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-22704_irnt/ukb-d-22704_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-22704_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 14:57:56 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22704_irnt/ukb-d-22704_irnt.vcf.gz ...
Read summary statistics for 13586582 SNPs.
Dropped 12710 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.017 (0.0021)
Lambda GC: 1.382
Mean Chi^2: 1.3932
Intercept: 1.2749 (0.0087)
Ratio: 0.6992 (0.022)
Analysis finished at Mon Nov 25 15:00:13 2019
Total time elapsed: 2.0m:17.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3622,
    "mean_EFFECT": 0,
    "n": 361187,
    "n_snps": 13586582,
    "n_clumped_hits": 7,
    "n_p_sig": 53,
    "n_mono": 0,
    "n_ns": 1251809,
    "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": 569298,
    "n_est": 362569.7654,
    "ratio_se_n": 1.0019,
    "mean_diff": 5.7775e-06,
    "ratio_diff": 31.4293,
    "sd_y_est1": 0.8601,
    "sd_y_est2": 0.8618,
    "r2_sum1": 0.0005,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0006,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.017,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.2749,
    "ldsc_intercept_se": 0.0087,
    "ldsc_lambda_gc": 1.382,
    "ldsc_mean_chisq": 1.3932,
    "ldsc_ratio": 0.6991
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 13574536 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57083 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051329e+00 6.184970e+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 7.902506e+07 5.591479e+07 3.02000e+02 3.293101e+07 7.013847e+07 1.148590e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.490000e-05 1.369420e-02 -1.79553e-01 -3.623500e-03 1.000000e-05 3.671700e-03 1.705360e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.504600e-03 8.203900e-03 1.66400e-03 2.421200e-03 4.461800e-03 1.222220e-02 4.127290e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.506928e-01 3.000125e-01 0.00000e+00 1.790280e-01 4.311506e-01 7.094585e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.506924e-01 3.000127e-01 0.00000e+00 1.790268e-01 4.311507e-01 7.094592e-01 9.999999e-01 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908017e-01 2.544020e-01 1.00000e-03 7.429000e-03 6.002920e-02 2.953070e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569298 0.9580985 NA NA NA NA NA 1.963331e-01 2.471005e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.611870e+05 0.000000e+00 3.61187e+05 3.611870e+05 3.611870e+05 3.611870e+05 3.611870e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0015546 0.0035442 0.6609339 0.6609333 0.1106400 0.1894970 361187
1 693731 rs12238997 A G -0.0002193 0.0033488 0.9477910 0.9477910 0.1158310 0.1417730 361187
1 707522 rs371890604 G C 0.0009008 0.0037648 0.8109039 0.8109040 0.0973038 0.1293930 361187
1 717587 rs144155419 G A -0.0065794 0.0089841 0.4639584 0.4639573 0.0156870 0.0045926 361187
1 723329 rs189787166 A T -0.0449601 0.0265051 0.0898338 0.0898327 0.0017337 0.0003994 361187
1 730087 rs148120343 T C 0.0015527 0.0046653 0.7392784 0.7392791 0.0564613 0.0127796 361187
1 731718 rs142557973 T C 0.0002041 0.0031760 0.9487540 0.9487541 0.1217390 0.1543530 361187
1 732032 rs61770163 A C 0.0019622 0.0033879 0.5624721 0.5624719 0.1211700 0.1555510 361187
1 734349 rs141242758 T C 0.0002844 0.0031777 0.9286760 0.9286762 0.1209660 0.1525560 361187
1 740284 rs61770167 C T -0.0177218 0.0145381 0.2228481 0.2228479 0.0057852 0.0023962 361187
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0068398 0.0036692 0.0623031 0.0623016 0.0561678 0.0309934 361187
23 154923374 rs111332691 T A 0.0025594 0.0040325 0.5256335 0.5256336 0.0447870 0.0116556 361187
23 154925045 rs509981 C T 0.0009079 0.0019403 0.6398483 0.6398485 0.2456040 0.3634440 361187
23 154925895 rs538470 C T 0.0007933 0.0019848 0.6893789 0.6893796 0.2419120 0.3634440 361187
23 154927581 rs644138 G A 0.0024042 0.0018247 0.1876269 0.1876275 0.3021610 0.4635760 361187
23 154929412 rs557132 C T 0.0010025 0.0019408 0.6054831 0.6054814 0.2454570 0.3568210 361187
23 154929637 rs35185538 CT C 0.0002855 0.0020256 0.8879150 0.8879147 0.2296950 0.3011920 361187
23 154929952 rs4012982 CAA C 0.0002115 0.0020413 0.9174741 0.9174746 0.2394230 0.3165560 361187
23 154930230 rs781880 A G 0.0008992 0.0019405 0.6431007 0.6431009 0.2458670 0.3618540 361187
23 154930487 rs781879 T A 0.0029932 0.0066571 0.6529847 0.6529842 0.0195615 0.1263580 361187

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11064  ES:SE:LP:AF:SS:ID   -0.00155457:0.00354419:0.179842:0.11064:361187:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115831 ES:SE:LP:AF:SS:ID   -0.000219285:0.00334883:0.0232874:0.115831:361187:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973038    ES:SE:LP:AF:SS:ID   0.000900761:0.00376478:0.0910306:0.0973038:361187:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015687 ES:SE:LP:AF:SS:ID   -0.00657945:0.00898407:0.333521:0.015687:361187:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173366   ES:SE:LP:AF:SS:ID   -0.0449601:0.0265051:1.04656:0.00173366:361187:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564613    ES:SE:LP:AF:SS:ID   0.00155266:0.00466533:0.131192:0.0564613:361187:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121739 ES:SE:LP:AF:SS:ID   0.000204128:0.00317603:0.0228464:0.121739:361187:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12117  ES:SE:LP:AF:SS:ID   