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-14147/UKB-b-14147_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14147/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14147/UKB-b-14147_data.vcf.gz ...
Read summary statistics for 9139958 SNPs.
Dropped 9369 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, 1287535 SNPs remain.
After merging with regression SNP LD, 1287535 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0548 (0.0024)
Lambda GC: 1.426
Mean Chi^2: 1.5253
Intercept: 1.0421 (0.0092)
Ratio: 0.0802 (0.0175)
Analysis finished at Thu Oct 17 14:44:55 2019
Total time elapsed: 1.0m:42.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9481,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 29,
    "n_p_sig": 2456,
    "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": 100613,
    "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": 1287535,
    "ldsc_nsnp_merge_regression_ld": 1287535,
    "ldsc_observed_scale_h2_beta": 0.0548,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0421,
    "ldsc_intercept_se": 0.0092,
    "ldsc_lambda_gc": 1.426,
    "ldsc_mean_chisq": 1.5253,
    "ldsc_ratio": 0.0801
}

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 9130634 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 9139958 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 8.639396e+00 5.756159e+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 7.879599e+07 5.632259e+07 828.0000000 3.246539e+07 6.936950e+07 1.145228e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 2.220000e-05 3.368500e-03 -0.0379445 -1.376400e-03 1.030000e-05 1.394200e-03 4.153000e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 2.514500e-03 1.901900e-03 0.0008828 1.056400e-03 1.640000e-03 3.450600e-03 2.148600e-02 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.563678e-01 3.003941e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.563688e-01 3.003714e-01 0.0000000 1.852432e-01 4.401643e-01 7.166638e-01 9.999998e-01 ▇▆▆▆▅
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.172583e-01 2.582187e-01 0.0029790 1.908700e-02 9.738000e-02 3.421700e-01 9.970210e-01 ▇▂▁▁▁
numeric AF_reference 100613 0.988992 NA NA NA NA NA NA NA 2.178170e-01 2.500737e-01 0.0000000 1.617410e-02 1.152160e-01 3.410540e-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 0.0011611 0.0016232 0.4700002 0.4744060 0.623792 0.7821490 NA
1 54676 rs2462492 C T -0.0018214 0.0016083 0.2599998 0.2574301 0.400420 NA NA
1 86028 rs114608975 T C -0.0033870 0.0025711 0.1900002 0.1877306 0.103572 0.0277556 NA
1 91536 rs6702460 G T 0.0010836 0.0015835 0.4899999 0.4937759 0.456830 0.4207270 NA
1 234313 rs8179466 C T -0.0064399 0.0031227 0.0389996 0.0391784 0.074504 NA NA
1 534192 rs6680723 C T 0.0015153 0.0018085 0.4000000 0.4020953 0.241035 NA NA
1 546697 rs12025928 A G -0.0043007 0.0022559 0.0569994 0.0565903 0.913452 NA NA
1 693731 rs12238997 A G 0.0003840 0.0015159 0.8000000 0.8000461 0.116315 0.1417730 NA
1 705882 rs72631875 G A 0.0001358 0.0022190 0.9500000 0.9512100 0.067389 0.0315495 NA
1 706368 rs55727773 A G -0.0001617 0.0011232 0.8900000 0.8855344 0.515777 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0000876 0.0013562 0.9500000 0.9485162 0.137845 0.2052720 NA
22 51219387 rs9616832 T C -0.0022548 0.0017600 0.2000000 0.2001569 0.073749 0.0654952 NA
22 51219704 rs147475742 G A -0.0021223 0.0023589 0.3700002 0.3682696 0.041944 0.0473243 NA
22 51221190 rs369304721 G A -0.0015110 0.0023542 0.5199996 0.5209697 0.049740 NA NA
22 51221731 rs115055839 T C -0.0020737 0.0017611 0.2399999 0.2390101 0.073238 0.0625000 NA
22 51222100 rs114553188 G T 0.0028902 0.0020750 0.1600000 0.1636596 0.054369 0.0880591 NA
22 51223637 rs375798137 G A 0.0028010 0.0020851 0.1800002 0.1791517 0.053998 0.0788738 NA
22 51229805 rs9616985 T C -0.0018310 0.0017674 0.2999998 0.3002035 0.073081 0.0730831 NA
22 51232488 rs376461333 A G 0.0019860 0.0041642 0.6300007 0.6334156 0.020036 NA NA
22 51237063 rs3896457 T C -0.0006818 0.0010809 0.5300002 0.5281873 0.298049 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623792 ES:SE:LP:AF:ID  0.0011611:0.00162317:0.327902:0.623792:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40042  ES:SE:LP:AF:ID  -0.0018214:0.00160832:0.585027:0.40042:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103572 ES:SE:LP:AF:ID  -0.00338702:0.00257114:0.721246:0.103572:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45683  ES:SE:LP:AF:ID  0.0010836:0.00158348:0.309804:0.45683:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074504 ES:SE:LP:AF:ID  -0.00643993:0.00312268:1.40894:0.074504:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241035 ES:SE:LP:AF:ID  0.00151534:0.00180853:0.39794:0.241035:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913452 ES:SE:LP:AF:ID  -0.00430073:0.00225587:1.24413:0.913452:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116315 ES:SE:LP:AF:ID  