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-41219_7/ukb-d-41219_7.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-41219_7/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 16:49:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-41219_7/ukb-d-41219_7.vcf.gz ...
Read summary statistics for 10619707 SNPs.
Dropped 8542 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, 1280953 SNPs remain.
After merging with regression SNP LD, 1280953 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.278 (0.1235)
Lambda GC: 0.9891
Mean Chi^2: 0.9942
Intercept: 1.0126 (0.0061)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 16:51:38 2019
Total time elapsed: 1.0m:43.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9444,
    "inflation_factor": 0.9929,
    "mean_EFFECT": -0.0001,
    "n": 3345,
    "n_snps": 10619707,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1118166,
    "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": 210025,
    "n_est": 3340.6704,
    "ratio_se_n": 0.9994,
    "mean_diff": -0.0001,
    "ratio_diff": 25.0877,
    "sd_y_est1": 0.4999,
    "sd_y_est2": 0.4996,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1280953,
    "ldsc_nsnp_merge_regression_ld": 1280953,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0126,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 0.9891,
    "ldsc_mean_chisq": 0.9942,
    "ldsc_ratio": -2.1724
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 10611740 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 50039 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30932 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.075262e+00 6.178795e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.880190e+07 5.604410e+07 302.0000000 3.256658e+07 6.977522e+07 1.147284e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.820000e-05 3.420310e-02 -0.3304530 -1.441110e-02 -6.340000e-05 1.414060e-02 4.022490e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.826090e-02 1.921380e-02 0.0117743 1.363580e-02 1.937740e-02 3.734570e-02 1.095460e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.009596e-01 2.885417e-01 0.0000005 2.513553e-01 5.015324e-01 7.508393e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.009117e-01 2.885705e-01 0.0000004 2.512721e-01 5.014847e-01 7.508203e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.408860e-01 2.624541e-01 0.0056772 2.906830e-02 1.296760e-01 3.857090e-01 9.943220e-01 ▇▂▂▁▁
numeric AF_reference 210025 0.9802231 NA NA NA NA NA 2.408439e-01 2.534348e-01 0.0000000 2.975240e-02 1.465650e-01 3.829870e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.345000e+03 0.000000e+00 3345.0000000 3.345000e+03 3.345000e+03 3.345000e+03 3.345000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0000094 0.0211817 0.9996450 0.9996445 0.1124020 0.1894970 3345
1 693731 rs12238997 A G -0.0044852 0.0200971 0.8234111 0.8233978 0.1170260 0.1417730 3345
1 707522 rs371890604 G C -0.0015691 0.0228134 0.9451691 0.9451649 0.0975873 0.1293930 3345
1 717587 rs144155419 G A 0.0190694 0.0523728 0.7158005 0.7157767 0.0168393 0.0045926 3345
1 730087 rs148120343 T C -0.0047368 0.0277014 0.8642391 0.8642283 0.0585521 0.0127796 3345
1 731718 rs142557973 T C -0.0044313 0.0190733 0.8162949 0.8162809 0.1229470 0.1543530 3345
1 732032 rs61770163 A C 0.0011403 0.0203734 0.9553689 0.9553649 0.1228790 0.1555510 3345
1 734349 rs141242758 T C -0.0056959 0.0190584 0.7650626 0.7650434 0.1220140 0.1525560 3345
1 740284 rs61770167 C T -0.1114740 0.0781906 0.1540561 0.1539636 0.0068302 0.0023962 3345
1 749963 rs529266287 T TAA -0.0096180 0.0185818 0.6047683 0.6047340 0.8685380 0.7641770 3345
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0196558 0.0266789 0.4613229 0.4612716 0.0569700 0.0309934 3345
23 154923374 rs111332691 T A -0.0067490 0.0289459 0.8156541 0.8156392 0.0457399 0.0116556 3345
23 154925045 rs509981 C T -0.0058665 0.0137185 0.6689444 0.6689175 0.2521760 0.3634440 3345
23 154925895 rs538470 C T -0.0081712 0.0140471 0.5608065 0.5607682 0.2482110 0.3634440 3345
23 154927581 rs644138 G A -0.0013481 0.0130342 0.9176310 0.9176246 0.3095370 0.4635760 3345
23 154929412 rs557132 C T -0.0062252 0.0137196 0.6500444 0.6500145 0.2520330 0.3568210 3345
23 154929637 rs35185538 CT C -0.0135812 0.0144510 0.3473834 0.3473148 0.2348110 0.3011920 3345
23 154929952 rs4012982 CAA C -0.0064397 0.0144931 0.6568346 0.6568055 0.2454930 0.3165560 3345
23 154930230 rs781880 A G -0.0066589 0.0137274 0.6276492 0.6276174 0.2519210 0.3618540 3345
23 154930487 rs781879 T A 0.0161474 0.0454251 0.7222574 0.7222352 0.0218471 0.1263580 3345

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112402 ES:SE:LP:AF:SS:ID   -9.43789e-06:0.0211817:0.000154202:0.112402:3345:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117026 ES:SE:LP:AF:SS:ID   -0.00448521:0.0200971:0.0843833:0.117026:3345:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0975873    ES:SE:LP:AF:SS:ID   -0.0015691:0.0228134:0.0244905:0.0975873:3345:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0168393    ES:SE:LP:AF:SS:ID   0.0190694:0.0523728:0.145208:0.0168393:3345:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0585521    ES:SE:LP:AF:SS:ID   -0.00473678:0.0277014:0.0633661:0.0585521:3345:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122947 ES:SE:LP:AF:SS:ID   -0.00443132:0.0190733:0.0881529:0.122947:3345:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122879 