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-22660_107/ukb-d-22660_107.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-22660_107/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 14:56:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22660_107/ukb-d-22660_107.vcf.gz ...
Read summary statistics for 11471562 SNPs.
Dropped 9730 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, 1282600 SNPs remain.
After merging with regression SNP LD, 1282600 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0046 (0.0063)
Lambda GC: 1.0077
Mean Chi^2: 1.0068
Intercept: 1.0007 (0.006)
Ratio: 0.0964 (0.8782)
Analysis finished at Mon Nov 25 14:58:15 2019
Total time elapsed: 1.0m:56.11s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9475,
    "inflation_factor": 1.011,
    "mean_EFFECT": 2.0318e-06,
    "n": 67655,
    "n_snps": 11471562,
    "n_clumped_hits": 1,
    "n_p_sig": 8,
    "n_mono": 0,
    "n_ns": 1160603,
    "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": 242191,
    "n_est": 67768.5073,
    "ratio_se_n": 1.0008,
    "mean_diff": 8.6568e-06,
    "ratio_diff": 9.4645,
    "sd_y_est1": 0.2077,
    "sd_y_est2": 0.2079,
    "r2_sum1": 0,
    "r2_sum2": 0.0005,
    "r2_sum3": 0.0005,
    "r2_sum4": 0.0005,
    "ldsc_nsnp_merge_refpanel_ld": 1282600,
    "ldsc_nsnp_merge_regression_ld": 1282600,
    "ldsc_observed_scale_h2_beta": 0.0046,
    "ldsc_observed_scale_h2_se": 0.0063,
    "ldsc_intercept_beta": 1.0007,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0077,
    "ldsc_mean_chisq": 1.0068,
    "ldsc_ratio": 0.1029
}

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 11462437 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 52206 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31703 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.073837e+00 6.183577e+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 7.884435e+07 5.599918e+07 3.02000e+02 3.263645e+07 6.984696e+07 1.147284e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.000000e-06 3.886500e-03 -3.73397e-02 -1.461200e-03 -1.710000e-05 1.412200e-03 4.638690e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.072400e-03 2.376100e-03 9.42200e-04 1.282700e-03 1.946800e-03 4.172200e-03 1.394360e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.984890e-01 2.892638e-01 0.00000e+00 2.473143e-01 4.976500e-01 7.492936e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.984867e-01 2.892652e-01 0.00000e+00 2.473103e-01 4.976473e-01 7.492933e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.240370e-01 2.607803e-01 3.46260e-03 1.958890e-02 1.057780e-01 3.578840e-01 9.965370e-01 ▇▂▁▁▁
numeric AF_reference 242191 0.9788877 NA NA NA NA NA 2.246924e-01 2.520308e-01 0.00000e+00 1.697280e-02 1.242010e-01 3.576280e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.765500e+04 0.000000e+00 6.76550e+04 6.765500e+04 6.765500e+04 6.765500e+04 6.765500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0003074 0.0019736 0.8762320 0.8762316 0.1113330 0.1894970 67655
1 693731 rs12238997 A G -0.0000430 0.0018696 0.9816410 0.9816410 0.1164250 0.1417730 67655
1 707522 rs371890604 G C 0.0008465 0.0021020 0.6871697 0.6871681 0.0978617 0.1293930 67655
1 717587 rs144155419 G A -0.0070455 0.0050054 0.1592608 0.1592565 0.0157910 0.0045926 67655
1 730087 rs148120343 T C 0.0043564 0.0025930 0.0929544 0.0929511 0.0569430 0.0127796 67655
1 731718 rs142557973 T C 0.0001371 0.0017744 0.9384130 0.9384131 0.1223980 0.1543530 67655
1 732032 rs61770163 A C -0.0000722 0.0018924 0.9695589 0.9695584 0.1220450 0.1555510 67655
1 734349 rs141242758 T C 0.0002086 0.0017758 0.9064989 0.9064994 0.1216050 0.1525560 67655
1 740284 rs61770167 C T 0.0063052 0.0082050 0.4422196 0.4422175 0.0056852 0.0023962 67655
1 749963 rs529266287 T TAA 0.0002914 0.0017462 0.8674880 0.8674874 0.8688800 0.7641770 67655
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0028219 0.0021166 0.1824559 0.1824503 0.0547784 0.0309934 67655
23 154923374 rs111332691 T A -0.0015834 0.0023032 0.4917926 0.4917916 0.0442687 0.0116556 67655
23 154925045 rs509981 C T -0.0009597 0.0010995 0.3827243 0.3827200 0.2448950 0.3634440 67655
23 154925895 rs538470 C T -0.0006447 0.0011243 0.5663879 0.5663851 0.2412550 0.3634440 67655
23 154927581 rs644138 G A -0.0015556 0.0010356 0.1330721 0.1330663 0.3000720 0.4635760 67655
23 154929412 rs557132 C T -0.0009426 0.0010998 0.3914119 0.3914109 0.2447530 0.3568210 67655
23 154929637 rs35185538 CT C -0.0017688 0.0011489 0.1236571 0.1236525 0.2291340 0.3011920 67655
23 154929952 rs4012982 CAA C -0.0004268 0.0011578 0.7124231 0.7124225 0.2385660 0.3165560 67655
23 154930230 rs781880 A G -0.0009549 0.0010996 0.3851643 0.3851621 0.2451600 0.3618540 67655
23 154930487 rs781879 T A -0.0039085 0.0037635 0.2990247 0.2990206 0.0193551 0.1263580 67655

