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-8714/UKB-b-8714_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8714/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8714/UKB-b-8714_data.vcf.gz ...
Read summary statistics for 5440132 SNPs.
Dropped 1943 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, 1167171 SNPs remain.
After merging with regression SNP LD, 1167171 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0045 (0.0011)
Lambda GC: 1.0606
Mean Chi^2: 1.062
Intercept: 1.0202 (0.007)
Ratio: 0.3254 (0.1126)
Analysis finished at Thu Oct 17 14:43:05 2019
Total time elapsed: 59.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9155,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 2.904e-07,
    "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": 47547,
    "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": 1167171,
    "ldsc_nsnp_merge_regression_ld": 1167171,
    "ldsc_observed_scale_h2_beta": 0.0045,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0202,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0606,
    "ldsc_mean_chisq": 1.062,
    "ldsc_ratio": 0.3258
}
 

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 1.00000 3 58 0 5438205 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.00000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.00000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 5440132 0.00000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.00000 NA NA NA NA NA NA NA 8.672844e+00 5.763366e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.00000 NA NA NA NA NA NA NA 7.855603e+07 5.656590e+07 828.0000000 3.195083e+07 6.897197e+07 1.145024e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.00000 NA NA NA NA NA NA NA 3.000000e-07 3.688000e-04 -0.0024157 -2.297000e-04 7.000000e-07 2.302000e-04 2.678900e-03 ▁▂▇▁▁
numeric SE 0 1.00000 NA NA NA NA NA NA NA 3.475000e-04 9.370000e-05 0.0002461 2.691000e-04 3.126000e-04 4.047000e-04 1.164000e-03 ▇▂▁▁▁
numeric PVAL 0 1.00000 NA NA NA NA NA NA NA 4.907331e-01 2.912945e-01 0.0000005 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.00000 NA NA NA NA NA NA NA 4.907328e-01 2.912706e-01 0.0000005 2.359107e-01 4.876898e-01 7.430137e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.00000 NA NA NA NA NA NA NA 3.337806e-01 2.461914e-01 0.0496110 1.230970e-01 2.609770e-01 5.006310e-01 9.503890e-01 ▇▃▂▂▂
numeric AF_reference 47547 0.99126 NA NA NA NA NA NA NA 3.287164e-01 2.409446e-01 0.0000000 1.301920e-01 2.653750e-01 4.904150e-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 0.0008438 0.0004529 0.0619998 0.0624862 0.623769 0.7821490 NA
1 54676 rs2462492 C T 0.0001110 0.0004487 0.8000000 0.8046023 0.400415 NA NA
1 86028 rs114608975 T C -0.0010567 0.0007174 0.1400000 0.1407582 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0010593 0.0004418 0.0160000 0.0164971 0.456849 0.4207270 NA
1 234313 rs8179466 C T 0.0019851 0.0008710 0.0230001 0.0226623 0.074513 NA NA
1 534192 rs6680723 C T 0.0005232 0.0005047 0.2999998 0.2999156 0.240956 NA NA
1 546697 rs12025928 A G 0.0000710 0.0006296 0.9100000 0.9102255 0.913480 NA NA
1 693731 rs12238997 A G -0.0003820 0.0004229 0.3700002 0.3664089 0.116325 0.1417730 NA
1 705882 rs72631875 G A -0.0006096 0.0006198 0.3300000 0.3253258 0.067288 0.0315495 NA
1 706368 rs55727773 A G -0.0001387 0.0003133 0.6600001 0.6579836 0.515647 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218224 rs9616975 C A -0.0001737 0.0004901 0.7199992 0.7230405 0.073342 0.0619010 NA
22 51218377 rs2519461 G C -0.0001749 0.0004895 0.7199992 0.7209460 0.073631 0.0826677 NA
22 51219006 rs28729663 G A -0.0002295 0.0003779 0.5400003 0.5437188 0.137960 0.2052720 NA
22 51219387 rs9616832 T C -0.0001974 0.0004905 0.6899999 0.6874018 0.073753 0.0654952 NA
22 51221190 rs369304721 G A -0.0001711 0.0006562 0.7899998 0.7942500 0.049736 NA NA
22 51221731 rs115055839 T C -0.0001771 0.0004908 0.7199992 0.7181786 0.073244 0.0625000 NA
22 51222100 rs114553188 G T -0.0001325 0.0005779 0.8200001 0.8186386 0.054459 0.0880591 NA
22 51223637 rs375798137 G A -0.0001629 0.0005807 0.7800007 0.7790301 0.054088 0.0788738 NA
22 51229805 rs9616985 T C -0.0001282 0.0004926 0.7899998 0.7946609 0.073079 0.0730831 NA
22 51237063 rs3896457 T C 0.0006395 0.0003013 0.0340001 0.0338131 0.297956 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623769 ES:SE:LP:AF:ID  0.000843752:0.000452941:1.20761:0.623769:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400415 ES:SE:LP:AF:ID  0.000111007:0.000448703:0.09691:0.400415:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  -0.00105672:0.000717406:0.853872:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456849 ES:SE:LP:AF:ID  0.0010593:0.000441793:1.79588:0.456849:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074513 ES:SE:LP:AF:ID  0.00198512:0.000871018:1.63827:0.074513:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  0.00052317:0.000504691:0.522879:0.240956:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91348  ES:SE:LP:AF:ID  