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-20433_irnt/ukb-d-20433_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-20433_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 14:58:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20433_irnt/ukb-d-20433_irnt.vcf.gz ...
Read summary statistics for 13559004 SNPs.
Dropped 12678 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0407 (0.0083)
Lambda GC: 1.0487
Mean Chi^2: 1.0512
Intercept: 1.0023 (0.0057)
Ratio: 0.0442 (0.1108)
Analysis finished at Mon Nov 25 15:00:47 2019
Total time elapsed: 2.0m:15.96s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0331,
    "mean_EFFECT": -0,
    "n": 61033,
    "n_snps": 13559004,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250882,
    "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": 561379,
    "n_est": 61203.2556,
    "ratio_se_n": 1.0014,
    "mean_diff": -3.1244e-06,
    "ratio_diff": 1.1255,
    "sd_y_est1": 0.9749,
    "sd_y_est2": 0.9763,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.0407,
    "ldsc_observed_scale_h2_se": 0.0083,
    "ldsc_intercept_beta": 1.0023,
    "ldsc_intercept_se": 0.0057,
    "ldsc_lambda_gc": 1.0487,
    "ldsc_mean_chisq": 1.0512,
    "ldsc_ratio": 0.0449
}

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 1.0000000 3 94 0 13546990 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57035 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33320 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051365e+00 6.185021e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902435e+07 5.591683e+07 3.02000e+02 3.292604e+07 7.013612e+07 1.148574e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.430000e-05 3.256130e-02 -3.93597e-01 -8.764500e-03 -4.250000e-05 8.705000e-03 4.019960e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.332770e-02 2.246920e-02 4.74140e-03 6.670900e-03 1.225990e-02 3.348520e-02 1.128980e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.946829e-01 2.901737e-01 0.00000e+00 2.416290e-01 4.929848e-01 7.463027e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.946802e-01 2.901753e-01 0.00000e+00 2.416246e-01 4.929822e-01 7.463017e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911642e-01 2.544877e-01 1.00000e-03 7.527800e-03 6.044270e-02 2.960470e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561379 0.9585973 NA NA NA NA NA 1.965919e-01 2.471521e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.087060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.103300e+04 0.000000e+00 6.10330e+04 6.103300e+04 6.103300e+04 6.103300e+04 6.103300e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0082532 0.0096974 0.3947290 0.3947262 0.1123020 0.1894970 61033
1 693731 rs12238997 A G 0.0076403 0.0091765 0.4050737 0.4050708 0.1172270 0.1417730 61033
1 707522 rs371890604 G C 0.0019390 0.0102689 0.8502309 0.8502311 0.0991093 0.1293930 61033
1 717587 rs144155419 G A 0.0075882 0.0249232 0.7607746 0.7607734 0.0155395 0.0045926 61033
1 723329 rs189787166 A T 0.0533771 0.0693623 0.4415755 0.4415725 0.0019008 0.0003994 61033
1 730087 rs148120343 T C -0.0120022 0.0127505 0.3465493 0.3465449 0.0574474 0.0127796 61033
1 731718 rs142557973 T C 0.0057519 0.0087039 0.5087144 0.5087114 0.1232180 0.1543530 61033
1 732032 rs61770163 A C 0.0034456 0.0092723 0.7101891 0.7101883 0.1226840 0.1555510 61033
1 734349 rs141242758 T C 0.0062287 0.0087077 0.4744178 0.4744157 0.1224980 0.1525560 61033
1 740284 rs61770167 C T -0.0112691 0.0396877 0.7764545 0.7764530 0.0058796 0.0023962 61033
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0113968 0.0105826 0.2815088 0.2815081 0.0553551 0.0309934 61033
23 154923374 rs111332691 T A 0.0196571 0.0116659 0.0919920 0.0919876 0.0434519 0.0116556 61033
23 154925045 rs509981 C T -0.0017294 0.0055317 0.7545604 0.7545599 0.2454630 0.3634440 61033
23 154925895 rs538470 C T -0.0008585 0.0056557 0.8793569 0.8793569 0.2418550 0.3634440 61033
23 154927581 rs644138 G A 0.0009716 0.0052071 0.8519751 0.8519744 0.3012320 0.4635760 61033
23 154929412 rs557132 C T -0.0016589 0.0055329 0.7643161 0.7643150 0.2453530 0.3568210 61033
23 154929637 rs35185538 CT C -0.0012209 0.0057798 0.8327001 0.8326993 0.2289170 0.3011920 61033
23 154929952 rs4012982 CAA C -0.0007135 0.0058285 0.9025679 0.9025676 0.2389850 0.3165560 61033
23 154930230 rs781880 A G -0.0017148 0.0055317 0.7565733 0.7565732 0.2456840 0.3618540 61033
23 154930487 rs781879 T A 0.0000666 0.0187792 0.9971710 0.9971709 0.0196031 0.1263580 61033

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112302 ES:SE:LP:AF:SS:ID   -0.00825325:0.00969741:0.403701:0.112302:61033:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117227 ES:SE:LP:AF:SS:ID   0.00764033:0.00917648:0.392466:0.117227:61033:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0991093    ES:SE:LP:AF:SS:ID   0.00193901:0.0102689:0.0704631:0.0991093:61033:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0155395    ES:SE:LP:AF:SS:ID   0.00758825:0.0249232:0.118744:0.0155395:61033:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00190077   ES:SE:LP:AF:SS:ID   0.0533771:0.0693623:0.354995:0.00190077:61033:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0574474    ES:SE:LP:AF:SS:ID   -0.0120022:0.0127505:0.460235:0.0574474:61033:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123218 ES:SE:LP:AF:SS:ID   0.00575194:0.00870391:0.293526:0.123218:61033:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122684 