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-2557/UKB-b-2557_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2557/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2557/UKB-b-2557_data.vcf.gz ...
Read summary statistics for 5083964 SNPs.
Dropped 1521 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, 1126576 SNPs remain.
After merging with regression SNP LD, 1126576 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.011 (0.0103)
Lambda GC: 1.0147
Mean Chi^2: 1.0147
Intercept: 1.0247 (0.007)
Ratio: 1.6824 (0.4742)
Analysis finished at Thu Oct 17 14:43:49 2019
Total time elapsed: 58.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9088,
    "inflation_factor": 1,
    "mean_EFFECT": -6.4638e-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": 43578,
    "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": 1126576,
    "ldsc_nsnp_merge_regression_ld": 1126576,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0247,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0147,
    "ldsc_mean_chisq": 1.0147,
    "ldsc_ratio": 1.6803
}

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 5082454 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 5083964 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 8.671983e+00 5.765707e+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 7.853549e+07 5.661330e+07 828.0000000 3.188756e+07 6.891615e+07 1.145262e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.500000e-06 3.042400e-03 -0.0207868 -1.936800e-03 -2.700000e-06 1.933500e-03 2.378260e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.949100e-03 6.827000e-04 0.0021755 2.371700e-03 2.703600e-03 3.382500e-03 8.324700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.971667e-01 2.890231e-01 0.0000001 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.971635e-01 2.889934e-01 0.0000001 2.457245e-01 4.964708e-01 7.470283e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.482794e-01 2.398893e-01 0.0626460 1.417698e-01 2.813900e-01 5.148530e-01 9.373540e-01 ▇▅▃▂▂
numeric AF_reference 43578 0.9914283 NA NA NA NA NA NA NA 3.419778e-01 2.362800e-01 0.0000000 1.469650e-01 2.841450e-01 5.043930e-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 0.0074308 0.0040353 0.0659994 0.0655602 0.622790 0.7821490 NA
1 54676 rs2462492 C T -0.0028202 0.0039875 0.4799997 0.4794079 0.399569 NA NA
1 86028 rs114608975 T C -0.0066500 0.0063493 0.2900000 0.2949323 0.104011 0.0277556 NA
1 91536 rs6702460 G T -0.0016784 0.0039395 0.6700003 0.6700692 0.456322 0.4207270 NA
1 234313 rs8179466 C T 0.0063609 0.0077912 0.4100001 0.4142580 0.073902 NA NA
1 534192 rs6680723 C T 0.0002387 0.0044431 0.9599999 0.9571592 0.243692 NA NA
1 546697 rs12025928 A G -0.0062960 0.0056566 0.2700001 0.2656895 0.914127 NA NA
1 693731 rs12238997 A G -0.0001778 0.0037415 0.9599999 0.9620998 0.116600 0.1417730 NA
1 705882 rs72631875 G A 0.0030127 0.0055438 0.5900000 0.5868292 0.066733 0.0315495 NA
1 706368 rs55727773 A G -0.0043096 0.0027790 0.1199999 0.1209489 0.513437 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T -0.0007972 0.0034507 0.8200001 0.8172966 0.127028 0.1727240 NA
22 51216564 rs9616970 T C -0.0005683 0.0034366 0.8700001 0.8686519 0.127507 0.1563500 NA
22 51217954 rs9616974 G A 0.0002309 0.0043680 0.9599999 0.9578357 0.072125 0.0621006 NA
22 51218224 rs9616975 C A 0.0002486 0.0043703 0.9500000 0.9546408 0.072132 0.0619010 NA
22 51218377 rs2519461 G C 0.0003376 0.0043645 0.9400001 0.9383477 0.072448 0.0826677 NA
22 51219006 rs28729663 G A 0.0007150 0.0033689 0.8300000 0.8319320 0.136750 0.2052720 NA
22 51219387 rs9616832 T C 0.0003921 0.0043729 0.9299999 0.9285488 0.072544 0.0654952 NA
22 51221731 rs115055839 T C 0.0004264 0.0043754 0.9199999 0.9223567 0.072106 0.0625000 NA
22 51229805 rs9616985 T C -0.0002215 0.0043866 0.9599999 0.9597303 0.072026 0.0730831 NA
22 51237063 rs3896457 T C -0.0007061 0.0026795 0.7899998 0.7921443 0.296954 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62279  ES:SE:LP:AF:ID  0.00743075:0.00403534:1.18046:0.62279:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399569 ES:SE:LP:AF:ID  -0.00282018:0.0039875:0.318759:0.399569:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104011 ES:SE:LP:AF:ID  -0.00665:0.00634928:0.537602:0.104011:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456322 ES:SE:LP:AF:ID  -0.00167844:0.00393951:0.173925:0.456322:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.073902 ES:SE:LP:AF:ID  0.00636091:0.00779119:0.387216:0.073902:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.243692 ES:SE:LP:AF:ID  0.000238676:0.00444306:0.0177288:0.243692:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.914127 ES:SE:LP:AF:ID  -0.006296:0.00565656:0.568636:0.914127:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.1166   ES:SE:LP:AF:ID  -0.000177791:0.00374149:0.0177288:0.1166:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066733 