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-4979/ukb-d-4979.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-4979/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 17:17:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4979/ukb-d-4979.vcf.gz ...
Read summary statistics for 13567321 SNPs.
Dropped 12685 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: 0.0416 (0.0049)
Lambda GC: 1.1031
Mean Chi^2: 1.1033
Intercept: 1.009 (0.0065)
Ratio: 0.0874 (0.0626)
Analysis finished at Mon Nov 25 17:20:10 2019
Total time elapsed: 2.0m:15.18s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.073,
    "mean_EFFECT": -0,
    "n": 113356,
    "n_snps": 13567321,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1251197,
    "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": 563058,
    "n_est": 113800.4773,
    "ratio_se_n": 1.002,
    "mean_diff": -0,
    "ratio_diff": 53.6227,
    "sd_y_est1": 0.5006,
    "sd_y_est2": 0.5016,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0416,
    "ldsc_observed_scale_h2_se": 0.0049,
    "ldsc_intercept_beta": 1.009,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.1031,
    "ldsc_mean_chisq": 1.1033,
    "ldsc_ratio": 0.0871
}

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 13555300 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 57051 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33328 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.051388e+00 6.184971e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.902457e+07 5.591678e+07 3.02000e+02 3.292789e+07 7.013742e+07 1.148559e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA -3.330000e-05 1.229920e-02 -1.44083e-01 -3.391200e-03 -2.210000e-05 3.333800e-03 1.535130e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 8.799800e-03 8.479900e-03 1.72820e-03 2.513700e-03 4.623500e-03 1.263570e-02 4.343030e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.894756e-01 2.911709e-01 1.00000e-07 2.350190e-01 4.847625e-01 7.418686e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.894742e-01 2.911718e-01 1.00000e-07 2.350168e-01 4.847618e-01 7.418674e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 1.910649e-01 2.544623e-01 1.00000e-03 7.507000e-03 6.031960e-02 2.958290e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563058 0.958499 NA NA NA NA NA 1.965142e-01 2.471414e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 1.133560e+05 0.000000e+00 1.13356e+05 1.133560e+05 1.133560e+05 1.133560e+05 1.133560e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0037370 0.0036785 0.3096877 0.3096846 0.1115570 0.1894970 113356
1 693731 rs12238997 A G 0.0054204 0.0034793 0.1192609 0.1192580 0.1168090 0.1417730 113356
1 707522 rs371890604 G C 0.0042662 0.0039024 0.2743039 0.2743011 0.0981383 0.1293930 113356
1 717587 rs144155419 G A 0.0065994 0.0093747 0.4814620 0.4814601 0.0156670 0.0045926 113356
1 723329 rs189787166 A T -0.0118718 0.0278440 0.6698399 0.6698395 0.0016865 0.0003994 113356
1 730087 rs148120343 T C 0.0016814 0.0048474 0.7286903 0.7286902 0.0569312 0.0127796 113356
1 731718 rs142557973 T C 0.0048709 0.0033030 0.1403011 0.1402972 0.1226070 0.1543530 113356
1 732032 rs61770163 A C 0.0048065 0.0035191 0.1719939 0.1719920 0.1221310 0.1555510 113356
1 734349 rs141242758 T C 0.0048678 0.0033054 0.1408410 0.1408379 0.1218150 0.1525560 113356
1 740284 rs61770167 C T 0.0002134 0.0148117 0.9885070 0.9885074 0.0059857 0.0023962 113356
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0009645 0.0038537 0.8023700 0.8023695 0.0550274 0.0309934 113356
23 154923374 rs111332691 T A 0.0022028 0.0042082 0.6006549 0.6006549 0.0442279 0.0116556 113356
23 154925045 rs509981 C T 0.0004529 0.0020205 0.8226500 0.8226491 0.2440180 0.3634440 113356
23 154925895 rs538470 C T 0.0003857 0.0020660 0.8518970 0.8518968 0.2404880 0.3634440 113356
23 154927581 rs644138 G A 0.0002675 0.0019005 0.8880579 0.8880576 0.2994530 0.4635760 113356
23 154929412 rs557132 C T 0.0004077 0.0020213 0.8401641 0.8401633 0.2438350 0.3568210 113356
23 154929637 rs35185538 CT C -0.0004567 0.0021085 0.8285141 0.8285141 0.2278850 0.3011920 113356
23 154929952 rs4012982 CAA C -0.0003204 0.0021262 0.8802049 0.8802053 0.2380420 0.3165560 113356
23 154930230 rs781880 A G 0.0002074 0.0020208 0.9182539 0.9182541 0.2443310 0.3618540 113356
23 154930487 rs781879 T A 0.0017148 0.0070150 0.8068849 0.8068844 0.0191514 0.1263580 113356

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111557 ES:SE:LP:AF:SS:ID   0.00373695:0.00367852:0.509076:0.111557:113356:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116809 ES:SE:LP:AF:SS:ID   0.00542037:0.00347929:0.923502:0.116809:113356:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981383    ES:SE:LP:AF:SS:ID   0.00426618:0.00390243:0.561768:0.0981383:113356:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015667 ES:SE:LP:AF:SS:ID   0.00659937:0.00937469:0.317438:0.015667:113356:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00168651   ES:SE:LP:AF:SS:ID   -0.0118718:0.027844:0.174029:0.00168651:113356:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0569312    ES:SE:LP:AF:SS:ID   0.00168141:0.0048474:0.137457:0.0569312:113356:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122607 ES:SE:LP:AF:SS:ID   0.00487093:0.00330303:0.852939:0.122607:113356:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122131 ES:SE:LP:AF:SS:ID   