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/dev/ukb-d-import/processed/ukb-d-20420_irnt/ukb-d-20420_irnt.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20420_irnt/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 14:56:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20420_irnt/ukb-d-20420_irnt.vcf.gz ...
Read summary statistics for 13529185 SNPs.
Dropped 12625 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283493 SNPs remain.
After merging with regression SNP LD, 1283493 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0645 (0.0175)
Lambda GC: 1.0287
Mean Chi^2: 1.0251
Intercept: 0.9941 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 14:58:19 2019
Total time elapsed: 2.0m:18.04s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0177,
    "mean_EFFECT": 0.0001,
    "n": 24738,
    "n_snps": 13529185,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1249732,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 554061,
    "n_est": 24842.5202,
    "ratio_se_n": 1.0021,
    "mean_diff": -4.9223e-06,
    "ratio_diff": 1.0789,
    "sd_y_est1": 1.0026,
    "sd_y_est2": 1.0047,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283493,
    "ldsc_nsnp_merge_regression_ld": 1283493,
    "ldsc_observed_scale_h2_beta": 0.0645,
    "ldsc_observed_scale_h2_se": 0.0175,
    "ldsc_intercept_beta": 0.9941,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0287,
    "ldsc_mean_chisq": 1.0251,
    "ldsc_ratio": -0.2351
}
 

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.000000 3 94 0 13517223 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 56973 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33301 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.051931e+00 6.185139e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.902246e+07 5.591707e+07 3.0200e+02 3.292006e+07 7.013347e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 7.710000e-05 5.202560e-02 -6.8746e-01 -1.383190e-02 5.440000e-05 1.397530e-02 6.509960e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 3.747100e-02 3.604940e-02 7.6372e-03 1.076800e-02 1.973240e-02 5.373240e-02 2.065800e-01 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.973807e-01 2.889964e-01 0.0000e+00 2.468340e-01 4.962266e-01 7.475926e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.973743e-01 2.890002e-01 0.0000e+00 2.468227e-01 4.962195e-01 7.475894e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 1.915616e-01 2.545867e-01 1.0000e-03 7.626900e-03 6.095870e-02 2.968730e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 554061 0.959047 NA NA NA NA NA 1.968913e-01 2.472226e-01 0.0000e+00 5.790700e-03 8.506390e-02 3.093050e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 2.473800e+04 0.000000e+00 2.4738e+04 2.473800e+04 2.473800e+04 2.473800e+04 2.473800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0113294 0.0157793 0.4727690 0.4727627 0.1116140 0.1894970 24738
1 693731 rs12238997 A G 0.0081868 0.0148069 0.5803353 0.5803298 0.1172340 0.1417730 24738
1 707522 rs371890604 G C -0.0007794 0.0166539 0.9626730 0.9626729 0.0985421 0.1293930 24738
1 717587 rs144155419 G A 0.0204639 0.0393541 0.6030718 0.6030677 0.0161810 0.0045926 24738
1 723329 rs189787166 A T -0.0320354 0.1120730 0.7750005 0.7749976 0.0019043 0.0003994 24738
1 730087 rs148120343 T C 0.0047032 0.0207796 0.8209420 0.8209402 0.0567203 0.0127796 24738
1 731718 rs142557973 T C 0.0082659 0.0140406 0.5560604 0.5560540 0.1234480 0.1543530 24738
1 732032 rs61770163 A C 0.0077124 0.0149992 0.6071276 0.6071233 0.1226690 0.1555510 24738
1 734349 rs141242758 T C 0.0095369 0.0140521 0.4973476 0.4973406 0.1226840 0.1525560 24738
1 740284 rs61770167 C T 0.0433548 0.0640065 0.4981900 0.4981839 0.0059371 0.0023962 24738
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0020125 0.0167714 0.9044869 0.9044864 0.0563293 0.0309934 24738
23 154923374 rs111332691 T A -0.0130446 0.0189341 0.4908627 0.4908563 0.0430108 0.0116556 24738
23 154925045 rs509981 C T -0.0096224 0.0088946 0.2793361 0.2793251 0.2461480 0.3634440 24738
23 154925895 rs538470 C T -0.0089926 0.0090954 0.3228167 0.3228079 0.2424960 0.3634440 24738
23 154927581 rs644138 G A -0.0088944 0.0083672 0.2877902 0.2877793 0.3029660 0.4635760 24738
23 154929412 rs557132 C T -0.0097655 0.0088965 0.2723579 0.2723468 0.2460790 0.3568210 24738
23 154929637 rs35185538 CT C -0.0066915 0.0093040 0.4720185 0.4720113 0.2291920 0.3011920 24738
23 154929952 rs4012982 CAA C -0.0067359 0.0093711 0.4722740 0.4722669 0.2397140 0.3165560 24738
23 154930230 rs781880 A G -0.0094009 0.0088982 0.2907529 0.2907430 0.2462950 0.3618540 24738
23 154930487 rs781879 T A -0.0299944 0.0288888 0.2991541 0.2991440 0.0209781 0.1263580 24738