0.00196216:0.00338786:0.249899:0.12117:361187:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120966 ES:SE:LP:AF:SS:ID   0.000284441:0.00317774:0.0321358:0.120966:361187:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578523   ES:SE:LP:AF:SS:ID   -0.0177218:0.0145381:0.651991:0.00578523:361187:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018779    ES:SE:LP:AF:SS:ID   0.012311:0.0274567:0.184501:0.0018779:361187:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869741 ES:SE:LP:AF:SS:ID   0.000399476:0.00313275:0.0464665:0.869741:361187:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153024   ES:SE:LP:AF:SS:ID   0.0392445:0.0283604:0.778774:0.00153024:361187:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122917 ES:SE:LP:AF:SS:ID   0.00101132:0.00310258:0.128162:0.122917:361187:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142713 ES:SE:LP:AF:SS:ID   -0.0004242:0.00306673:0.0506173:0.142713:361187:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123032 ES:SE:LP:AF:SS:ID   0.00104964:0.00309826:0.133847:0.123032:361187:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870889 ES:SE:LP:AF:SS:ID   -0.000269895:0.00301915:0.0320923:0.870889:361187:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875471 ES:SE:LP:AF:SS:ID   -0.000994972:0.00306918:0.127377:0.875471:361187:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128632 ES:SE:LP:AF:SS:ID   0.000407882:0.00302672:0.0492448:0.128632:361187:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363607    ES:SE:LP:AF:SS:ID   0.00479415:0.00549123:0.417218:0.0363607:361187:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870483 ES:SE:LP:AF:SS:ID   -0.000425212:0.00301601:0.0516447:0.870483:361187:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870588 ES:SE:LP:AF:SS:ID   -0.000419127:0.00301739:0.0508414:0.870588:361187:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87048  ES:SE:LP:AF:SS:ID   -0.00038432:0.0030159:0.0464341:0.87048:361187:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504377   ES:SE:LP:AF:SS:ID   0.0188744:0.015483:0.652028:0.00504377:361187:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501074   ES:SE:LP:AF:SS:ID   0.0183149:0.0155244:0.623239:0.00501074:361187:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558588   ES:SE:LP:AF:SS:ID   0.00279602:0.0149966:0.0695115:0.00558588:361187:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870562 ES:SE:LP:AF:SS:ID   -0.000478477:0.00301059:0.0586262:0.870562:361187:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125986 ES:SE:LP:AF:SS:ID   0.000634511:0.00307191:0.0776073:0.125986:361187:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870125 ES:SE:LP:AF:SS:ID   -0.000598157:0.00300335:0.0746183:0.870125:361187:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869413 ES:SE:LP:AF:SS:ID   -0.000843992:0.00300061:0.108741:0.869413:361187:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87028  ES:SE:LP:AF:SS:ID   -0.000553461:0.00300593:0.0685843:0.87028:361187:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870286 ES:SE:LP:AF:SS:ID   -0.000554525:0.00300614:0.0687202:0.870286:361187:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870294 ES:SE:LP:AF:SS:ID   -0.000539463:0.00300624:0.0667223:0.870294:361187:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870738 ES:SE:LP:AF:SS:ID   -0.000375101:0.00301389:0.0452979:0.870738:361187:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988461    ES:SE:LP:AF:SS:ID   0.000414639:0.00350232:0.0429873:0.0988461:361187:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647484   ES:SE:LP:AF:SS:ID   0.0176199:0.0135482:0.713499:0.00647484:361187:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874634 ES:SE:LP:AF:SS:ID   -0.000567377:0.00305881:0.0691299:0.874634:361187:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864026 ES:SE:LP:AF:SS:ID   -0.00105882:0.00299962:0.140201:0.864026:361187:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869424 ES:SE:LP:AF:SS:ID   -0.000855511:0.00302874:0.10925:0.869424:361187:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86637  ES:SE:LP:AF:SS:ID   -0.000385952:0.00302936:0.0464234:0.86637:361187:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987837    ES:SE:LP:AF:SS:ID   0.000286476:0.00362671:0.0282419:0.0987837:361187:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871555 ES:SE:LP:AF:SS:ID   -0.000404514:0.00306387:0.0481949:0.871555:361187:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871555 ES:SE:LP:AF:SS:ID   -0.000404559:0.00306387:0.0482007:0.871555:361187:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871554 ES:SE:LP:AF:SS:ID   -0.000403266:0.00306393:0.0480377:0.871554:361187:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871928 ES:SE:LP:AF:SS:ID   -0.000284804:0.00306567:0.0333975:0.871928:361187:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125563 ES:SE:LP:AF:SS:ID   0.000568529:0.00306809:0.0690555:0.125563:361187:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10543  ES:SE:LP:AF:SS:ID   0.00066659:0.00334002:0.0747849:0.10543:361187:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855376 ES:SE:LP:AF:SS:ID   -0.00124972:0.0029985:0.169516:0.855376:361187:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165447   ES:SE:LP:AF:SS:ID   -0.0400292:0.0265621:0.880052:0.00165447:361187:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83836  ES:SE:LP:AF:SS:ID   0.00212723:0.00295407:0.326552:0.83836:361187:rs376645387