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-30500_irnt/ukb-d-30500_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-30500_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 14:53:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30500_irnt/ukb-d-30500_irnt.vcf.gz ...
Read summary statistics for 13571116 SNPs.
Dropped 12696 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, 1283499 SNPs remain.
After merging with regression SNP LD, 1283499 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0322 (0.0051)
Lambda GC: 1.0658
Mean Chi^2: 1.0758
Intercept: 1.0054 (0.0074)
Ratio: 0.0709 (0.0983)
Analysis finished at Mon Nov 25 14:56:15 2019
Total time elapsed: 2.0m:49.06s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0436,
    "mean_EFFECT": -0,
    "n": 108706,
    "n_snps": 13571116,
    "n_clumped_hits": 5,
    "n_p_sig": 61,
    "n_mono": 0,
    "n_ns": 1251335,
    "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": 565532,
    "n_est": 109256.518,
    "ratio_se_n": 1.0025,
    "mean_diff": 1.9684e-06,
    "ratio_diff": 1.0091,
    "sd_y_est1": 0.9985,
    "sd_y_est2": 1.001,
    "r2_sum1": 0.0026,
    "r2_sum2": 0.0026,
    "r2_sum3": 0.0026,
    "r2_sum4": 0.0026,
    "ldsc_nsnp_merge_refpanel_ld": 1283499,
    "ldsc_nsnp_merge_regression_ld": 1283499,
    "ldsc_observed_scale_h2_beta": 0.0322,
    "ldsc_observed_scale_h2_se": 0.0051,
    "ldsc_intercept_beta": 1.0054,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.0658,
    "ldsc_mean_chisq": 1.0758,
    "ldsc_ratio": 0.0712
}

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 13559084 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57064 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33329 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051335e+00 6.184827e+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 7.902533e+07 5.591519e+07 3.02000e+02 3.292863e+07 7.014106e+07 1.148611e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.760000e-05 2.498360e-02 -3.24294e-01 -6.765400e-03 2.640000e-05 6.792700e-03 4.498730e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.794070e-02 1.729700e-02 3.45260e-03 5.121600e-03 9.422500e-03 2.576260e-02 8.891760e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.931605e-01 2.908426e-01 0.00000e+00 2.391603e-01 4.908005e-01 7.454525e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.931590e-01 2.908434e-01 0.00000e+00 2.391574e-01 4.907983e-01 7.454526e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910040e-01 2.544515e-01 1.00000e-03 7.481700e-03 6.024510e-02 2.957420e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 565532 0.9583283 NA NA NA NA NA 1.964835e-01 2.471353e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.087060e+05 0.000000e+00 1.08706e+05 1.087060e+05 1.087060e+05 1.087060e+05 1.087060e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0033104 0.0075470 0.6609247 0.6609235 0.1098300 0.1894970 108706
1 693731 rs12238997 A G 0.0020452 0.0071163 0.7738076 0.7738064 0.1151960 0.1417730 108706
1 707522 rs371890604 G C -0.0002792 0.0080060 0.9721800 0.9721804 0.0970262 0.1293930 108706
1 717587 rs144155419 G A -0.0037162 0.0191630 0.8462350 0.8462348 0.0155164 0.0045926 108706
1 723329 rs189787166 A T -0.0770840 0.0569453 0.1758511 0.1758481 0.0016846 0.0003994 108706
1 730087 rs148120343 T C -0.0012090 0.0099258 0.9030510 0.9030507 0.0561206 0.0127796 108706
1 731718 rs142557973 T C -0.0026327 0.0067504 0.6965351 0.6965344 0.1211770 0.1543530 108706
1 732032 rs61770163 A C 0.0021541 0.0072021 0.7648724 0.7648730 0.1208790 0.1555510 108706
1 734349 rs141242758 T C -0.0024737 0.0067534 0.7141460 0.7141452 0.1204320 0.1525560 108706
1 740284 rs61770167 C T 0.0260221 0.0310025 0.4012731 0.4012702 0.0057180 0.0023962 108706
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0025134 0.0075475 0.7391252 0.7391250 0.0570625 0.0309934 108706
23 154923374 rs111332691 T A 0.0063998 0.0083231 0.4419417 0.4419401 0.0452321 0.0116556 108706
23 154925045 rs509981 C T -0.0041096 0.0040546 0.3107921 0.3107893 0.2408370 0.3634440 108706
23 154925895 rs538470 C T -0.0038631 0.0041469 0.3515734 0.3515706 0.2375210 0.3634440 108706
23 154927581 rs644138 G A -0.0029417 0.0037997 0.4388277 0.4388263 0.2982470 0.4635760 108706
23 154929412 rs557132 C T -0.0041272 0.0040557 0.3088553 0.3088517 0.2407170 0.3568210 108706
23 154929637 rs35185538 CT C -0.0035087 0.0042315 0.4069959 0.4069939 0.2256290 0.3011920 108706
23 154929952 rs4012982 CAA C -0.0036008 0.0042659 0.3986328 0.3986305 0.2347650 0.3165560 108706
23 154930230 rs781880 A G -0.0038756 0.0040550 0.3391939 0.3391917 0.2411790 0.3618540 108706
23 154930487 rs781879 T A -0.0014342 0.0139443 0.9180791 0.9180787 0.0192303 0.1263580 108706

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.10983  ES:SE:LP:AF:SS:ID   0.0033104:0.00754699:0.179848:0.10983:108706:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115196 ES:SE:LP:AF:SS:ID   0.00204521:0.00711626:0.111367:0.115196:108706:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0970262    ES:SE:LP:AF:SS:ID   -0.000279198:0.00800596:0.0122533:0.0970262:108706:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0155164    ES:SE:LP:AF:SS:ID   -0.00371618:0.019163:0.072509:0.0155164:108706:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00168461   ES:SE:LP:AF:SS:ID   -0.077084:0.0569453:0.754855:0.00168461:108706:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0561206    ES:SE:LP:AF:SS:ID   -0.00120904:0.00992575:0.0442877:0.0561206:108706:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121177 