0.00480651:0.00351911:0.764487:0.122131:113356:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121815 ES:SE:LP:AF:SS:ID   0.00486779:0.0033054:0.851271:0.121815:113356:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00598574   ES:SE:LP:AF:SS:ID   0.000213353:0.0148117:0.00502025:0.00598574:113356:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00178751   ES:SE:LP:AF:SS:ID   0.0357798:0.0296078:0.644217:0.00178751:113356:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868772 ES:SE:LP:AF:SS:ID   -0.00613261:0.00325686:1.22398:0.868772:113356:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00158738   ES:SE:LP:AF:SS:ID   0.00688078:0.028816:0.0908324:0.00158738:113356:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123785 ES:SE:LP:AF:SS:ID   0.00617358:0.00322643:1.25419:0.123785:113356:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143326 ES:SE:LP:AF:SS:ID   0.00587083:0.00319574:1.17914:0.143326:113356:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123903 ES:SE:LP:AF:SS:ID   0.00613612:0.0032218:1.24535:0.123903:113356:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869987 ES:SE:LP:AF:SS:ID   -0.00638385:0.00313808:1.37755:0.869987:113356:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874681 ES:SE:LP:AF:SS:ID   -0.00599728:0.00319109:1.22044:0.874681:113356:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129585 ES:SE:LP:AF:SS:ID   0.00600744:0.00314514:1.25083:0.129585:113356:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0366809    ES:SE:LP:AF:SS:ID   0.00508908:0.00568084:0.431395:0.0366809:113356:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869597 ES:SE:LP:AF:SS:ID   -0.00647596:0.00313498:1.41052:0.869597:113356:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869719 ES:SE:LP:AF:SS:ID   -0.00647005:0.0031366:1.4074:0.869719:113356:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869595 ES:SE:LP:AF:SS:ID   -0.00649299:0.00313484:1.41636:0.869595:113356:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00512344   ES:SE:LP:AF:SS:ID   0.0297809:0.0160086:1.20173:0.00512344:113356:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509021   ES:SE:LP:AF:SS:ID   0.0300929:0.0160509:1.21598:0.00509021:113356:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00546505   ES:SE:LP:AF:SS:ID   -0.012275:0.0157321:0.361267:0.00546505:113356:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869706 ES:SE:LP:AF:SS:ID   -0.00639168:0.00312956:1.38596:0.869706:113356:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126875 ES:SE:LP:AF:SS:ID   0.00635399:0.00319351:1.33132:0.126875:113356:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869283 ES:SE:LP:AF:SS:ID   -0.00657027:0.00312225:1.4516:0.869283:113356:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868493 ES:SE:LP:AF:SS:ID   -0.00677802:0.00311851:1.52657:0.868493:113356:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869434 ES:SE:LP:AF:SS:ID   -0.00657278:0.00312482:1.45061:0.869434:113356:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869441 ES:SE:LP:AF:SS:ID   -0.00657256:0.00312504:1.45037:0.869441:113356:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86945  ES:SE:LP:AF:SS:ID   -0.00659891:0.00312514:1.45933:0.86945:113356:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869882 ES:SE:LP:AF:SS:ID   -0.00656939:0.00313321:1.44342:0.869882:113356:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996929    ES:SE:LP:AF:SS:ID   0.00513782:0.00363391:0.802973:0.0996929:113356:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00627435   ES:SE:LP:AF:SS:ID   -0.00814089:0.0142765:0.245252:0.00627435:113356:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873803 ES:SE:LP:AF:SS:ID   -0.00661557:0.0031807:1.42555:0.873803:113356:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863151 ES:SE:LP:AF:SS:ID   -0.00649022:0.00311901:1.42656:0.863151:113356:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868603 ES:SE:LP:AF:SS:ID   -0.00659602:0.00314908:1.44117:0.868603:113356:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865373 ES:SE:LP:AF:SS:ID   -0.00565969:0.0031488:1.14102:0.865373:113356:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993746    ES:SE:LP:AF:SS:ID   0.00953537:0.0037754:1.93744:0.0993746:113356:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87063  ES:SE:LP:AF:SS:ID   -0.00610535:0.00318514:1.25756:0.87063:113356:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87063  ES:SE:LP:AF:SS:ID   -0.00610496:0.00318514:1.25744:0.87063:113356:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870632 ES:SE:LP:AF:SS:ID   -0.00612215:0.00318531:1.26273:0.870632:113356:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871005 ES:SE:LP:AF:SS:ID   -0.00637134:0.00318699:1.34111:0.871005:113356:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126447 ES:SE:LP:AF:SS:ID   0.00620729:0.00318943:1.28708:0.126447:113356:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106176 ES:SE:LP:AF:SS:ID   0.005894:0.00346816:1.04946:0.106176:113356:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854535 ES:SE:LP:AF:SS:ID   -0.00523607:0.00311908:1.03054:0.854535:113356:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00158503   ES:SE:LP:AF:SS:ID   -0.00994325:0.0280624:0.140805:0.00158503:113356:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837873 ES:SE:LP:AF:SS:ID   -0.000824181:0.00306618:0.103426:0.837873:113356:rs376645387