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-22610_1/ukb-d-22610_1.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-22610_1/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 16:37:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22610_1/ukb-d-22610_1.vcf.gz ...
Read summary statistics for 13566574 SNPs.
Dropped 12683 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0243 (0.005)
Lambda GC: 1.0543
Mean Chi^2: 1.0563
Intercept: 1.0149 (0.0059)
Ratio: 0.2639 (0.1043)
Analysis finished at Mon Nov 25 16:39:34 2019
Total time elapsed: 2.0m:4.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0392,
    "mean_EFFECT": 0,
    "n": 88638,
    "n_snps": 13566574,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1251219,
    "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": 562992,
    "n_est": 88961.7094,
    "ratio_se_n": 1.0018,
    "mean_diff": 0,
    "ratio_diff": 36.8015,
    "sd_y_est1": 0.4208,
    "sd_y_est2": 0.4216,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0243,
    "ldsc_observed_scale_h2_se": 0.005,
    "ldsc_intercept_beta": 1.0149,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0543,
    "ldsc_mean_chisq": 1.0563,
    "ldsc_ratio": 0.2647
}

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 13554555 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57045 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33332 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051324e+00 6.184975e+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 7.902468e+07 5.591663e+07 3.02000e+02 3.292804e+07 7.013432e+07 1.148619e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.970000e-05 1.167740e-02 -1.39762e-01 -3.147900e-03 -1.480000e-05 3.124500e-03 1.534710e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.365400e-03 8.061800e-03 1.64790e-03 2.390200e-03 4.396300e-03 1.201180e-02 4.046530e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.938783e-01 2.905513e-01 1.00000e-07 2.404689e-01 4.917111e-01 7.455744e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.938765e-01 2.905523e-01 1.00000e-07 2.404657e-01 4.917095e-01 7.455737e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910729e-01 2.544764e-01 1.00000e-03 7.499400e-03 6.030680e-02 2.957860e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 562992 0.9585015 NA NA NA NA NA 1.965265e-01 2.471471e-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 8.863800e+04 0.000000e+00 8.86380e+04 8.863800e+04 8.863800e+04 8.863800e+04 8.863800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0014002 0.0034917 0.6884081 0.6884074 0.1113450 0.1894970 88638
1 693731 rs12238997 A G 0.0034359 0.0033083 0.2989978 0.2989964 0.1163190 0.1417730 88638
1 707522 rs371890604 G C 0.0049321 0.0037181 0.1846750 0.1846723 0.0977362 0.1293930 88638
1 717587 rs144155419 G A -0.0087685 0.0088478 0.3216674 0.3216641 0.0158097 0.0045926 88638
1 723329 rs189787166 A T 0.0018062 0.0258065 0.9442020 0.9442015 0.0017813 0.0003994 88638
1 730087 rs148120343 T C 0.0046598 0.0045896 0.3099752 0.3099723 0.0567943 0.0127796 88638
1 731718 rs142557973 T C 0.0018858 0.0031392 0.5480271 0.5480265 0.1221780 0.1543530 88638
1 732032 rs61770163 A C 0.0033816 0.0033474 0.3124000 0.3123972 0.1218840 0.1555510 88638
1 734349 rs141242758 T C 0.0020627 0.0031415 0.5114439 0.5114440 0.1214140 0.1525560 88638
1 740284 rs61770167 C T 0.0149504 0.0143967 0.2990577 0.2990559 0.0057548 0.0023962 88638
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0018021 0.0036723 0.6236300 0.6236285 0.0550976 0.0309934 88638
23 154923374 rs111332691 T A -0.0010532 0.0039841 0.7915147 0.7915131 0.0449751 0.0116556 88638
23 154925045 rs509981 C T -0.0019887 0.0019231 0.3010849 0.3010818 0.2446440 0.3634440 88638
23 154925895 rs538470 C T -0.0020065 0.0019659 0.3074220 0.3074194 0.2411540 0.3634440 88638
23 154927581 rs644138 G A -0.0013309 0.0018090 0.4618968 0.4618953 0.3001550 0.4635760 88638
23 154929412 rs557132 C T -0.0020093 0.0019237 0.2962511 0.2962481 0.2444980 0.3568210 88638
23 154929637 rs35185538 CT C -0.0022357 0.0020086 0.2656740 0.2656717 0.2289290 0.3011920 88638
23 154929952 rs4012982 CAA C -0.0023405 0.0020248 0.2477251 0.2477213 0.2384260 0.3165560 88638
23 154930230 rs781880 A G -0.0020250 0.0019230 0.2923412 0.2923364 0.2449550 0.3618540 88638
23 154930487 rs781879 T A -0.0099951 0.0065229 0.1254481 0.1254444 0.0196537 0.1263580 88638

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111345 ES:SE:LP:AF:SS:ID   0.00140022:0.00349167:0.162154:0.111345:88638:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116319 ES:SE:LP:AF:SS:ID   0.00343594:0.00330828:0.524332:0.116319:88638:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977362    ES:SE:LP:AF:SS:ID   0.00493208:0.0037181:0.733592:0.0977362:88638:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158097    ES:SE:LP:AF:SS:ID   -0.00876851:0.00884775:0.492593:0.0158097:88638:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00178134   ES:SE:LP:AF:SS:ID   0.0018062:0.0258065:0.0249351:0.00178134:88638:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0567943    ES:SE:LP:AF:SS:ID   0.00465976:0.00458963:0.508673:0.0567943:88638:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122178 ES:SE:LP:AF:SS:ID   0.00188578:0.0031392:0.261198:0.122178:88638:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121884 ES:SE:LP:AF:SS:ID   