ES:SE:LP:AF:SS:ID   0.00344562:0.00927231:0.148626:0.122684:61033:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122498 ES:SE:LP:AF:SS:ID   0.00622873:0.0087077:0.323839:0.122498:61033:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00587965   ES:SE:LP:AF:SS:ID   -0.0112691:0.0396877:0.109884:0.00587965:61033:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00190206   ES:SE:LP:AF:SS:ID   -0.0101935:0.0745799:0.0499834:0.00190206:61033:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868202 ES:SE:LP:AF:SS:ID   0.00186514:0.00857006:0.0821192:0.868202:61033:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00157029   ES:SE:LP:AF:SS:ID   -0.0314538:0.0767409:0.166277:0.00157029:61033:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124669 ES:SE:LP:AF:SS:ID   0.00186689:0.0084834:0.0831136:0.124669:61033:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143993 ES:SE:LP:AF:SS:ID   -0.00470866:0.00840545:0.240067:0.143993:61033:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124762 ES:SE:LP:AF:SS:ID   0.00172596:0.00847275:0.0764539:0.124762:61033:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869102 ES:SE:LP:AF:SS:ID   -0.0020769:0.00826317:0.0960699:0.869102:61033:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873672 ES:SE:LP:AF:SS:ID   -0.00256344:0.00839312:0.11916:0.873672:61033:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.13029  ES:SE:LP:AF:SS:ID   0.00146956:0.00828754:0.0658774:0.13029:61033:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365868    ES:SE:LP:AF:SS:ID   -0.00312233:0.015085:0.0777813:0.0365868:61033:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86872  ES:SE:LP:AF:SS:ID   -0.0021965:0.00825478:0.102278:0.86872:61033:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868799 ES:SE:LP:AF:SS:ID   -0.00258109:0.00825739:0.122283:0.868799:61033:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868721 ES:SE:LP:AF:SS:ID   -0.00219105:0.00825453:0.102002:0.868721:61033:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00503488   ES:SE:LP:AF:SS:ID   -0.0162855:0.0428205:0.152607:0.00503488:61033:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500186   ES:SE:LP:AF:SS:ID   -0.0150591:0.0429135:0.139272:0.00500186:61033:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00576968   ES:SE:LP:AF:SS:ID   -0.0682438:0.0405596:1.03402:0.00576968:61033:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86877  ES:SE:LP:AF:SS:ID   -0.00188392:0.00824053:0.086627:0.86877:61033:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127668 ES:SE:LP:AF:SS:ID   -8.85274e-05:0.00840917:0.00366348:0.127668:61033:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868325 ES:SE:LP:AF:SS:ID   -0.00135836:0.00821994:0.0611072:0.868325:61033:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867756 ES:SE:LP:AF:SS:ID   -0.00151733:0.00821545:0.0688112:0.867756:61033:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86849  ES:SE:LP:AF:SS:ID   -0.00121197:0.00822734:0.0540944:0.86849:61033:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868496 ES:SE:LP:AF:SS:ID   -0.0012243:0.0082279:0.0546728:0.868496:61033:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868499 ES:SE:LP:AF:SS:ID   -0.0012243:0.00822797:0.0546723:0.868499:61033:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86889  ES:SE:LP:AF:SS:ID   -0.00156988:0.00824738:0.0710739:0.86889:61033:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100641 ES:SE:LP:AF:SS:ID   0.0011895:0.00955238:0.0453229:0.100641:61033:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00661214   ES:SE:LP:AF:SS:ID   -0.066096:0.0369004:1.1351:0.00661214:61033:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872864 ES:SE:LP:AF:SS:ID   -0.00120302:0.00837081:0.0527011:0.872864:61033:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862355 ES:SE:LP:AF:SS:ID   -0.000336394:0.00821341:0.0144249:0.862355:61033:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867599 ES:SE:LP:AF:SS:ID   -0.000609854:0.00829484:0.02623:0.867599:61033:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864827 ES:SE:LP:AF:SS:ID   0.000249605:0.00830359:0.0105417:0.864827:61033:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100679 ES:SE:LP:AF:SS:ID   0.00281736:0.00989343:0.110238:0.100679:61033:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869853 ES:SE:LP:AF:SS:ID   -6.43662e-06:0.00839119:0.00026587:0.869853:61033:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869853 ES:SE:LP:AF:SS:ID   -5.71785e-06:0.00839118:0.00023632:0.869853:61033:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.86985  ES:SE:LP:AF:SS:ID   -1.21516e-05:0.00839119:0.0005019:0.86985:61033:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870162 ES:SE:LP:AF:SS:ID   -0.00114563:0.00839406:0.0499069:0.870162:61033:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127312 ES:SE:LP:AF:SS:ID   0.000732344:0.00839957:0.0312734:0.127312:61033:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107155 ES:SE:LP:AF:SS:ID   0.00324259:0.00912212:0.141317:0.107155:61033:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853578 ES:SE:LP:AF:SS:ID   -0.00337735:0.00821417:0.166881:0.853578:61033:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00181348   ES:SE:LP:AF:SS:ID   0.0613706:0.0696997:0.42183:0.00181348:61033:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837912 ES:SE:LP:AF:SS:ID   0.0135708:0.00815023:1.01818:0.837912:61033:rs376645387