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111614 ES:SE:LP:AF:SS:ID   0.0113294:0.0157793:0.325351:0.111614:24738:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117234 ES:SE:LP:AF:SS:ID   0.00818678:0.0148069:0.236321:0.117234:24738:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0985421    ES:SE:LP:AF:SS:ID   -0.000779396:0.0166539:0.0165212:0.0985421:24738:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.016181 ES:SE:LP:AF:SS:ID   0.0204639:0.0393541:0.219631:0.016181:24738:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00190427   ES:SE:LP:AF:SS:ID   -0.0320354:0.112073:0.110698:0.00190427:24738:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0567203    ES:SE:LP:AF:SS:ID   0.00470317:0.0207796:0.0856875:0.0567203:24738:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123448 ES:SE:LP:AF:SS:ID   0.00826588:0.0140406:0.254878:0.123448:24738:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122669 ES:SE:LP:AF:SS:ID   0.00771235:0.0149992:0.21672:0.122669:24738:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122684 ES:SE:LP:AF:SS:ID   0.00953688:0.0140521:0.30334:0.122684:24738:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00593712   ES:SE:LP:AF:SS:ID   0.0433548:0.0640065:0.302605:0.00593712:24738:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00195524   ES:SE:LP:AF:SS:ID   0.144624:0.119372:0.646466:0.00195524:24738:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867947 ES:SE:LP:AF:SS:ID   -0.0129223:0.013841:0.455303:0.867947:24738:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00167988   ES:SE:LP:AF:SS:ID   -0.049575:0.118875:0.169631:0.00167988:24738:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124953 ES:SE:LP:AF:SS:ID   0.0141596:0.013702:0.520815:0.124953:24738:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14488  ES:SE:LP:AF:SS:ID   0.0119104:0.0135571:0.420602:0.14488:24738:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124995 ES:SE:LP:AF:SS:ID   0.0139604:0.013687:0.511805:0.124995:24738:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868672 ES:SE:LP:AF:SS:ID   -0.0133713:0.0133504:0.49954:0.868672:24738:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873546 ES:SE:LP:AF:SS:ID   -0.0149393:0.0135749:0.566834:0.873546:24738:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130918 ES:SE:LP:AF:SS:ID   0.0120902:0.0133797:0.436277:0.130918:24738:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0378365    ES:SE:LP:AF:SS:ID   0.0227194:0.0240013:0.463623:0.0378365:24738:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868191 ES:SE:LP:AF:SS:ID   -0.0139276:0.0133326:0.528408:0.868191:24738:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868213 ES:SE:LP:AF:SS:ID   -0.0135961:0.0133338:0.511597:0.868213:24738:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86818  ES:SE:LP:AF:SS:ID   -0.0139211:0.013332:0.528112:0.86818:24738:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00533909   ES:SE:LP:AF:SS:ID   0.0475434:0.0667073:0.322367:0.00533909:24738:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00531531   ES:SE:LP:AF:SS:ID   0.0466508:0.0668354:0.314092:0.00531531:24738:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00571432   ES:SE:LP:AF:SS:ID   0.0382499:0.0653806:0.252953:0.00571432:24738:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868393 ES:SE:LP:AF:SS:ID   -0.0136419:0.013315:0.514869:0.868393:24738:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128122 ES:SE:LP:AF:SS:ID   0.0114134:0.0135712:0.397557:0.128122:24738:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867956 ES:SE:LP:AF:SS:ID   -0.013276:0.0132839:0.49811:0.867956:24738:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867225 ES:SE:LP:AF:SS:ID   -0.0126981:0.0132653:0.470502:0.867225:24738:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868079 ES:SE:LP:AF:SS:ID   -0.013805:0.0132914:0.524354:0.868079:24738:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868085 ES:SE:LP:AF:SS:ID   -0.0138371:0.0132921:0.525951:0.868085:24738:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868085 ES:SE:LP:AF:SS:ID   -0.0138531:0.0132921:0.526767:0.868085:24738:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868488 ES:SE:LP:AF:SS:ID   -0.0141468:0.0133245:0.540041:0.868488:24738:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100269 ES:SE:LP:AF:SS:ID   0.00554375:0.0154518:0.14281:0.100269:24738:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00680671   ES:SE:LP:AF:SS:ID   -0.00464258:0.0584843:0.0283856:0.00680671:24738:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872578 ES:SE:LP:AF:SS:ID   -0.0142433:0.0135285:0.533984:0.872578:24738:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86128  ES:SE:LP:AF:SS:ID   -0.0130206:0.0132579:0.486701:0.86128:24738:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867502 ES:SE:LP:AF:SS:ID   -0.0153582:0.0134117:0.598313:0.867502:24738:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864488 ES:SE:LP:AF:SS:ID   -0.0117416:0.013418:0.41845:0.864488:24738:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.101219 ES:SE:LP:AF:SS:ID   0.0216434:0.0159226:0.759286:0.101219:24738:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.8696   ES:SE:LP:AF:SS:ID   -0.0119795:0.0135555:0.423836:0.8696:24738:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.8696   ES:SE:LP:AF:SS:ID   -0.0119817:0.0135555:0.423934:0.8696:24738:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869596 ES:SE:LP:AF:SS:ID   -0.0119925:0.0135555:0.424431:0.869596:24738:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869949 ES:SE:LP:AF:SS:ID   -0.0114461:0.013564:0.399291:0.869949:24738:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127604 ES:SE:LP:AF:SS:ID   0.0124913:0.0135689:0.446995:0.127604:24738:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106828 ES:SE:LP:AF:SS:ID   0.00908784:0.0147396:0.269596:0.106828:24738:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853048 ES:SE:LP:AF:SS:ID   -0.0112557:0.0132469:0.402844:0.853048:24738:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00182889   ES:SE:LP:AF:SS:ID   -0.0434135:0.112681:0.154881:0.00182889:24738:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838112 ES:SE:LP:AF:SS:ID   -0.0132972:0.0131643:0.505206:0.838112:24738:rs376645387