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111333 ES:SE:LP:AF:SS:ID   0.000307386:0.00197361:0.0573809:0.111333:67655:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116425 ES:SE:LP:AF:SS:ID   -4.30236e-05:0.00186965:0.00804731:0.116425:67655:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978617    ES:SE:LP:AF:SS:ID   0.000846498:0.00210205:0.162936:0.0978617:67655:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015791 ES:SE:LP:AF:SS:ID   -0.00704547:0.00500539:0.797891:0.015791:67655:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.056943 ES:SE:LP:AF:SS:ID   0.00435639:0.00259304:1.03173:0.056943:67655:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122398 ES:SE:LP:AF:SS:ID   0.000137099:0.00177441:0.027606:0.122398:67655:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122045 ES:SE:LP:AF:SS:ID   -7.22195e-05:0.00189244:0.0134258:0.122045:67655:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121605 ES:SE:LP:AF:SS:ID   0.000208571:0.00177575:0.0426327:0.121605:67655:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00568516   ES:SE:LP:AF:SS:ID   0.00630515:0.00820498:0.354362:0.00568516:67655:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.86888  ES:SE:LP:AF:SS:ID   0.00029135:0.00174617:0.0617365:0.86888:67655:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123646 ES:SE:LP:AF:SS:ID   -1.74911e-05:0.00173191:0.00351372:0.123646:67655:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143073 ES:SE:LP:AF:SS:ID   -0.00117724:0.00171413:0.307841:0.143073:67655:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123779 ES:SE:LP:AF:SS:ID   -5.02711e-05:0.00172937:0.0101899:0.123779:67655:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869863 ES:SE:LP:AF:SS:ID   8.2466e-05:0.00168485:0.0172933:0.869863:67655:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874632 ES:SE:LP:AF:SS:ID   -9.75789e-05:0.00171293:0.0201913:0.874632:67655:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129534 ES:SE:LP:AF:SS:ID   -0.000147926:0.00168991:0.0314017:0.129534:67655:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358436    ES:SE:LP:AF:SS:ID   -0.00186828:0.00308474:0.263804:0.0358436:67655:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869516 ES:SE:LP:AF:SS:ID   9.12196e-05:0.00168336:0.0191856:0.869516:67655:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869601 ES:SE:LP:AF:SS:ID   6.77238e-05:0.00168422:0.0141583:0.869601:67655:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86951  ES:SE:LP:AF:SS:ID   9.66827e-05:0.00168328:0.020362:0.86951:67655:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00535705   ES:SE:LP:AF:SS:ID   -0.0114081:0.00838453:0.760348:0.00535705:67655:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00532268   ES:SE:LP:AF:SS:ID   -0.0111397:0.00840566:0.732617:0.00532268:67655:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00587606   ES:SE:LP:AF:SS:ID   0.0125533:0.00809829:0.916795:0.00587606:67655:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869521 ES:SE:LP:AF:SS:ID   2.28432e-05:0.00168007:0.00473697:0.869521:67655:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126879 ES:SE:LP:AF:SS:ID   -0.000232277:0.00171485:0.0495105:0.126879:67655:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869086 ES:SE:LP:AF:SS:ID   4.54736e-05:0.00167581:0.00950486:0.869086:67655:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86843  ES:SE:LP:AF:SS:ID   0.000128793:0.00167404:0.0274847:0.86843:67655:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   6.11251e-05:0.00167718:0.0128134:0.869213:67655:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869219 ES:SE:LP:AF:SS:ID   6.27842e-05:0.00167729:0.0131651:0.869219:67655:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:SS:ID   6.26387e-05:0.0016773:0.0131343:0.869221:67655:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869661 ES:SE:LP:AF:SS:ID   6.95175e-05:0.00168167:0.0145618:0.869661:67655:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991549    ES:SE:LP:AF:SS:ID   0.00151869:0.00195771:0.358625:0.0991549:67655:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00672466   ES:SE:LP:AF:SS:ID   0.00757935:0.00738322:0.516229:0.00672466:67655:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873693 ES:SE:LP:AF:SS:ID   0.000164591:0.00170646:0.0347221:0.873693:67655:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86311  ES:SE:LP:AF:SS:ID   3.68591e-05:0.00167372:0.00769838:0.86311:67655:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868459 ES:SE:LP:AF:SS:ID   0.000254318:0.00169063:0.0553066:0.868459:67655:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865449 ES:SE:LP:AF:SS:ID   0.000187466:0.00169074:0.0401419:0.865449:67655:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0996966    ES:SE:LP:AF:SS:ID   -0.000348794:0.00202165:0.0639781:0.0996966:67655:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   -7.78899e-05:0.00171007:0.0160712:0.870704:67655:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   -7.79643e-05:0.00171007:0.016087:0.870704:67655:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870702 ES:SE:LP:AF:SS:ID   -7.73175e-05:0.00171008:0.0159509:0.870702:67655:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871042 ES:SE:LP:AF:SS:ID   -0.000134999:0.00171089:0.0282104:0.871042:67655:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126524 ES:SE:LP:AF:SS:ID   -0.000323291:0.00171262:0.0704411:0.126524:67655:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105925 ES:SE:LP:AF:SS:ID   0.000968722:0.00186383:0.219509:0.105925:67655:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854403 ES:SE:LP:AF:SS:ID   0.000344029:0.00167298:0.0772361:0.854403:67655:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839355 ES:SE:LP:AF:SS:ID   0.00137186:0.00165245:0.391011:0.839355:67655:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763322 ES:SE:LP:AF:SS:ID   0.000356718:0.00132845:0.103309:0.763322:67655:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.104959 ES:SE:LP:AF:SS:ID   -0.000819206:0.00183236:0.183878:0.104959:67655:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00786948   ES:SE:LP:AF:SS:ID   -0.00523778:0.00672165:0.360672:0.00786948:67655:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129874 ES:SE:LP:AF:SS:ID   -0.000331215:0.00168903:0.0733829:0.129874:67655:rs762168062