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-19202/UKB-b-19202_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19202/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19202/UKB-b-19202_data.vcf.gz ...
Read summary statistics for 4820960 SNPs.
Dropped 1253 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, 1090587 SNPs remain.
After merging with regression SNP LD, 1090587 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0066 (0.0073)
Lambda GC: 1.0277
Mean Chi^2: 1.0278
Intercept: 1.0188 (0.0067)
Ratio: 0.6747 (0.2397)
Analysis finished at Thu Oct 17 14:41:59 2019
Total time elapsed: 57.64s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9022,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -9.9443e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 7,
    "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": 40770,
    "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": 1090587,
    "ldsc_nsnp_merge_regression_ld": 1090587,
    "ldsc_observed_scale_h2_beta": 0.0066,
    "ldsc_observed_scale_h2_se": 0.0073,
    "ldsc_intercept_beta": 1.0188,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0277,
    "ldsc_mean_chisq": 1.0278,
    "ldsc_ratio": 0.6763
}

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 4819716 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 4820960 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 8.667867e+00 5.767168e+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 7.857243e+07 5.666279e+07 828.0000000 3.184838e+07 6.892875e+07 1.146394e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -9.900000e-06 1.889700e-03 -0.0116668 -1.220800e-03 -1.120000e-05 1.195800e-03 1.317540e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.824900e-03 3.754000e-04 0.0013925 1.505000e-03 1.692600e-03 2.068700e-03 5.301900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.958412e-01 2.897680e-01 0.0000000 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 4.958421e-01 2.897407e-01 0.0000000 2.439666e-01 4.949147e-01 7.460710e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.593517e-01 2.346003e-01 0.0738090 1.568770e-01 2.969640e-01 5.251400e-01 9.261910e-01 ▇▅▃▂▂
numeric AF_reference 40770 0.9915432 NA NA NA NA NA NA NA 3.520172e-01 2.323697e-01 0.0000000 1.603430e-01 2.981230e-01 5.141770e-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 -0.0004365 0.0025663 0.8600001 0.8649556 0.623812 0.7821490 NA
1 54676 rs2462492 C T -0.0039302 0.0025589 0.1199999 0.1245551 0.399144 NA NA
1 86028 rs114608975 T C 0.0026292 0.0040733 0.5199996 0.5186178 0.103536 0.0277556 NA
1 91536 rs6702460 G T -0.0011368 0.0025168 0.6499995 0.6515058 0.455916 0.4207270 NA
1 234313 rs8179466 C T -0.0030136 0.0049774 0.5400003 0.5448769 0.074455 NA NA
1 534192 rs6680723 C T 0.0021073 0.0028665 0.4600002 0.4622608 0.242057 NA NA
1 546697 rs12025928 A G 0.0014293 0.0035567 0.6899999 0.6877977 0.912862 NA NA
1 693731 rs12238997 A G -0.0018643 0.0023902 0.4400003 0.4353948 0.117313 0.1417730 NA
1 706368 rs55727773 A G 0.0013587 0.0017742 0.4400003 0.4437708 0.513304 0.2751600 NA
1 722670 rs116030099 T C 0.0002143 0.0028952 0.9400001 0.9410082 0.102736 0.0413339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51202748 rs9616963 A G 0.0009908 0.0027806 0.7199992 0.7215941 0.073992 0.0391374 NA
22 51208537 rs72619593 G A 0.0010630 0.0023634 0.6499995 0.6528760 0.120936 0.1142170 NA
22 51210289 rs112565862 C T -0.0054182 0.0023572 0.0219999 0.0215276 0.129762 0.1018370 NA
22 51211106 rs9628250 T C 0.0004149 0.0017544 0.8100000 0.8130368 0.271468 0.1671330 NA
22 51211392 rs3888396 T C -0.0050942 0.0023361 0.0290001 0.0292122 0.132383 0.1641370 NA
22 51212875 rs2238837 A C 0.0010312 0.0016677 0.5400003 0.5363544 0.331351 0.3724040 NA
22 51213613 rs34726907 C T 0.0012079 0.0022132 0.5900000 0.5852215 0.126422 0.1727240 NA
22 51216564 rs9616970 T C 0.0014844 0.0022045 0.5000000 0.5007160 0.126887 0.1563500 NA
22 51219006 rs28729663 G A 0.0022990 0.0021582 0.2900000 0.2867691 0.136315 0.2052720 NA
22 51237063 rs3896457 T C 0.0006947 0.0017038 0.6800001 0.6834517 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.000436454:0.00256633:0.0655015:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  -0.00393025:0.00255887:0.920819:0.399144:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  0.00262923:0.00407331:0.283997:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  -0.00113678:0.00251683:0.187087:0.455916:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074455 ES:SE:LP:AF:ID  -0.00301356:0.00497735:0.267606:0.074455:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  0.00210727:0.00286653:0.337242:0.242057:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912862 ES:SE:LP:AF:ID  