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_102/ukb-d-22660_102.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_102/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 14:57:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22660_102/ukb-d-22660_102.vcf.gz ...
Read summary statistics for 10847325 SNPs.
Dropped 8856 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, 1281630 SNPs remain.
After merging with regression SNP LD, 1281630 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0011 (0.0066)
Lambda GC: 1.0098
Mean Chi^2: 1.0067
Intercept: 1.0052 (0.0059)
Ratio: 0.774 (0.8748)
Analysis finished at Mon Nov 25 14:59:18 2019
Total time elapsed: 1.0m:46.92s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9454,
    "inflation_factor": 1,
    "mean_EFFECT": 2.799e-07,
    "n": 67655,
    "n_snps": 10847325,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1130275,
    "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": 215268,
    "n_est": 67750.692,
    "ratio_se_n": 1.0007,
    "mean_diff": 2.226e-06,
    "ratio_diff": 2.3795,
    "sd_y_est1": 0.1781,
    "sd_y_est2": 0.1782,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1281630,
    "ldsc_nsnp_merge_regression_ld": 1281630,
    "ldsc_observed_scale_h2_beta": 0.0011,
    "ldsc_observed_scale_h2_se": 0.0066,
    "ldsc_intercept_beta": 1.0052,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0098,
    "ldsc_mean_chisq": 1.0067,
    "ldsc_ratio": 0.7761
}

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 TRUE
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 10839049 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 50660 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31142 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.074073e+00 6.179699e+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 7.880631e+07 5.603594e+07 3.02000e+02 3.258131e+07 6.976845e+07 1.147399e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.000000e-07 2.852300e-03 -2.98274e-02 -1.173300e-03 -1.390000e-05 1.141600e-03 3.537360e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.335000e-03 1.649100e-03 8.08200e-04 1.085300e-03 1.567600e-03 3.107700e-03 9.327400e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.999736e-01 2.882478e-01 2.00000e-07 2.501463e-01 5.000046e-01 7.492073e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.999712e-01 2.882492e-01 2.00000e-07 2.501419e-01 5.000026e-01 7.492063e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.361595e-01 2.621031e-01 4.95840e-03 2.615480e-02 1.230050e-01 3.779980e-01 9.950420e-01 ▇▂▂▁▁
numeric AF_reference 215268 0.9801547 NA NA NA NA NA 2.362549e-01 2.531486e-01 0.00000e+00 2.555910e-02 1.401760e-01 3.759980e-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 -0.0032927 0.0016928 0.0517595 0.0517549 0.1113330 0.1894970 67655
1 693731 rs12238997 A G -0.0019811 0.0016036 0.2166841 0.2166804 0.1164250 0.1417730 67655
1 707522 rs371890604 G C -0.0033467 0.0018029 0.0634264 0.0634217 0.0978617 0.1293930 67655
1 717587 rs144155419 G A 0.0040735 0.0042933 0.3427181 0.3427156 0.0157910 0.0045926 67655
1 730087 rs148120343 T C -0.0035367 0.0022241 0.1118070 0.1118020 0.0569430 0.0127796 67655
1 731718 rs142557973 T C -0.0019995 0.0015220 0.1889331 0.1889307 0.1223980 0.1543530 67655
1 732032 rs61770163 A C -0.0020536 0.0016232 0.2058169 0.2058123 0.1220450 0.1555510 67655
1 734349 rs141242758 T C -0.0021488 0.0015231 0.1582949 0.1582911 0.1216050 0.1525560 67655
1 740284 rs61770167 C T -0.0026337 0.0070377 0.7082393 0.7082371 0.0056852 0.0023962 67655
1 749963 rs529266287 T TAA 0.0020751 0.0014977 0.1658979 0.1658937 0.8688800 0.7641770 67655
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0012045 0.0018155 0.5070456 0.5070448 0.0547784 0.0309934 67655
23 154923374 rs111332691 T A 0.0022855 0.0019755 0.2473199 0.2473157 0.0442687 0.0116556 67655
23 154925045 rs509981 C T 0.0015393 0.0009431 0.1026370 0.1026328 0.2448950 0.3634440 67655
23 154925895 rs538470 C T 0.0016552 0.0009643 0.0860954 0.0860919 0.2412550 0.3634440 67655
23 154927581 rs644138 G A 0.0010288 0.0008883 0.2467840 0.2467815 0.3000720 0.4635760 67655
23 154929412 rs557132 C T 0.0015539 0.0009433 0.0995222 0.0995183 0.2447530 0.3568210 67655
23 154929637 rs35185538 CT C 0.0015202 0.0009854 0.1229111 0.1229062 0.2291340 0.3011920 67655
23 154929952 rs4012982 CAA C 0.0014277 0.0009930 0.1505210 0.1505177 0.2385660 0.3165560 67655
23 154930230 rs781880 A G 0.0015959 0.0009431 0.0906317 0.0906273 0.2451600 0.3618540 67655
23 154930487 rs781879 T A -0.0020033 0.0032281 0.5348697 0.5348682 0.0193551 0.1263580 67655

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111333 ES:SE:LP:AF:SS:ID   -0.00329272:0.00169277:1.28601:0.111333:67655:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116425 ES:SE:LP:AF:SS:ID   -0.00198113:0.00160363:0.664173:0.116425:67655:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978617    ES:SE:LP:AF:SS:ID   -0.00334666:0.00180294:1.19773:0.0978617:67655:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015791 ES:SE:LP:AF:SS:ID   0.00407354:0.0042933:0.465063:0.015791:67655:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.056943 ES:SE:LP:AF:SS:ID   -0.00353669:0.00222413:0.951531:0.056943:67655:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122398 ES:SE:LP:AF:SS:ID   -0.00199946:0.00152195:0.723692:0.122398:67655:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122045 