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-4957/ukb-d-4957.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-4957/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 17:16:39 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4957/ukb-d-4957.vcf.gz ...
Read summary statistics for 13567694 SNPs.
Dropped 12693 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0831 (0.0056)
Lambda GC: 1.1715
Mean Chi^2: 1.1993
Intercept: 1.0088 (0.0066)
Ratio: 0.0439 (0.0333)
Analysis finished at Mon Nov 25 17:19:04 2019
Total time elapsed: 2.0m:25.32s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1074,
    "mean_EFFECT": -0,
    "n": 116815,
    "n_snps": 13567694,
    "n_clumped_hits": 3,
    "n_p_sig": 52,
    "n_mono": 0,
    "n_ns": 1251201,
    "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": 563206,
    "n_est": 117278.8432,
    "ratio_se_n": 1.002,
    "mean_diff": -0.0001,
    "ratio_diff": 18.6279,
    "sd_y_est1": 0.362,
    "sd_y_est2": 0.3627,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0009,
    "r2_sum3": 0.0009,
    "r2_sum4": 0.0008,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0831,
    "ldsc_observed_scale_h2_se": 0.0056,
    "ldsc_intercept_beta": 1.0088,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.1715,
    "ldsc_mean_chisq": 1.1993,
    "ldsc_ratio": 0.0442
}

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 13555665 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57052 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33328 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051371e+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 7.902505e+07 5.591686e+07 3.02000e+02 3.292856e+07 7.013807e+07 1.148573e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.590000e-05 8.790100e-03 -1.10742e-01 -2.456200e-03 2.500000e-06 2.451800e-03 9.929770e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 6.268600e-03 6.040800e-03 1.23010e-03 1.790500e-03 3.293400e-03 9.001200e-03 3.076650e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.834541e-01 2.933822e-01 0.00000e+00 2.256758e-01 4.778306e-01 7.374575e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.834527e-01 2.933830e-01 0.00000e+00 2.256732e-01 4.778293e-01 7.374572e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910599e-01 2.544607e-01 1.00000e-03 7.506800e-03 6.031430e-02 2.958240e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563206 0.9584892 NA NA NA NA NA 1.965112e-01 2.471408e-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 1.168150e+05 0.000000e+00 1.16815e+05 1.168150e+05 1.168150e+05 1.168150e+05 1.168150e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0007486 0.0026185 0.7749648 0.7749651 0.1115900 0.1894970 116815
1 693731 rs12238997 A G 0.0001298 0.0024762 0.9581970 0.9581965 0.1169120 0.1417730 116815
1 707522 rs371890604 G C -0.0011504 0.0027787 0.6788847 0.6788816 0.0982624 0.1293930 116815
1 717587 rs144155419 G A 0.0012675 0.0066677 0.8492309 0.8492305 0.0157120 0.0045926 116815
1 723329 rs189787166 A T -0.0277295 0.0198545 0.1625261 0.1625232 0.0016831 0.0003994 116815
1 730087 rs148120343 T C 0.0038234 0.0034529 0.2681588 0.2681575 0.0568906 0.0127796 116815
1 731718 rs142557973 T C -0.0003955 0.0023507 0.8663999 0.8663995 0.1227450 0.1543530 116815
1 732032 rs61770163 A C -0.0016923 0.0025048 0.4992856 0.4992844 0.1222720 0.1555510 116815
1 734349 rs141242758 T C -0.0003629 0.0023523 0.8773931 0.8773923 0.1219550 0.1525560 116815
1 740284 rs61770167 C T 0.0065022 0.0105175 0.5364262 0.5364265 0.0060190 0.0023962 116815
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0013630 0.0027424 0.6191830 0.6191821 0.0550677 0.0309934 116815
23 154923374 rs111332691 T A 0.0023198 0.0030005 0.4394455 0.4394428 0.0441082 0.0116556 116815
23 154925045 rs509981 C T -0.0018421 0.0014389 0.2004652 0.2004625 0.2438070 0.3634440 116815
23 154925895 rs538470 C T -0.0016358 0.0014712 0.2661932 0.2661920 0.2402960 0.3634440 116815
23 154927581 rs644138 G A -0.0020486 0.0013532 0.1300610 0.1300587 0.2992830 0.4635760 116815
23 154929412 rs557132 C T -0.0018629 0.0014395 0.1956001 0.1955978 0.2436290 0.3568210 116815
23 154929637 rs35185538 CT C -0.0009210 0.0015016 0.5396411 0.5396392 0.2276100 0.3011920 116815
23 154929952 rs4012982 CAA C -0.0014809 0.0015145 0.3281550 0.3281533 0.2377300 0.3165560 116815
23 154930230 rs781880 A G -0.0017350 0.0014391 0.2279460 0.2279457 0.2441100 0.3618540 116815
23 154930487 rs781879 T A -0.0034846 0.0049971 0.4856037 0.4856019 0.0190868 0.1263580 116815

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11159  ES:SE:LP:AF:SS:ID   0.000748588:0.00261848:0.110718:0.11159:116815:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116912 ES:SE:LP:AF:SS:ID   0.000129792:0.00247615:0.0185452:0.116912:116815:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0982624    ES:SE:LP:AF:SS:ID   -0.00115037:0.00277874:0.168204:0.0982624:116815:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015712 ES:SE:LP:AF:SS:ID   0.00126754:0.00666774:0.0709742:0.015712:116815:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0016831    ES:SE:LP:AF:SS:ID   -0.0277295:0.0198545:0.789077:0.0016831:116815:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568906    ES:SE:LP:AF:SS:ID   0.00382345:0.0034529:0.571608:0.0568906:116815:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122745 ES:SE:LP:AF:SS:ID   -0.00039547:0.00235072:0.0622816:0.122745:116815:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122272 