0.000383961:0.00151591:0.09691:0.116315:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067389 ES:SE:LP:AF:ID  0.000135774:0.00221899:0.0222764:0.067389:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515777 ES:SE:LP:AF:ID  -0.000161694:0.00112321:0.05061:0.515777:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032998 ES:SE:LP:AF:ID  -0.000775355:0.00283094:0.107905:0.032998:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.0366   ES:SE:LP:AF:ID  -0.000569376:0.00257211:0.0861861:0.0366:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036714 ES:SE:LP:AF:ID  -0.000317074:0.00256244:0.0457575:0.036714:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036412 ES:SE:LP:AF:ID  -0.000896852:0.00258093:0.136677:0.036412:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016426 ES:SE:LP:AF:ID  0.00324882:0.00396939:0.387216:0.016426:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036954 ES:SE:LP:AF:ID  -0.000890095:0.00255227:0.136677:0.036954:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  -0.00064625:0.0025434:0.09691:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101173 ES:SE:LP:AF:ID  -0.000798273:0.00185267:0.173925:0.101173:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959129 ES:SE:LP:AF:ID  0.000650177:0.00245348:0.102373:0.959129:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03144  ES:SE:LP:AF:ID  -0.00262259:0.00445563:0.251812:0.03144:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05323  ES:SE:LP:AF:ID  -0.000933253:0.00354341:0.102373:0.05323:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036569 ES:SE:LP:AF:ID  -0.000883981:0.00255995:0.136677:0.036569:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036887 ES:SE:LP:AF:ID  -0.000559352:0.00253661:0.0809219:0.036887:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843243 ES:SE:LP:AF:ID  -0.000270187:0.00131373:0.0757207:0.843243:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055933 ES:SE:LP:AF:ID  -0.00180084:0.00212676:0.39794:0.055933:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122291 ES:SE:LP:AF:ID  -7.35513e-05:0.00143797:0.0177288:0.122291:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02573  ES:SE:LP:AF:ID  -0.00414561:0.00353693:0.619789:0.02573:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121535 ES:SE:LP:AF:ID  -0.000100518:0.00143856:0.0268721:0.121535:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132273 ES:SE:LP:AF:ID  -0.000676124:0.00141813:0.200659:0.132273:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011088 ES:SE:LP:AF:ID  0.00646501:0.00516706:0.677781:0.011088:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005707 ES:SE:LP:AF:ID  0.00230097:0.0066491:0.136677:0.005707:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036798 ES:SE:LP:AF:ID  -0.000688309:0.00251115:0.107905:0.036798:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838995 ES:SE:LP:AF:ID  -0.000357818:0.00127229:0.107905:0.838995:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838625 ES:SE:LP:AF:ID  -0.000477477:0.0012709:0.148742:0.838625:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869815 ES:SE:LP:AF:ID  -0.000300948:0.00136375:0.0809219:0.869815:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12983  ES:SE:LP:AF:ID  0.000496266:0.00136654:0.142668:0.12983:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037298 ES:SE:LP:AF:ID  -0.000304935:0.00246891:0.0457575:0.037298:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037542 ES:SE:LP:AF:ID  -0.000232118:0.00245333:0.0362122:0.037542:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869162 ES:SE:LP:AF:ID  -0.000483859:0.00136109:0.142668:0.869162:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869258 ES:SE:LP:AF:ID  -0.00051448:0.0013616:0.148742:0.869258:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037502 ES:SE:LP:AF:ID  -0.000412735:0.00246384:0.0604807:0.037502:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869165 ES:SE:LP:AF:ID  -0.00047628:0.00136106:0.136677:0.869165:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005116 ES:SE:LP:AF:ID  0.00818617:0.00699677:0.619789:0.005116:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005081 ES:SE:LP:AF:ID  0.00852652:0.00701544:0.657577:0.005081:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83808  ES:SE:LP:AF:ID  -0.000532087:0.00126739:0.173925:0.83808:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037515 ES:SE:LP:AF:ID  -0.000410119:0.00246727:0.0604807:0.037515:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838714 ES:SE:LP:AF:ID  -0.000503992:0.00127098:0.161151:0.838714:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013778 ES:SE:LP:AF:ID  -0.0050362:0.00443535:0.585027:0.013778:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005554 ES:SE:LP:AF:ID  -0.00274941:0.00683876:0.161151:0.005554:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839828 ES:SE:LP:AF:ID  -0.00028987:0.00128819:0.0861861:0.839828:rs3131965