ES:SE:LP:AF:SS:ID   -0.00205359:0.00162318:0.686519:0.122045:67655:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121605 ES:SE:LP:AF:SS:ID   -0.00214884:0.00152309:0.800533:0.121605:67655:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00568516   ES:SE:LP:AF:SS:ID   -0.00263367:0.00703767:0.14982:0.00568516:67655:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.86888  ES:SE:LP:AF:SS:ID   0.00207512:0.00149772:0.780159:0.86888:67655:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123646 ES:SE:LP:AF:SS:ID   -0.00195214:0.00148549:0.723991:0.123646:67655:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143073 ES:SE:LP:AF:SS:ID   -0.00211868:0.00147024:0.825138:0.143073:67655:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123779 ES:SE:LP:AF:SS:ID   -0.00193308:0.00148331:0.715556:0.123779:67655:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869863 ES:SE:LP:AF:SS:ID   0.00191025:0.00144513:0.729974:0.869863:67655:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874632 ES:SE:LP:AF:SS:ID   0.00186673:0.00146921:0.690606:0.874632:67655:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129534 ES:SE:LP:AF:SS:ID   -0.0019283:0.00144947:0.736582:0.129534:67655:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358436    ES:SE:LP:AF:SS:ID   -0.000331479:0.00264588:0.0456123:0.0358436:67655:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869516 ES:SE:LP:AF:SS:ID   0.00196486:0.00144384:0.76054:0.869516:67655:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869601 ES:SE:LP:AF:SS:ID   0.00194621:0.00144458:0.749812:0.869601:67655:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86951  ES:SE:LP:AF:SS:ID   0.00196573:0.00144377:0.761069:0.86951:67655:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00535705   ES:SE:LP:AF:SS:ID   -0.000963239:0.00719175:0.0489283:0.00535705:67655:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00532268   ES:SE:LP:AF:SS:ID   -0.000813599:0.00720987:0.0408851:0.00532268:67655:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00587606   ES:SE:LP:AF:SS:ID   0.00647552:0.00694621:0.454424:0.00587606:67655:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869521 ES:SE:LP:AF:SS:ID   0.00192552:0.00144103:0.741164:0.869521:67655:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126879 ES:SE:LP:AF:SS:ID   -0.00216913:0.00147085:0.852989:0.126879:67655:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869086 ES:SE:LP:AF:SS:ID   0.0019402:0.00143737:0.751835:0.869086:67655:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86843  ES:SE:LP:AF:SS:ID   0.00188191:0.00143585:0.721294:0.86843:67655:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   0.00190828:0.00143854:0.733608:0.869213:67655:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869219 ES:SE:LP:AF:SS:ID   0.00190733:0.00143864:0.733028:0.869219:67655:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:SS:ID   0.00190626:0.00143865:0.732443:0.869221:67655:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869661 ES:SE:LP:AF:SS:ID   0.00199711:0.00144239:0.779408:0.869661:67655:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991549    ES:SE:LP:AF:SS:ID   -0.00299783:0.00167916:1.12951:0.0991549:67655:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00672466   ES:SE:LP:AF:SS:ID   0.00332452:0.00633283:0.222133:0.00672466:67655:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873693 ES:SE:LP:AF:SS:ID   0.00194284:0.00146366:0.734274:0.873693:67655:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86311  ES:SE:LP:AF:SS:ID   0.00208732:0.00143557:0.83579:0.86311:67655:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868459 ES:SE:LP:AF:SS:ID   0.00203468:0.00145008:0.794319:0.868459:67655:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865449 ES:SE:LP:AF:SS:ID   0.00233923:0.00145017:0.971701:0.865449:67655:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0996966    ES:SE:LP:AF:SS:ID   -0.00195227:0.00173401:0.584653:0.0996966:67655:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   0.00206757:0.00146676:0.799541:0.870704:67655:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   0.00206756:0.00146676:0.799538:0.870704:67655:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870702 ES:SE:LP:AF:SS:ID   0.0020681:0.00146676:0.799834:0.870702:67655:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871042 ES:SE:LP:AF:SS:ID   0.0020673:0.00146746:0.798846:0.871042:67655:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126524 ES:SE:LP:AF:SS:ID   -0.00191668:0.00146894:0.71678:0.126524:67655:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105925 ES:SE:LP:AF:SS:ID   -0.00252225:0.00159863:0.940713:0.105925:67655:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854403 ES:SE:LP:AF:SS:ID   0.0018961:0.00143494:0.729601:0.854403:67655:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839355 ES:SE:LP:AF:SS:ID   -0.00242567:0.00141733:1.06045:0.839355:67655:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763322 ES:SE:LP:AF:SS:ID   -0.000168359:0.00113945:0.0542671:0.763322:67655:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.104959 ES:SE:LP:AF:SS:ID   0.0025001:0.00157164:0.952071:0.104959:67655:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00786948   ES:SE:LP:AF:SS:ID   0.01624:0.00576504:2.31433:0.00786948:67655:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129874 ES:SE:LP:AF:SS:ID   -0.00203795:0.00144871:0.797212:0.129874:67655:rs762168062