0.00142926:0.00355674:0.161151:0.912862:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117313 ES:SE:LP:AF:ID  -0.00186434:0.0023902:0.356547:0.117313:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  0.00135874:0.00177418:0.356547:0.513304:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.102736 ES:SE:LP:AF:ID  0.000214255:0.00289523:0.0268721:0.102736:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  0.0020909:0.00206708:0.508638:0.841441:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  -0.00317772:0.00227042:0.79588:0.123078:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  -0.00336365:0.00227115:0.853872:0.12233:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  -0.00228678:0.0022295:0.508638:0.134139:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  0.00194289:0.00199965:0.481486:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  0.001803:0.00199818:0.431798:0.836733:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  0.00293154:0.00214715:0.769551:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131004 ES:SE:LP:AF:ID  -0.0027082:0.00215267:0.677781:0.131004:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.867976 ES:SE:LP:AF:ID  0.0028256:0.0021437:0.721246:0.867976:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86805  ES:SE:LP:AF:ID  0.00293188:0.00214458:0.769551:0.86805:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867987 ES:SE:LP:AF:ID  0.00281387:0.00214365:0.721246:0.867987:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  0.00173493:0.00199234:0.420216:0.836159:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  0.00172811:0.0019978:0.408935:0.836793:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  0.00200438:0.00202592:0.49485:0.838109:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  0.00292123:0.00214089:0.769551:0.868228:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867742 ES:SE:LP:AF:ID  0.00296219:0.00213522:0.769551:0.867742:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866644 ES:SE:LP:AF:ID  0.00258792:0.0021313:0.657577:0.866644:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867911 ES:SE:LP:AF:ID  0.00284216:0.00213738:0.744727:0.867911:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867923 ES:SE:LP:AF:ID  0.00283937:0.00213753:0.744727:0.867923:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867932 ES:SE:LP:AF:ID  0.00283674:0.00213761:0.744727:0.867932:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868398 ES:SE:LP:AF:ID  0.00291911:0.00214323:0.769551:0.868398:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.836369 ES:SE:LP:AF:ID  0.00162195:0.00198737:0.387216:0.836369:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.836495 ES:SE:LP:AF:ID  0.00162603:0.00198872:0.387216:0.836495:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860851 ES:SE:LP:AF:ID  0.0019714:0.00213003:0.455932:0.860851:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705804 ES:SE:LP:AF:ID  0.00424594:0.00207854:1.38722:0.705804:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106094 ES:SE:LP:AF:ID  -0.00364757:0.00239175:0.886057:0.106094:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.758252 ES:SE:LP:AF:ID  0.00223042:0.00168467:0.721246:0.758252:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108262 ES:SE:LP:AF:ID  -0.00129152:0.00231872:0.236572:0.108262:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.13066  ES:SE:LP:AF:ID  -0.0025224:0.00215185:0.619789:0.13066:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.867852 ES:SE:LP:AF:ID  0.00259782:0.00214009:0.657577:0.867852:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.130756 ES:SE:LP:AF:ID  -0.0024279:0.0021504:0.585027:0.130756:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.867878 ES:SE:LP:AF:ID  0.00257013:0.00214022:0.638272:0.867878:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.263729 ES:SE:LP:AF:ID  -1.28196e-05:0.00190361:0.00436481:0.263729:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  0.00214049:0.00214585:0.49485:0.869067:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.096639 ES:SE:LP:AF:ID  -0.000720296:0.00247169:0.113509:0.096639:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.129594 ES:SE:LP:AF:ID  -0.00193944:0.00215403:0.431798:0.129594:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.129863 ES:SE:LP:AF:ID  -0.00196269:0.00215037:0.443698:0.129863:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.867843 ES:SE:LP:AF:ID  0.00229613:0.00214052:0.552842:0.867843:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.102807 ES:SE:LP:AF:ID  -0.00289665:0.00242759:0.638272:0.102807:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.130424 ES:SE:LP:AF:ID  -0.00194315:0.00215078:0.431798:0.130424:rs6594026