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-1658/UKB-b-1658_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1658/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1658/UKB-b-1658_data.vcf.gz ...
Read summary statistics for 5286950 SNPs.
Dropped 1737 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, 1150606 SNPs remain.
After merging with regression SNP LD, 1150606 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0197 (0.0075)
Lambda GC: 1.0236
Mean Chi^2: 1.0255
Intercept: 0.9988 (0.0073)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:46:09 2019
Total time elapsed: 1.0m:0.67s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9127,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -6.4093e-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": 45774,
    "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": 1150606,
    "ldsc_nsnp_merge_regression_ld": 1150606,
    "ldsc_observed_scale_h2_beta": 0.0197,
    "ldsc_observed_scale_h2_se": 0.0075,
    "ldsc_intercept_beta": 0.9988,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0236,
    "ldsc_mean_chisq": 1.0255,
    "ldsc_ratio": -0.0471
}

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 5285226 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 5286950 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 8.673422e+00 5.763223e+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 7.853582e+07 5.658458e+07 828.0000000 3.191573e+07 6.891943e+07 1.144989e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.400000e-06 2.297300e-03 -0.0160559 -1.445800e-03 -2.800000e-06 1.431100e-03 1.616050e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.200500e-03 5.565000e-04 0.0015906 1.732800e-03 1.996300e-03 2.545700e-03 7.605800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.953833e-01 2.902236e-01 0.0000014 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.953847e-01 2.901982e-01 0.0000014 2.428701e-01 4.940227e-01 7.468302e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.398236e-01 2.435591e-01 0.0549020 1.308030e-01 2.694960e-01 5.066100e-01 9.450980e-01 ▇▃▂▂▂
numeric AF_reference 45774 0.9913421 NA NA NA NA NA NA NA 3.342502e-01 2.389875e-01 0.0000000 1.371810e-01 2.733630e-01 4.962060e-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 -0.0021745 0.0029312 0.4600002 0.4581809 0.623812 0.7821490 NA
1 54676 rs2462492 C T 0.0007825 0.0029227 0.7899998 0.7889054 0.399144 NA NA
1 86028 rs114608975 T C -0.0011067 0.0046525 0.8100000 0.8119849 0.103536 0.0277556 NA
1 91536 rs6702460 G T 0.0016987 0.0028747 0.5500004 0.5545791 0.455916 0.4207270 NA
1 234313 rs8179466 C T 0.0022563 0.0056851 0.6899999 0.6914508 0.074455 NA NA
1 534192 rs6680723 C T 0.0022931 0.0032741 0.4799997 0.4836878 0.242057 NA NA
1 546697 rs12025928 A G 0.0021998 0.0040625 0.5900000 0.5881744 0.912862 NA NA
1 693731 rs12238997 A G 0.0023517 0.0027301 0.3900004 0.3890064 0.117313 0.1417730 NA
1 705882 rs72631875 G A -0.0014435 0.0039794 0.7199992 0.7167941 0.067698 0.0315495 NA
1 706368 rs55727773 A G -0.0033685 0.0020264 0.0959997 0.0964607 0.513304 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T 0.0006978 0.0025277 0.7800007 0.7824915 0.126422 0.1727240 NA
22 51216564 rs9616970 T C 0.0007492 0.0025178 0.7700005 0.7660465 0.126887 0.1563500 NA
22 51217954 rs9616974 G A -0.0005875 0.0032068 0.8499999 0.8546275 0.071487 0.0621006 NA
22 51218224 rs9616975 C A -0.0006045 0.0032083 0.8499999 0.8505579 0.071497 0.0619010 NA
22 51218377 rs2519461 G C -0.0003128 0.0032041 0.9199999 0.9222239 0.071792 0.0826677 NA
22 51219006 rs28729663 G A 0.0004023 0.0024649 0.8700001 0.8703377 0.136315 0.2052720 NA
22 51219387 rs9616832 T C -0.0003779 0.0032127 0.9100000 0.9063575 0.071797 0.0654952 NA
22 51221731 rs115055839 T C -0.0007906 0.0032134 0.8100000 0.8056495 0.071348 0.0625000 NA
22 51229805 rs9616985 T C -0.0004001 0.0032233 0.9000000 0.9012115 0.071253 0.0730831 NA
22 51237063 rs3896457 T C 0.0005153 0.0019459 0.7899998 0.7911721 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.00217452:0.00293123:0.337242:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  0.000782504:0.00292271:0.102373:0.399144:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  -0.00110667:0.00465249:0.091515:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  0.00169869:0.00287469:0.259637:0.455916:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074455 ES:SE:LP:AF:ID  0.00225633:0.00568507:0.161151:0.074455:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  0.00229314:0.00327412:0.318759:0.242057:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912862 ES:SE:LP:AF:ID  0.00219976:0.00406247:0.229148:0.912862:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117313 