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-16609/UKB-b-16609_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16609/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16609/UKB-b-16609_data.vcf.gz ...
Read summary statistics for 5427725 SNPs.
Dropped 1927 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, 1166169 SNPs remain.
After merging with regression SNP LD, 1166169 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0382 (0.0081)
Lambda GC: 1.062
Mean Chi^2: 1.0604
Intercept: 1.0066 (0.0071)
Ratio: 0.1094 (0.1176)
Analysis finished at Thu Oct 17 14:46:12 2019
Total time elapsed: 59.3s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9156,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 2.715e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 47404,
    "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": 1166169,
    "ldsc_nsnp_merge_regression_ld": 1166169,
    "ldsc_observed_scale_h2_beta": 0.0382,
    "ldsc_observed_scale_h2_se": 0.0081,
    "ldsc_intercept_beta": 1.0066,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.062,
    "ldsc_mean_chisq": 1.0604,
    "ldsc_ratio": 0.1093
}

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 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 5425814 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 5427725 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 8.673122e+00 5.763839e+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 7.856128e+07 5.656927e+07 828.0000000 3.195449e+07 6.897862e+07 1.145113e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.700000e-06 2.351900e-03 -0.0185797 -1.465700e-03 2.200000e-06 1.466100e-03 1.729780e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.216000e-03 5.942000e-04 0.0015725 1.718800e-03 1.995400e-03 2.578900e-03 7.475800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.907714e-01 2.909787e-01 0.0000005 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.907718e-01 2.909549e-01 0.0000005 2.365303e-01 4.868806e-01 7.427340e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.342725e-01 2.459216e-01 0.0500360 1.237690e-01 2.616540e-01 5.010040e-01 9.499640e-01 ▇▃▂▂▂
numeric AF_reference 47404 0.9912663 NA NA NA NA NA NA NA 3.292172e-01 2.407561e-01 0.0000000 1.309900e-01 2.661740e-01 4.910140e-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 0.0027477 0.0029054 0.3400001 0.3442992 0.623987 0.7821490 NA
1 54676 rs2462492 C T -0.0045924 0.0028875 0.1100001 0.1117362 0.399180 NA NA
1 86028 rs114608975 T C 0.0006495 0.0045768 0.8900000 0.8871475 0.104002 0.0277556 NA
1 91536 rs6702460 G T -0.0004805 0.0028408 0.8700001 0.8656731 0.456263 0.4207270 NA
1 234313 rs8179466 C T 0.0088745 0.0055529 0.1100001 0.1100032 0.074922 NA NA
1 534192 rs6680723 C T 0.0007236 0.0032470 0.8200001 0.8236445 0.240514 NA NA
1 546697 rs12025928 A G -0.0035352 0.0040297 0.3800004 0.3803247 0.912581 NA NA
1 693731 rs12238997 A G 0.0001025 0.0027038 0.9699999 0.9697577 0.117125 0.1417730 NA
1 705882 rs72631875 G A -0.0012326 0.0039401 0.7499995 0.7544036 0.067985 0.0315495 NA
1 706368 rs55727773 A G 0.0002059 0.0020023 0.9199999 0.9181119 0.513999 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217954 rs9616974 G A 0.0034429 0.0031535 0.2700001 0.2749306 0.071924 0.0621006 NA
22 51218224 rs9616975 C A 0.0034017 0.0031552 0.2800000 0.2809781 0.071931 0.0619010 NA
22 51218377 rs2519461 G C 0.0034186 0.0031499 0.2800000 0.2777883 0.072280 0.0826677 NA
22 51219006 rs28729663 G A 0.0008893 0.0024207 0.7099994 0.7133354 0.136759 0.2052720 NA
22 51219387 rs9616832 T C 0.0037479 0.0031597 0.2399999 0.2355553 0.072276 0.0654952 NA
22 51221731 rs115055839 T C 0.0033715 0.0031604 0.2900000 0.2860646 0.071785 0.0625000 NA
22 51222100 rs114553188 G T 0.0007666 0.0036893 0.8400000 0.8353907 0.054300 0.0880591 NA
22 51223637 rs375798137 G A 0.0008502 0.0037085 0.8200001 0.8186677 0.053911 0.0788738 NA
22 51229805 rs9616985 T C 0.0035594 0.0031718 0.2599998 0.2617788 0.071663 0.0730831 NA
22 51237063 rs3896457 T C -0.0028294 0.0019249 0.1400000 0.1415918 0.297836 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623987 ES:SE:LP:AF:ID  0.00274766:0.00290541:0.468521:0.623987:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39918  ES:SE:LP:AF:ID  -0.00459242:0.00288752:0.958607:0.39918:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104002 ES:SE:LP:AF:ID  0.000649513:0.00457679:0.05061:0.104002:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456263 ES:SE:LP:AF:ID  -0.000480538:0.00284078:0.0604807:0.456263:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074922 ES:SE:LP:AF:ID  0.00887451:0.00555289:0.958607:0.074922:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240514 ES:SE:LP:AF:ID  0.000723635:0.00324704:0.0861861:0.240514:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912581 ES:SE:LP:AF:ID  -0.00353524:0.00402969:0.420216:0.912581:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117125 ES:SE:LP:AF:ID  