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-8659/UKB-b-8659_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8659/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-8659/UKB-b-8659_data.vcf.gz ...
Read summary statistics for 4251245 SNPs.
Dropped 874 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, 998282 SNPs remain.
After merging with regression SNP LD, 998282 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0131 (0.0082)
Lambda GC: 1.0386
Mean Chi^2: 1.0359
Intercept: 1.0176 (0.0082)
Ratio: 0.4906 (0.2284)
Analysis finished at Thu Oct 17 14:42:58 2019
Total time elapsed: 52.05s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.885,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 3.2806e-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": 34968,
    "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": 998282,
    "ldsc_nsnp_merge_regression_ld": 998282,
    "ldsc_observed_scale_h2_beta": 0.0131,
    "ldsc_observed_scale_h2_se": 0.0082,
    "ldsc_intercept_beta": 1.0176,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.0386,
    "ldsc_mean_chisq": 1.0359,
    "ldsc_ratio": 0.4903
}

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 4250376 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 4251245 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 8.656113e+00 5.766084e+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 7.859026e+07 5.672868e+07 828.0000000 3.167815e+07 6.896946e+07 1.146705e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.300000e-06 1.521800e-03 -0.0088586 -9.962000e-04 -2.200000e-06 1.005200e-03 9.102000e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.476600e-03 2.306000e-04 0.0011921 1.277400e-03 1.399300e-03 1.632500e-03 4.381200e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.932701e-01 2.902078e-01 0.0000008 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 4.932723e-01 2.901840e-01 0.0000008 2.407205e-01 4.905501e-01 7.444222e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.835157e-01 2.202781e-01 0.1032150 1.920640e-01 3.311110e-01 5.445500e-01 8.967850e-01 ▇▅▃▂▂
numeric AF_reference 34968 0.9917746 NA NA NA NA NA NA NA 3.737525e-01 2.220438e-01 0.0000000 1.908950e-01 3.290730e-01 5.327480e-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 -0.0005958 0.0021970 0.7899998 0.7862515 0.623812 0.7821490 NA
1 54676 rs2462492 C T 0.0019678 0.0021906 0.3700002 0.3690312 0.399144 NA NA
1 86028 rs114608975 T C -0.0022316 0.0034871 0.5199996 0.5221949 0.103536 0.0277556 NA
1 91536 rs6702460 G T 0.0008292 0.0021546 0.6999999 0.7003682 0.455916 0.4207270 NA
1 534192 rs6680723 C T -0.0025256 0.0024540 0.2999998 0.3034005 0.242057 NA NA
1 693731 rs12238997 A G 0.0025221 0.0020462 0.2200002 0.2177406 0.117313 0.1417730 NA
1 706368 rs55727773 A G -0.0018201 0.0015189 0.2300001 0.2307823 0.513304 0.2751600 NA
1 729679 rs4951859 C G -0.0018364 0.0017696 0.2999998 0.2993847 0.841441 0.6399760 NA
1 731718 rs142557973 T C 0.0029293 0.0019437 0.1299999 0.1317897 0.123078 0.1543530 NA
1 734349 rs141242758 T C 0.0028850 0.0019443 0.1400000 0.1378568 0.122330 0.1525560 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G 0.0007699 0.0015140 0.6100002 0.6110762 0.254586 0.0984425 NA
22 51208537 rs72619593 G A -0.0025176 0.0020231 0.2099999 0.2133570 0.120936 0.1142170 NA
22 51210289 rs112565862 C T -0.0054856 0.0020178 0.0065999 0.0065548 0.129762 0.1018370 NA
22 51211106 rs9628250 T C 0.0005283 0.0015018 0.7300002 0.7250029 0.271468 0.1671330 NA
22 51211392 rs3888396 T C -0.0054972 0.0019997 0.0060000 0.0059792 0.132383 0.1641370 NA
22 51212875 rs2238837 A C 0.0030318 0.0014276 0.0340001 0.0336947 0.331351 0.3724040 NA
22 51213613 rs34726907 C T 0.0017351 0.0018945 0.3599996 0.3597286 0.126422 0.1727240 NA
22 51216564 rs9616970 T C 0.0019892 0.0018870 0.2900000 0.2918176 0.126887 0.1563500 NA
22 51219006 rs28729663 G A 0.0023787 0.0018474 0.2000000 0.1978900 0.136315 0.2052720 NA
22 51237063 rs3896457 T C 0.0017333 0.0014584 0.2300001 0.2346543 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.000595791:0.00219702:0.102373:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  0.00196782:0.00219063:0.431798:0.399144:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  -0.00223165:0.00348714:0.283997:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  0.000829156:0.00215464:0.154902:0.455916:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  -0.0025256:0.00245402:0.522879:0.242057:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.117313 ES:SE:LP:AF:ID  0.00252211:0.00204624:0.657577:0.117313:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  -0.00182012:0.00151886:0.638272:0.513304:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  -0.00183643:0.00176962:0.522879:0.841441:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  0.0029293:0.00194369:0.886057:0.123078:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  0.00288502:0.00194432:0.853872:0.12233:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  0.00138103:0.00190866:0.327902:0.134139:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  -0.00246612:0.00171189:0.823909:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  -0.00243355:0.00171063:0.823909:0.836733:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  -0.00391258:0.00183816:1.48149:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131004 ES:SE:LP:AF:ID  0.00362139:0.00184289:1.3098:0.131004:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.867976 ES:SE:LP:AF:ID  -0.00380967:0.00183521:1.42022:0.867976:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86805  ES:SE:LP:AF:ID  -0.00370814:0.00183596:1.36653:0.86805:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867987 ES:SE:LP:AF:ID  -0.00381462:0.00183516:1.42022:0.867987:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  -0.00229871:0.00170563:0.744727:0.836159:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  -0.0023512:0.0017103:0.769551:0.836793:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  -0.00275023:0.00173438:0.958607:0.838109:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  -0.00376425:0.0018328:1.39794:0.868228:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867742 ES:SE:LP:AF:ID  -0.00377351:0.00182795:1.40894:0.867742:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866644 ES:SE:LP:AF:ID  -0.00366793:0.0018246:1.35655:0.866644:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867911 ES:SE:LP:AF:ID  -0.00380649:0.0018298:1.42022:0.867911:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867923 ES:SE:LP:AF:ID  -0.00381022:0.00182993:1.4318:0.867923:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867932 ES:SE:LP:AF:ID  -0.00381636:0.00182999:1.4318:0.867932:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868398 ES:SE:LP:AF:ID  -0.00377931:0.00183481:1.40894:0.868398:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.836369 ES:SE:LP:AF:ID  -0.00247863:0.00170138:0.823909:0.836369:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.836495 ES:SE:LP:AF:ID  -0.00242784:0.00170254:0.823909:0.836495:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860851 ES:SE:LP:AF:ID  -0.00394344:0.0018235:1.50864:0.860851:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705804 ES:SE:LP:AF:ID  -0.00160942:0.00177942:0.431798:0.705804:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106094 ES:SE:LP:AF:ID  0.00365409:0.00204756:1.13077:0.106094:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.758252 ES:SE:LP:AF:ID  -0.00151068:0.00144223:0.537602:0.758252:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108262 ES:SE:LP:AF:ID  -0.00201327:0.00198504:0.508638:0.108262:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.13066  ES:SE:LP:AF:ID  0.00354474:0.00184218:1.26761:0.13066:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.867852 ES:SE:LP:AF:ID  -0.00391293:0.00183212:1.48149:0.867852:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.130756 ES:SE:LP:AF:ID  0.00357016:0.00184095:1.284:0.130756:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.867878 ES:SE:LP:AF:ID  -0.00394901:0.00183223:1.50864:0.867878:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.263729 ES:SE:LP:AF:ID  -0.00197192:0.00162967:0.638272:0.263729:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  -0.00399872:0.00183705:1.52288:0.869067:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.129594 ES:SE:LP:AF:ID  0.00359041:0.00184406:1.284:0.129594:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.129863 ES:SE:LP:AF:ID  0.00371281:0.00184091:1.35655:0.129863:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.867843 ES:SE:LP:AF:ID  -0.00409969:0.00183249:1.60206:0.867843:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.130424 ES:SE:LP:AF:ID  0.00384184:0.00184127:1.4318:0.130424:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.867493 ES:SE:LP:AF:ID  -0.00404153:0.00183194:1.56864:0.867493:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.867448 ES:SE:LP:AF:ID  -0.00401171:0.00183322:1.5376:0.867448:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.859749 ES:SE:LP:AF:ID  -0.00382811:0.00183265:1.4318:0.859749:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.129403 ES:SE:LP:AF:ID  0.00361757:0.0018508:1.29243:0.129403:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.860334 ES:SE:LP:AF:ID  -0.00429134:0.00183368:1.72125:0.860334:rs2905054