0.0033816:0.00334744:0.505289:0.121884:88638:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121414 ES:SE:LP:AF:SS:ID   0.0020627:0.00314153:0.291202:0.121414:88638:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00575478   ES:SE:LP:AF:SS:ID   0.0149504:0.0143967:0.524245:0.00575478:88638:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00182996   ES:SE:LP:AF:SS:ID   0.036342:0.0275363:0.728367:0.00182996:88638:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869087 ES:SE:LP:AF:SS:ID   -0.00282817:0.00308949:0.443726:0.869087:88638:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00161171   ES:SE:LP:AF:SS:ID   -0.0169919:0.0271472:0.274603:0.00161171:88638:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12356  ES:SE:LP:AF:SS:ID   0.00288834:0.00306288:0.46133:0.12356:88638:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1431   ES:SE:LP:AF:SS:ID   0.0011026:0.00303162:0.145036:0.1431:88638:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123692 ES:SE:LP:AF:SS:ID   0.00276934:0.0030585:0.43744:0.123692:88638:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87006  ES:SE:LP:AF:SS:ID   -0.00134276:0.00298037:0.185536:0.87006:88638:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874702 ES:SE:LP:AF:SS:ID   -0.00261172:0.00302873:0.41059:0.874702:88638:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129376 ES:SE:LP:AF:SS:ID   0.00116278:0.00298944:0.156577:0.129376:88638:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0357522    ES:SE:LP:AF:SS:ID   0.00818139:0.00546411:0.871859:0.0357522:88638:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869698 ES:SE:LP:AF:SS:ID   -0.00127958:0.0029778:0.175607:0.869698:88638:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869776 ES:SE:LP:AF:SS:ID   -0.00125456:0.0029791:0.171554:0.869776:88638:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869694 ES:SE:LP:AF:SS:ID   -0.00128501:0.00297768:0.176479:0.869694:88638:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00531348   ES:SE:LP:AF:SS:ID   -0.000794621:0.0148625:0.0189238:0.00531348:88638:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00527862   ES:SE:LP:AF:SS:ID   -0.00068104:0.014899:0.0161298:0.00527862:88638:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00567028   ES:SE:LP:AF:SS:ID   -0.0148726:0.0146369:0.509221:0.00567028:88638:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869688 ES:SE:LP:AF:SS:ID   -0.00146572:0.00297159:0.206321:0.869688:88638:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126767 ES:SE:LP:AF:SS:ID   0.0019095:0.00303313:0.27655:0.126767:88638:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:SS:ID   -0.00159006:0.00296383:0.227956:0.869215:88638:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86859  ES:SE:LP:AF:SS:ID   -0.00142767:0.00296185:0.200801:0.86859:88638:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869368 ES:SE:LP:AF:SS:ID   -0.00150342:0.00296659:0.21303:0.869368:88638:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869374 ES:SE:LP:AF:SS:ID   -0.00150562:0.00296678:0.213383:0.869374:88638:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869376 ES:SE:LP:AF:SS:ID   -0.00150902:0.00296681:0.213951:0.869376:88638:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86985  ES:SE:LP:AF:SS:ID   -0.00153181:0.00297473:0.2171:0.86985:88638:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0990386    ES:SE:LP:AF:SS:ID   0.00419482:0.00346174:0.646649:0.0990386:88638:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00651513   ES:SE:LP:AF:SS:ID   -0.0218865:0.0133269:0.997683:0.00651513:88638:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873831 ES:SE:LP:AF:SS:ID   -0.00232873:0.00301866:0.356108:0.873831:88638:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863222 ES:SE:LP:AF:SS:ID   -0.00205528:0.00296101:0.311925:0.863222:88638:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868644 ES:SE:LP:AF:SS:ID   -0.00166376:0.00299045:0.238097:0.868644:88638:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865523 ES:SE:LP:AF:SS:ID   -0.00187756:0.00299119:0.275557:0.865523:88638:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993726    ES:SE:LP:AF:SS:ID   0.00323387:0.00358099:0.435933:0.0993726:88638:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870804 ES:SE:LP:AF:SS:ID   -0.00192461:0.00302519:0.280129:0.870804:88638:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870804 ES:SE:LP:AF:SS:ID   -0.00192472:0.00302519:0.280149:0.870804:88638:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870801 ES:SE:LP:AF:SS:ID   -0.00192492:0.0030252:0.280183:0.870801:88638:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871168 ES:SE:LP:AF:SS:ID   -0.00200913:0.0030266:0.29516:0.871168:88638:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126371 ES:SE:LP:AF:SS:ID   0.00204916:0.0030296:0.302072:0.126371:88638:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105855 ES:SE:LP:AF:SS:ID   0.00318649:0.00329466:0.476952:0.105855:88638:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854488 ES:SE:LP:AF:SS:ID   -0.00237796:0.00295954:0.375004:0.854488:88638:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00169447   ES:SE:LP:AF:SS:ID   0.00147175:0.0258851:0.0201517:0.00169447:88638:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839146 ES:SE:LP:AF:SS:ID   -0.000146475:0.0029236:0.0177098:0.839146:88638:rs376645387