ES:SE:LP:AF:SS:ID   -0.00263266:0.00675036:0.157057:0.121177:108706:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.120879 ES:SE:LP:AF:SS:ID   0.00215407:0.00720213:0.116411:0.120879:108706:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120432 ES:SE:LP:AF:SS:ID   -0.00247372:0.00675336:0.146213:0.120432:108706:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00571801   ES:SE:LP:AF:SS:ID   0.0260221:0.0310025:0.39656:0.00571801:108706:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00186585   ES:SE:LP:AF:SS:ID   -0.0740646:0.0581413:0.693121:0.00186585:108706:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.870325 ES:SE:LP:AF:SS:ID   0.00301211:0.0066591:0.186397:0.870325:108706:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00156423   ES:SE:LP:AF:SS:ID   -0.00422143:0.0591268:0.0254501:0.00156423:108706:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122336 ES:SE:LP:AF:SS:ID   -0.00215221:0.00659436:0.128343:0.122336:108706:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142191 ES:SE:LP:AF:SS:ID   -0.00390987:0.00651885:0.260701:0.142191:108706:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.122437 ES:SE:LP:AF:SS:ID   -0.00228864:0.00658598:0.13774:0.122437:108706:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.871453 ES:SE:LP:AF:SS:ID   0.0021151:0.00641858:0.129738:0.871453:108706:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875937 ES:SE:LP:AF:SS:ID   0.00240199:0.00652295:0.147094:0.875937:108706:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128045 ES:SE:LP:AF:SS:ID   -0.00243111:0.00643462:0.151462:0.128045:108706:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0359226    ES:SE:LP:AF:SS:ID   -0.00212338:0.0116899:0.0675952:0.0359226:108706:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.871076 ES:SE:LP:AF:SS:ID   0.00244696:0.0064126:0.153187:0.871076:108706:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.871187 ES:SE:LP:AF:SS:ID   0.00213025:0.00641506:0.130864:0.871187:108706:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.871066 ES:SE:LP:AF:SS:ID   0.00246687:0.00641215:0.154625:0.871066:108706:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00494457   ES:SE:LP:AF:SS:ID   -0.0127437:0.0331437:0.154524:0.00494457:108706:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00490346   ES:SE:LP:AF:SS:ID   -0.0122726:0.0332523:0.147475:0.00490346:108706:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00569339   ES:SE:LP:AF:SS:ID   0.0336243:0.0314136:0.545986:0.00569339:108706:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87102  ES:SE:LP:AF:SS:ID   0.00173102:0.00639733:0.104184:0.87102:108706:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125537 ES:SE:LP:AF:SS:ID   -0.00143996:0.00652865:0.0833166:0.125537:108706:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870555 ES:SE:LP:AF:SS:ID   0.000979738:0.00638256:0.0565045:0.870555:108706:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869872 ES:SE:LP:AF:SS:ID   0.00233562:0.00637614:0.146218:0.869872:108706:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870729 ES:SE:LP:AF:SS:ID   0.00131475:0.00638722:0.0773181:0.870729:108706:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870736 ES:SE:LP:AF:SS:ID   0.00132954:0.00638775:0.0782506:0.870736:108706:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87074  ES:SE:LP:AF:SS:ID   0.00132242:0.00638781:0.0777979:0.87074:108706:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.871221 ES:SE:LP:AF:SS:ID   0.00165699:0.00640464:0.0991666:0.871221:108706:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0985354    ES:SE:LP:AF:SS:ID   -0.00269146:0.00743836:0.144193:0.0985354:108706:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00664905   ES:SE:LP:AF:SS:ID   0.00990406:0.028321:0.138729:0.00664905:108706:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.875214 ES:SE:LP:AF:SS:ID   0.00130286:0.00650172:0.0751116:0.875214:108706:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864496 ES:SE:LP:AF:SS:ID   0.00145183:0.00637518:0.0862629:0.864496:108706:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869919 ES:SE:LP:AF:SS:ID   0.00133851:0.00643826:0.0781534:0.869919:108706:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866861 ES:SE:LP:AF:SS:ID   0.00288091:0.00643747:0.184091:0.866861:108706:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0981944    ES:SE:LP:AF:SS:ID   0.00155469:0.00771154:0.0756039:0.0981944:108706:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.872175 ES:SE:LP:AF:SS:ID   0.00262691:0.00651476:0.16318:0.872175:108706:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.872175 ES:SE:LP:AF:SS:ID   0.00262782:0.00651476:0.163245:0.872175:108706:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.872173 ES:SE:LP:AF:SS:ID   0.00262802:0.00651478:0.163258:0.872173:108706:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.872573 ES:SE:LP:AF:SS:ID   0.00268688:0.00652:0.16732:0.872573:108706:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125071 ES:SE:LP:AF:SS:ID   -0.00191886:0.00651982:0.114345:0.125071:108706:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105296 ES:SE:LP:AF:SS:ID   -0.00207538:0.00709565:0.113557:0.105296:108706:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855952 ES:SE:LP:AF:SS:ID   0.00264833:0.00637214:0.168966:0.855952:108706:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00162381   ES:SE:LP:AF:SS:ID   -0.0842482:0.0568057:0.859957:0.00162381:108706:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838089 ES:SE:LP:AF:SS:ID   -0.0103975:0.0062386:1.0196:0.838089:108706:rs376645387