7.09881e-05:0.000629583:0.0409586:0.91348:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  -0.000381999:0.00042293:0.431798:0.116325:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  -0.000609569:0.00061975:0.481486:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515647 ES:SE:LP:AF:ID  -0.000138698:0.000313301:0.180456:0.515647:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101212 ES:SE:LP:AF:ID  0.00122571:0.000516844:1.74473:0.101212:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053258 ES:SE:LP:AF:ID  -0.000794411:0.000988062:0.376751:0.053258:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843223 ES:SE:LP:AF:ID  0.000439467:0.000366542:0.638272:0.843223:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055914 ES:SE:LP:AF:ID  5.51449e-05:0.000593438:0.0315171:0.055914:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122303 ES:SE:LP:AF:ID  -0.000394361:0.0004012:0.481486:0.122303:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121546 ES:SE:LP:AF:ID  -0.00035453:0.000401369:0.420216:0.121546:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132322 ES:SE:LP:AF:ID  -0.000324493:0.000395591:0.387216:0.132322:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838958 ES:SE:LP:AF:ID  0.000434763:0.000354966:0.657577:0.838958:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838588 ES:SE:LP:AF:ID  0.00037902:0.000354583:0.537602:0.838588:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869784 ES:SE:LP:AF:ID  0.000373546:0.00038049:0.481486:0.869784:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129864 ES:SE:LP:AF:ID  -0.000308124:0.000381268:0.376751:0.129864:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869128 ES:SE:LP:AF:ID  0.000320721:0.000379745:0.39794:0.869128:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869226 ES:SE:LP:AF:ID  0.00031173:0.000379896:0.387216:0.869226:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86913  ES:SE:LP:AF:ID  0.000324659:0.000379737:0.408935:0.86913:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83804  ES:SE:LP:AF:ID  0.000391267:0.000353599:0.568636:0.83804:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.83867  ES:SE:LP:AF:ID  0.000382914:0.000354592:0.552842:0.83867:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839783 ES:SE:LP:AF:ID  0.000355688:0.000359387:0.49485:0.839783:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869408 ES:SE:LP:AF:ID  0.000353796:0.000379297:0.455932:0.869408:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868954 ES:SE:LP:AF:ID  0.000340321:0.000378341:0.431798:0.868954:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867909 ES:SE:LP:AF:ID  0.000313345:0.00037762:0.387216:0.867909:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869098 ES:SE:LP:AF:ID  0.000341298:0.000378651:0.431798:0.869098:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  0.00034108:0.000378681:0.431798:0.869106:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  0.000340621:0.000378689:0.431798:0.869114:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869592 ES:SE:LP:AF:ID  0.000361735:0.00037973:0.468521:0.869592:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.83832  ES:SE:LP:AF:ID  0.000415933:0.000352928:0.619789:0.83832:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.83844  ES:SE:LP:AF:ID  0.000415923:0.000353177:0.619789:0.83844:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862268 ES:SE:LP:AF:ID  0.0004029:0.000377326:0.537602:0.862268:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706764 ES:SE:LP:AF:ID  0.000321249:0.000367328:0.420216:0.706764:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105136 ES:SE:LP:AF:ID  -0.000154904:0.000423151:0.148742:0.105136:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761336 ES:SE:LP:AF:ID  0.000394257:0.000299816:0.721246:0.761336:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106462 ES:SE:LP:AF:ID  -0.000305487:0.000413283:0.337242:0.106462:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129572 ES:SE:LP:AF:ID  -0.000351394:0.000381037:0.443698:0.129572:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868913 ES:SE:LP:AF:ID  0.00035419:0.000379003:0.455932:0.868913:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129673 ES:SE:LP:AF:ID  -0.000340901:0.000380791:0.431798:0.129673:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868923 ES:SE:LP:AF:ID  0.00035101:0.00037901:0.455932:0.868923:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.2654   ES:SE:LP:AF:ID  1.44418e-07:0.000334868:-0:0.2654:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870044 ES:SE:LP:AF:ID  0.000361048:0.000379782:0.468521:0.870044:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095128 ES:SE:LP:AF:ID  -9.90908e-05:0.000440209:0.0861861:0.095128:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128573 ES:SE:LP:AF:ID  -0.000332512:0.000381281:0.420216:0.128573:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.12887  ES:SE:LP:AF:ID  -0.000348338:0.000380634:0.443698:0.12887:rs4040617