00383908:0.0705811:0.037548:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838541 ES:SE:LP:AF:ID  0.000246001:0.00197764:0.0457575:0.838541:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013796 ES:SE:LP:AF:ID  0.00482698:0.00690076:0.318759:0.013796:rs181660517