ES:SE:LP:AF:ID  0.00235173:0.00273006:0.408935:0.117313:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067698 ES:SE:LP:AF:ID  -0.0014435:0.00397936:0.142668:0.067698:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  -0.00336847:0.00202644:1.01773:0.513304:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.102736 ES:SE:LP:AF:ID  -0.000971418:0.0033069:0.113509:0.102736:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  -0.0021164:0.002361:0.431798:0.841441:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056334 ES:SE:LP:AF:ID  -0.000231672:0.00383531:0.0222764:0.056334:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  0.00225967:0.00259324:0.420216:0.123078:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  0.00225595:0.00259408:0.420216:0.12233:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  0.00175271:0.00254651:0.309804:0.134139:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  -0.000908128:0.00228398:0.161151:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  -0.000964357:0.0022823:0.173925:0.836733:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  -0.0012427:0.00245245:0.21467:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131004 ES:SE:LP:AF:ID  0.00171064:0.00245875:0.309804:0.131004:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.867976 ES:SE:LP:AF:ID  -0.00163797:0.00244851:0.30103:0.867976:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86805  ES:SE:LP:AF:ID  -0.00163277:0.00244951:0.29243:0.86805:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867987 ES:SE:LP:AF:ID  -0.00159179:0.00244845:0.283997:0.867987:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  -0.00120276:0.00227563:0.221849:0.836159:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  -0.00117138:0.00228186:0.21467:0.836793:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  -0.001164:0.00231398:0.21467:0.838109:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  -0.00154472:0.0024453:0.275724:0.868228:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867742 ES:SE:LP:AF:ID  -0.00159465:0.00243882:0.29243:0.867742:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866644 ES:SE:LP:AF:ID  -0.00182371:0.00243435:0.346787:0.866644:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867911 ES:SE:LP:AF:ID  -0.00159428:0.00244129:0.29243:0.867911:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867923 ES:SE:LP:AF:ID  -0.00157845:0.00244146:0.283997:0.867923:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867932 ES:SE:LP:AF:ID  -0.0015814:0.00244155:0.283997:0.867932:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868398 ES:SE:LP:AF:ID  -0.00146249:0.00244797:0.259637:0.868398:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.836369 ES:SE:LP:AF:ID  -0.00110621:0.00226995:0.200659:0.836369:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.836495 ES:SE:LP:AF:ID  -0.00109285:0.0022715:0.200659:0.836495:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860851 ES:SE:LP:AF:ID  -0.00204608:0.00243289:0.39794:0.860851:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705804 ES:SE:LP:AF:ID  -0.00258504:0.00237408:0.552842:0.705804:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106094 ES:SE:LP:AF:ID  0.00106047:0.00273183:0.154902:0.106094:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.758252 ES:SE:LP:AF:ID  -0.000735964:0.00192421:0.154902:0.758252:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108262 ES:SE:LP:AF:ID  -0.000624047:0.00264841:0.091515:0.108262:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.13066  ES:SE:LP:AF:ID  0.00160267:0.00245781:0.29243:0.13066:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.867852 ES:SE:LP:AF:ID  -0.00136893:0.00244439:0.236572:0.867852:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.130756 ES:SE:LP:AF:ID  0.00146559:0.00245617:0.259637:0.130756:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.867878 ES:SE:LP:AF:ID  -0.0013864:0.00244453:0.244125:0.867878:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.263729 ES:SE:LP:AF:ID  -0.00159597:0.00217428:0.337242:0.263729:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  -0.001666:0.00245097:0.30103:0.869067:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.096639 ES:SE:LP:AF:ID  -0.00230288:0.00282313:0.387216:0.096639:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.129594 ES:SE:LP:AF:ID  0.00173031:0.00246031:0.318759:0.129594:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.129863 ES:SE:LP:AF:ID  0.00175286:0.00245612:0.318759:0.129863:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.867843 ES:SE:LP:AF:ID  -0.00181165:0.00244488:0.337242:0.867843:rs2977612