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-11842/UKB-b-11842_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11842/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11842/UKB-b-11842_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: 0.2513 (0.0077)
Lambda GC: 2.5617
Mean Chi^2: 3.5945
Intercept: 1.2464 (0.0205)
Ratio: 0.0949 (0.0079)
Analysis finished at Thu Oct 17 14:42:55 2019
Total time elapsed: 1.0m:46.04s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 2.0012,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 498,
    "n_p_sig": 84931,
    "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": 0.2513,
    "ldsc_observed_scale_h2_se": 0.0077,
    "ldsc_intercept_beta": 1.2464,
    "ldsc_intercept_se": 0.0205,
    "ldsc_lambda_gc": 2.5617,
    "ldsc_mean_chisq": 3.5945,
    "ldsc_ratio": 0.095
}
 

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 1.000000 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+07 828.000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.040000e-05 9.594400e-03 -0.260137 -3.726800e-03 -8.200000e-06 3.723300e-03 1.673870e-01 ▁▁▃▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.977300e-03 5.657300e-03 0.001670 2.047800e-03 3.433800e-03 7.922600e-03 8.776190e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.916297e-01 3.122625e-01 0.000000 9.499920e-02 3.400001e-01 6.600001e-01 1.000000e+00 ▇▃▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.916307e-01 3.122406e-01 0.000000 9.455190e-02 3.441146e-01 6.588174e-01 1.000000e+00 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568613e-01 0.000994 1.316900e-02 7.791300e-02 3.164560e-01 9.990080e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.000000 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 0.0010369 0.0030687 0.7400005 0.7354428 0.623762 0.7821490 NA
1 54676 rs2462492 C T 0.0024934 0.0030403 0.4100001 0.4121342 0.400410 NA NA
1 86028 rs114608975 T C 0.0051204 0.0048604 0.2900000 0.2921150 0.103555 0.0277556 NA
1 91536 rs6702460 G T 0.0048396 0.0029935 0.1100001 0.1059399 0.456845 0.4207270 NA
1 234313 rs8179466 C T -0.0115824 0.0059020 0.0500000 0.0497109 0.074504 NA NA
1 534192 rs6680723 C T -0.0018055 0.0034193 0.5999997 0.5974783 0.240939 NA NA
1 546697 rs12025928 A G 0.0028673 0.0042653 0.5000000 0.5014262 0.913463 NA NA
1 693731 rs12238997 A G -0.0018703 0.0028662 0.5099998 0.5140543 0.116272 0.1417730 NA
1 705882 rs72631875 G A -0.0013154 0.0041988 0.7499995 0.7540697 0.067302 0.0315495 NA
1 706368 rs55727773 A G -0.0004800 0.0021226 0.8200001 0.8210978 0.515699 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0030052 0.0044873 0.5000000 0.5030365 0.041944 0.0473243 NA
22 51219766 rs182321900 C T -0.0189898 0.0209139 0.3599996 0.3638788 0.001936 NA NA
22 51220146 rs868950473 C T -0.0216325 0.0207160 0.2999998 0.2963738 0.001984 NA NA
22 51221190 rs369304721 G A 0.0017017 0.0044800 0.6999999 0.7040610 0.049728 NA NA
22 51221731 rs115055839 T C 0.0029820 0.0033505 0.3700002 0.3734590 0.073237 0.0625000 NA
22 51222100 rs114553188 G T 0.0016227 0.0039440 0.6800001 0.6807501 0.054474 0.0880591 NA
22 51223637 rs375798137 G A 0.0017203 0.0039631 0.6600001 0.6642258 0.054103 0.0788738 NA
22 51229805 rs9616985 T C 0.0029015 0.0033626 0.3900004 0.3882108 0.073071 0.0730831 NA
22 51232488 rs376461333 A G 0.0037843 0.0079186 0.6300007 0.6327173 0.020052 NA NA
22 51237063 rs3896457 T C 0.0023633 0.0020567 0.2500000 0.2505290 0.297898 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  0.00103691:0.00306874:0.130768:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40041  ES:SE:LP:AF:ID  0.00249345:0.00304026:0.387216:0.40041:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103555 ES:SE:LP:AF:ID  0.00512043:0.00486043:0.537602:0.103555:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456845 ES:SE:LP:AF:ID  0.00483957:0.00299346:0.958607:0.456845:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074504 ES:SE:LP:AF:ID  -0.0115824:0.00590203:1.30103:0.074504:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240939 ES:SE:LP:AF:ID  -0.00180551:0.00341933:0.221849:0.240939:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913463 ES:SE:LP:AF:ID  0.00286733:0.00426529:0.30103:0.913463:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116272 ES:SE:LP:AF:ID  -0.00187033:0.00286624:0.29243:0.116272:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067302 ES:SE:LP:AF:ID  -0.0013154:0.00419883:0.124939:0.067302:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515699 ES:SE:LP:AF:ID  -0.000479995:0.00212262:0.0861861:0.515699:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033008 ES:SE:LP:AF:ID  -0.00205807:0.00535095:0.154902:0.033008:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036624 ES:SE:LP:AF:ID  -0.00208124:0.00486055:0.173925:0.036624:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036742 ES:SE:LP:AF:ID  -0.00198071:0.00484201:0.167491:0.036742:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036439 ES:SE:LP:AF:ID  -0.00313765:0.00487704:0.283997:0.036439:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016396 ES:SE:LP:AF:ID  -0.0027306:0.0075126:0.142668:0.016396:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036979 ES:SE:LP:AF:ID  -0.0025959:0.00482299:0.229148:0.036979:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037076 ES:SE:LP:AF:ID  -0.00268015:0.00480645:0.236572:0.037076:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101204 ES:SE:LP:AF:ID  0.00189174:0.0035022:0.229148:0.101204:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95909  ES:SE:LP:AF:ID  0.00365446:0.00463571:0.366532:0.95909:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  0.00405975:0.00841543:0.200659:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053249 ES:SE:LP:AF:ID  0.00154442:0.00669543:0.0861861:0.053249:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036595 ES:SE:LP:AF:ID  -0.0034016:0.00483743:0.318759:0.036595:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036912 ES:SE:LP:AF:ID  -0.00423305:0.0047934:0.420216:0.036912:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843262 ES:SE:LP:AF:ID  0.00291444:0.0024837:0.619789:0.843262:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055881 ES:SE:LP:AF:ID  -0.00655109:0.00402196:1:0.055881:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122247 ES:SE:LP:AF:ID  -0.00228461:0.00271888:0.39794:0.122247:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025715 ES:SE:LP:AF:ID  -0.00611727:0.00668585:0.443698:0.025715:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12149  ES:SE:LP:AF:ID  -0.00206051:0.00272002:0.346787:0.12149:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132291 ES:SE:LP:AF:ID  -0.00302724:0.00268063:0.585027:0.132291:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011133 ES:SE:LP:AF:ID  0.004556:0.00974559:0.19382:0.011133:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005694 ES:SE:LP:AF:ID  0.01562:0.0125849:0.677781:0.005694:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002274 ES:SE:LP:AF:ID  0.00656841:0.0211247:0.119186:0.002274:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001031 ES:SE:LP:AF:ID  0.00586446:0.0346049:0.0604807:0.001031:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036828 ES:SE:LP:AF:ID  -0.00326505:0.00474487:0.309804:0.036828:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839004 ES:SE:LP:AF:ID  0.0026092:0.00240531:0.552842:0.839004:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838634 ES:SE:LP:AF:ID  0.0029732:0.00240271:0.657577:0.838634:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86984  ES:SE:LP:AF:ID  0.00190082:0.00257841:0.337242:0.86984:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129805 ES:SE:LP:AF:ID  -0.00256577:0.00258374:0.49485:0.129805:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037339 ES:SE:LP:AF:ID  -0.00501756:0.00466449:0.552842:0.037339:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037581 ES:SE:LP:AF:ID  -0.00489991:0.00463513:0.537602:0.037581:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869186 ES:SE:LP:AF:ID  0.00220013:0.00257337:0.408935:0.869186:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869283 ES:SE:LP:AF:ID  0.0021705:0.00257439:0.39794:0.869283:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037538 ES:SE:LP:AF:ID  -0.00499352:0.00465525:0.552842:0.037538:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869188 ES:SE:LP:AF:ID  0.00224442:0.00257332:0.420216:0.869188:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  -0.00685918:0.0132113:0.221849:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  -0.00718:0.0132454:0.229148:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838088 ES:SE:LP:AF:ID  0.00305342:0.00239607:0.69897:0.838088:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  -0.00522527:0.00466184:0.585027:0.03755:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838721 ES:SE:LP:AF:ID  0.00305911:0.00240283:0.69897:0.838721:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013769 ES:SE:LP:AF:ID  0.0165886:0.00838727:1.31876:0.013769:rs181660517