0.000102507:0.0027038:0.0132283:0.117125:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067985 ES:SE:LP:AF:ID  -0.00123262:0.00394012:0.124939:0.067985:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513999 ES:SE:LP:AF:ID  0.000205858:0.00200227:0.0362122:0.513999:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101533 ES:SE:LP:AF:ID  -0.000455414:0.00330741:0.05061:0.101533:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.052627 ES:SE:LP:AF:ID  -0.00765893:0.00636475:0.638272:0.052627:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.841145 ES:SE:LP:AF:ID  -0.00195117:0.00233679:0.39794:0.841145:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05603  ES:SE:LP:AF:ID  0.00649325:0.00380233:1.05552:0.05603:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123133 ES:SE:LP:AF:ID  0.000418756:0.00256458:0.0604807:0.123133:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.122315 ES:SE:LP:AF:ID  0.000512494:0.00256644:0.0757207:0.122315:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133576 ES:SE:LP:AF:ID  0.00406862:0.00252419:0.958607:0.133576:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837051 ES:SE:LP:AF:ID  -0.00148537:0.0022615:0.29243:0.837051:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836575 ES:SE:LP:AF:ID  -0.00167578:0.00225861:0.337242:0.836575:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868582 ES:SE:LP:AF:ID  2.11581e-05:0.00242645:0.00436481:0.868582:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131122 ES:SE:LP:AF:ID  0.00015757:0.0024313:0.0222764:0.131122:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.867862 ES:SE:LP:AF:ID  -8.59842e-05:0.00242158:0.0132283:0.867862:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867967 ES:SE:LP:AF:ID  -3.5084e-05:0.00242282:0.00436481:0.867967:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867883 ES:SE:LP:AF:ID  -9.88991e-05:0.00242152:0.0132283:0.867883:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836137 ES:SE:LP:AF:ID  -0.00146849:0.00225447:0.29243:0.836137:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836768 ES:SE:LP:AF:ID  -0.00154068:0.00226068:0.30103:0.836768:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838175 ES:SE:LP:AF:ID  -0.00112017:0.00229289:0.200659:0.838175:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868268 ES:SE:LP:AF:ID  0.000159673:0.00241957:0.0222764:0.868268:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867821 ES:SE:LP:AF:ID  0.000254896:0.00241373:0.0362122:0.867821:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866495 ES:SE:LP:AF:ID  -1.90302e-05:0.00240712:0.00436481:0.866495:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867978 ES:SE:LP:AF:ID  0.000218088:0.00241562:0.0315171:0.867978:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867989 ES:SE:LP:AF:ID  0.000215071:0.00241579:0.0315171:0.867989:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867999 ES:SE:LP:AF:ID  0.000212001:0.00241588:0.0315171:0.867999:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868456 ES:SE:LP:AF:ID  0.000118158:0.00242265:0.0177288:0.868456:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.83649  ES:SE:LP:AF:ID  -0.00102707:0.00225047:0.187087:0.83649:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.836627 ES:SE:LP:AF:ID  -0.00102762:0.00225205:0.187087:0.836627:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860682 ES:SE:LP:AF:ID  -0.000715996:0.00240522:0.113509:0.860682:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705866 ES:SE:LP:AF:ID  0.000765682:0.00235312:0.130768:0.705866:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105752 ES:SE:LP:AF:ID  0.00106979:0.00270284:0.161151:0.105752:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.758492 ES:SE:LP:AF:ID  0.00138013:0.00190303:0.327902:0.758492:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.107905 ES:SE:LP:AF:ID  -0.00207393:0.00261753:0.366532:0.107905:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.130611 ES:SE:LP:AF:ID  0.000180154:0.00243098:0.0268721:0.130611:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.867853 ES:SE:LP:AF:ID  0.000321979:0.00241817:0.05061:0.867853:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.130677 ES:SE:LP:AF:ID  0.000147745:0.00242959:0.0222764:0.130677:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.867853 ES:SE:LP:AF:ID  0.00018716:0.00241815:0.0268721:0.867853:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265039 ES:SE:LP:AF:ID  0.00346974:0.00214488:0.958607:0.265039:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869064 ES:SE:LP:AF:ID  -0.000460535:0.00242458:0.0705811:0.869064:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.09652  ES:SE:LP:AF:ID  -0.000934096:0.00279019:0.130768:0.09652:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.129504 ES:SE:LP:AF:ID  0.000921381:0.00243371:0.154902:0.129504:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.129812 ES:SE:LP:AF:ID  0.00082658:0.00242952:0.136677:0.129812:rs4040617