ES:SE:LP:AF:ID  0.00301272:0.00554383:0.229148:0.066733:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513437 ES:SE:LP:AF:ID  -0.00430962:0.00277896:0.920819:0.513437:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.099599 ES:SE:LP:AF:ID  0.0066986:0.00461893:0.823909:0.099599:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.841354 ES:SE:LP:AF:ID  0.00039295:0.00322205:0.0457575:0.841354:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.123286 ES:SE:LP:AF:ID  -0.000443547:0.00353352:0.0457575:0.123286:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.122413 ES:SE:LP:AF:ID  -0.000225276:0.0035366:0.0222764:0.122413:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133622 ES:SE:LP:AF:ID  -0.00204:0.00348627:0.251812:0.133622:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.83698  ES:SE:LP:AF:ID  -0.000377829:0.00312374:0.0457575:0.83698:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836506 ES:SE:LP:AF:ID  -0.000239589:0.00311859:0.0268721:0.836506:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868333 ES:SE:LP:AF:ID  -0.00110352:0.00335137:0.130768:0.868333:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131501 ES:SE:LP:AF:ID  0.00159954:0.00335485:0.200659:0.131501:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.86761  ES:SE:LP:AF:ID  -0.00121311:0.00334328:0.142668:0.86761:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867738 ES:SE:LP:AF:ID  -0.00114241:0.00334473:0.136677:0.867738:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867622 ES:SE:LP:AF:ID  -0.00113522:0.00334312:0.136677:0.867622:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.835925 ES:SE:LP:AF:ID  -0.000352295:0.00310993:0.0409586:0.835925:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836577 ES:SE:LP:AF:ID  -0.000435382:0.00311924:0.05061:0.836577:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.837931 ES:SE:LP:AF:ID  -0.000665835:0.00316224:0.0809219:0.837931:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.867897 ES:SE:LP:AF:ID  -0.00126393:0.00333926:0.148742:0.867897:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867441 ES:SE:LP:AF:ID  -0.00142643:0.00333103:0.173925:0.867441:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86635  ES:SE:LP:AF:ID  -0.00165155:0.003325:0.207608:0.86635:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867627 ES:SE:LP:AF:ID  -0.00138056:0.00333399:0.167491:0.867627:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867638 ES:SE:LP:AF:ID  -0.00136967:0.00333425:0.167491:0.867638:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867641 ES:SE:LP:AF:ID  -0.00137867:0.00333427:0.167491:0.867641:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86811  ES:SE:LP:AF:ID  -0.00136818:0.00334349:0.167491:0.86811:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.836485 ES:SE:LP:AF:ID  -0.000114962:0.00310948:0.0132283:0.836485:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.83655  ES:SE:LP:AF:ID  -0.00010706:0.00311108:0.0132283:0.83655:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860581 ES:SE:LP:AF:ID  -0.00162891:0.00332214:0.207608:0.860581:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705645 ES:SE:LP:AF:ID  0.000500698:0.00323777:0.0555173:0.705645:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106072 ES:SE:LP:AF:ID  -0.00114948:0.00372776:0.119186:0.106072:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.757393 ES:SE:LP:AF:ID  -0.00049826:0.00264849:0.0705811:0.757393:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108739 ES:SE:LP:AF:ID  -0.00136085:0.00363792:0.148742:0.108739:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.130948 ES:SE:LP:AF:ID  0.00156064:0.0033553:0.19382:0.130948:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.867477 ES:SE:LP:AF:ID  -0.00132666:0.00333661:0.161151:0.867477:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.131193 ES:SE:LP:AF:ID  0.00189275:0.00335162:0.244125:0.131193:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.867466 ES:SE:LP:AF:ID  -0.00133483:0.00333632:0.161151:0.867466:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.263552 ES:SE:LP:AF:ID  0.00138878:0.0029853:0.19382:0.263552:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.868981 ES:SE:LP:AF:ID  -0.000670064:0.00334659:0.0757207:0.868981:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.097039 ES:SE:LP:AF:ID  -0.000842318:0.00387913:0.0809219:0.097039:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.129725 ES:SE:LP:AF:ID  0.00126444:0.00335873:0.148742:0.129725:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.130064 ES:SE:LP:AF:ID  0.00127723:0.0033523:0.154902:0.130064:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.86758  ES:SE:LP:AF:ID  -0.00113104:0.00333677:0.136677:0.86758:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.102386 ES:SE:LP:AF:ID  -0.00143832:0.00378665:0.154902:0.102386:rs61768199