ES:SE:LP:AF:SS:ID   0.00114032:0.0203734:0.0198289:0.122879:3345:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122014 ES:SE:LP:AF:SS:ID   -0.00569588:0.0190584:0.116303:0.122014:3345:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00683021   ES:SE:LP:AF:SS:ID   -0.111474:0.0781906:0.812321:0.00683021:3345:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.868538 ES:SE:LP:AF:SS:ID   -0.00961803:0.0185818:0.218411:0.868538:3345:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.124236 ES:SE:LP:AF:SS:ID   0.0109155:0.0185048:0.25546:0.124236:3345:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.141999 ES:SE:LP:AF:SS:ID   0.0153375:0.0185109:0.389967:0.141999:3345:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124292 ES:SE:LP:AF:SS:ID   0.0107719:0.0184882:0.251675:0.124292:3345:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869637 ES:SE:LP:AF:SS:ID   -0.00877786:0.018013:0.203376:0.869637:3345:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873655 ES:SE:LP:AF:SS:ID   -0.00693551:0.0182831:0.152144:0.873655:3345:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129651 ES:SE:LP:AF:SS:ID   0.0110828:0.0180886:0.267509:0.129651:3345:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0415546    ES:SE:LP:AF:SS:ID   -0.0405085:0.0310417:0.716712:0.0415546:3345:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869262 ES:SE:LP:AF:SS:ID   -0.00896972:0.0179898:0.208945:0.869262:3345:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869262 ES:SE:LP:AF:SS:ID   -0.00895992:0.0179888:0.208689:0.869262:3345:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869256 ES:SE:LP:AF:SS:ID   -0.00897496:0.017988:0.209115:0.869256:3345:rs3131967
1   755435  rs184270342 T   G   .   PASS    AF=0.00620651   ES:SE:LP:AF:SS:ID   0.0585031:0.0846623:0.310156:0.00620651:3345:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868938 ES:SE:LP:AF:SS:ID   -0.0072767:0.0179461:0.164212:0.868938:3345:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126814 ES:SE:LP:AF:SS:ID   0.00946167:0.0183794:0.217005:0.126814:3345:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868759 ES:SE:LP:AF:SS:ID   -0.00685118:0.0179129:0.153579:0.868759:3345:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867793 ES:SE:LP:AF:SS:ID   -0.00745817:0.0178913:0.169535:0.867793:3345:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868643 ES:SE:LP:AF:SS:ID   -0.00756948:0.0179172:0.172172:0.868643:3345:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868646 ES:SE:LP:AF:SS:ID   -0.00758383:0.0179184:0.172537:0.868646:3345:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868658 ES:SE:LP:AF:SS:ID   -0.00755202:0.0179196:0.171686:0.868658:3345:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869132 ES:SE:LP:AF:SS:ID   -0.00818497:0.0179641:0.187965:0.869132:3345:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0979091    ES:SE:LP:AF:SS:ID   0.00762144:0.0213224:0.142194:0.0979091:3345:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00693338   ES:SE:LP:AF:SS:ID   0.081465:0.0785782:0.522976:0.00693338:3345:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873294 ES:SE:LP:AF:SS:ID   -0.00804113:0.0182696:0.180544:0.873294:3345:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862376 ES:SE:LP:AF:SS:ID   -0.00526433:0.0179179:0.114115:0.862376:3345:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868107 ES:SE:LP:AF:SS:ID   -0.00759693:0.0180864:0.171026:0.868107:3345:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865048 ES:SE:LP:AF:SS:ID   -0.008063:0.0181179:0.182879:0.865048:3345:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100185 ES:SE:LP:AF:SS:ID   0.00818196:0.0215864:0.152004:0.100185:3345:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870606 ES:SE:LP:AF:SS:ID   -0.00931051:0.0183448:0.213378:0.870606:3345:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870606 ES:SE:LP:AF:SS:ID   -0.00931367:0.0183448:0.213464:0.870606:3345:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870601 ES:SE:LP:AF:SS:ID   -0.00929991:0.0183448:0.21309:0.870601:3345:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870733 ES:SE:LP:AF:SS:ID   -0.00885863:0.0183433:0.201229:0.870733:3345:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126593 ES:SE:LP:AF:SS:ID   0.0100971:0.0183569:0.234833:0.126593:3345:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10536  ES:SE:LP:AF:SS:ID   0.00423568:0.0200726:0.0794144:0.10536:3345:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853371 ES:SE:LP:AF:SS:ID   -0.00948717:0.017799:0.226172:0.853371:3345:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.833954 ES:SE:LP:AF:SS:ID   -0.0163761:0.0175741:0.454082:0.833954:3345:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.760547 ES:SE:LP:AF:SS:ID   -0.0124511:0.0141848:0.420068:0.760547:3345:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.107623 ES:SE:LP:AF:SS:ID   0.0150179:0.0194904:0.35552:0.107623:3345:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00814913   ES:SE:LP:AF:SS:ID   0.0102993:0.0712347:0.0530327:0.00814913:3345:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.130185 ES:SE:LP:AF:SS:ID   0.0103644:0.0180718:0.246924:0.130185:3345:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.1298   ES:SE:LP:AF:SS:ID   0.00933558:0.0180582:0.218094:0.1298:3345:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.10685  ES:SE:LP:AF:SS:ID   0.0132972:0.0196516:0.302181:0.10685:3345:rs7518545