ES:SE:LP:AF:SS:ID   -0.00169229:0.00250481:0.301651:0.122272:116815:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121955 ES:SE:LP:AF:SS:ID   -0.000362906:0.00235232:0.0568058:0.121955:116815:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.006019 ES:SE:LP:AF:SS:ID   0.00650219:0.0105175:0.27049:0.006019:116815:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00177875   ES:SE:LP:AF:SS:ID   -0.0205345:0.0211537:0.479273:0.00177875:116815:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868699 ES:SE:LP:AF:SS:ID   -0.000248236:0.00231875:0.0387:0.868699:116815:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00157472   ES:SE:LP:AF:SS:ID   0.0187426:0.0206501:0.438807:0.00157472:116815:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123866 ES:SE:LP:AF:SS:ID   6.9546e-05:0.00229699:0.0106187:0.123866:116815:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14343  ES:SE:LP:AF:SS:ID   0.000960679:0.00227511:0.172089:0.14343:116815:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123986 ES:SE:LP:AF:SS:ID   7.1409e-05:0.00229365:0.0109228:0.123986:116815:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869912 ES:SE:LP:AF:SS:ID   -4.29345e-05:0.00223422:0.00671018:0.869912:116815:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874588 ES:SE:LP:AF:SS:ID   3.97397e-05:0.00227176:0.00610415:0.874588:116815:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129661 ES:SE:LP:AF:SS:ID   0.000216159:0.00223918:0.0347531:0.129661:116815:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0366263    ES:SE:LP:AF:SS:ID   0.00759187:0.00404919:1.21604:0.0366263:116815:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869527 ES:SE:LP:AF:SS:ID   -4.46709e-05:0.00223205:0.00699034:0.869527:116815:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869646 ES:SE:LP:AF:SS:ID   2.81608e-05:0.00223318:0.00439157:0.869646:116815:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869525 ES:SE:LP:AF:SS:ID   3.47101e-06:0.00223195:0.000539294:0.869525:116815:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00510853   ES:SE:LP:AF:SS:ID   0.0100539:0.0114196:0.42177:0.00510853:116815:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050758    ES:SE:LP:AF:SS:ID   0.0102097:0.0114497:0.42881:0.0050758:116815:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00550482   ES:SE:LP:AF:SS:ID   0.00834589:0.0111565:0.342544:0.00550482:116815:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869642 ES:SE:LP:AF:SS:ID   0.000121397:0.00222822:0.0192919:0.869642:116815:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12695  ES:SE:LP:AF:SS:ID   -0.00029111:0.00227354:0.0466676:0.12695:116815:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869229 ES:SE:LP:AF:SS:ID   0.000225406:0.0022231:0.0365716:0.869229:116815:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868437 ES:SE:LP:AF:SS:ID   -8.37548e-05:0.00222046:0.0132681:0.868437:116815:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869375 ES:SE:LP:AF:SS:ID   5.36475e-05:0.00222488:0.00843593:0.869375:116815:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869382 ES:SE:LP:AF:SS:ID   5.15341e-05:0.00222504:0.00809996:0.869382:116815:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869391 ES:SE:LP:AF:SS:ID   4.55337e-05:0.00222511:0.00714881:0.869391:116815:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869814 ES:SE:LP:AF:SS:ID   9.45851e-05:0.00223076:0.014942:0.869814:116815:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0997706    ES:SE:LP:AF:SS:ID   -0.00100761:0.00258737:0.156795:0.0997706:116815:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00630832   ES:SE:LP:AF:SS:ID   0.00892449:0.0101323:0.422013:0.00630832:116815:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873725 ES:SE:LP:AF:SS:ID   0.000274734:0.00226446:0.0441031:0.873725:116815:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863108 ES:SE:LP:AF:SS:ID   -0.000258386:0.00222084:0.0422118:0.863108:116815:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868529 ES:SE:LP:AF:SS:ID   0.000259897:0.00224203:0.04205:0.868529:116815:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86529  ES:SE:LP:AF:SS:ID   9.14073e-05:0.00224185:0.0143594:0.86529:116815:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994244    ES:SE:LP:AF:SS:ID   0.00106236:0.00268808:0.159462:0.0994244:116815:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870528 ES:SE:LP:AF:SS:ID   0.000115444:0.00226755:0.0180021:0.870528:116815:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870528 ES:SE:LP:AF:SS:ID   0.000115624:0.00226755:0.0180306:0.870528:116815:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870529 ES:SE:LP:AF:SS:ID   0.000122484:0.00226767:0.0191221:0.870529:116815:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870922 ES:SE:LP:AF:SS:ID   -0.000146389:0.00226895:0.0229361:0.870922:116815:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126533 ES:SE:LP:AF:SS:ID   -9.13215e-05:0.00227054:0.0141614:0.126533:116815:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106241 ES:SE:LP:AF:SS:ID   -0.000682357:0.00246967:0.106614:0.106241:116815:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854457 ES:SE:LP:AF:SS:ID   -0.000245452:0.00222074:0.0400094:0.854457:116815:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00158229   ES:SE:LP:AF:SS:ID   -0.0261946:0.0200069:0.720235:0.00158229:116815:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837888 ES:SE:LP:AF:SS:ID   -0.00290895:0.00218428:0.737691:0.837888:116815:rs376645387