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-4803_0/ukb-d-4803_0.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-4803_0/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 17:07:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4803_0/ukb-d-4803_0.vcf.gz ...
Read summary statistics for 13567873 SNPs.
Dropped 12690 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: 0.0582 (0.0046)
Lambda GC: 1.1266
Mean Chi^2: 1.1411
Intercept: 1.0034 (0.0066)
Ratio: 0.0239 (0.0466)
Analysis finished at Mon Nov 25 17:09:33 2019
Total time elapsed: 2.0m:17.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0806,
    "mean_EFFECT": -0,
    "n": 117882,
    "n_snps": 13567873,
    "n_clumped_hits": 2,
    "n_p_sig": 28,
    "n_mono": 0,
    "n_ns": 1251208,
    "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": 563299,
    "n_est": 118346.7412,
    "ratio_se_n": 1.002,
    "mean_diff": -0.0001,
    "ratio_diff": 129.3568,
    "sd_y_est1": 0.4542,
    "sd_y_est2": 0.4551,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0005,
    "r2_sum3": 0.0005,
    "r2_sum4": 0.0005,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0582,
    "ldsc_observed_scale_h2_se": 0.0046,
    "ldsc_intercept_beta": 1.0034,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.1266,
    "ldsc_mean_chisq": 1.1411,
    "ldsc_ratio": 0.0241
}

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 13555847 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57056 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33329 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051400e+00 6.184912e+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 7.902508e+07 5.591606e+07 3.02000e+02 3.292944e+07 7.013902e+07 1.148570e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.910000e-05 1.097650e-02 -1.39997e-01 -3.037300e-03 -1.320000e-05 3.004100e-03 1.387200e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.830500e-03 7.546100e-03 1.53630e-03 2.236600e-03 4.114200e-03 1.124430e-02 3.844510e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.876505e-01 2.923687e-01 0.00000e+00 2.311522e-01 4.832168e-01 7.411396e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.876491e-01 2.923695e-01 0.00000e+00 2.311500e-01 4.832154e-01 7.411396e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910588e-01 2.544622e-01 1.00000e-03 7.505600e-03 6.030960e-02 2.958290e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563299 0.9584829 NA NA NA NA NA 1.965112e-01 2.471427e-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 1.178820e+05 0.000000e+00 1.17882e+05 1.178820e+05 1.178820e+05 1.178820e+05 1.178820e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0007766 0.0032702 0.8122939 0.8122936 0.1115810 0.1894970 117882
1 693731 rs12238997 A G -0.0018519 0.0030928 0.5493195 0.5493185 0.1168770 0.1417730 117882
1 707522 rs371890604 G C 0.0002021 0.0034722 0.9535951 0.9535950 0.0981926 0.1293930 117882
1 717587 rs144155419 G A -0.0016103 0.0083279 0.8466749 0.8466743 0.0157291 0.0045926 117882
1 723329 rs189787166 A T 0.0278941 0.0247282 0.2593098 0.2593081 0.0016918 0.0003994 117882
1 730087 rs148120343 T C 0.0022795 0.0043176 0.5975373 0.5975360 0.0567623 0.0127796 117882
1 731718 rs142557973 T C -0.0019143 0.0029365 0.5144593 0.5144586 0.1227030 0.1543530 117882
1 732032 rs61770163 A C -0.0014354 0.0031295 0.6464873 0.6464876 0.1222200 0.1555510 117882
1 734349 rs141242758 T C -0.0016021 0.0029384 0.5855986 0.5855971 0.1219220 0.1525560 117882
1 740284 rs61770167 C T 0.0112333 0.0131244 0.3920460 0.3920478 0.0060284 0.0023962 117882
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0081360 0.0034251 0.0175311 0.0175296 0.0549643 0.0309934 117882
23 154923374 rs111332691 T A -0.0001158 0.0037411 0.9753069 0.9753070 0.0442010 0.0116556 117882
23 154925045 rs509981 C T 0.0003205 0.0017956 0.8583460 0.8583457 0.2443250 0.3634440 117882
23 154925895 rs538470 C T 0.0007127 0.0018357 0.6978290 0.6978290 0.2408360 0.3634440 117882
23 154927581 rs644138 G A 0.0022584 0.0016890 0.1811761 0.1811716 0.2996770 0.4635760 117882
23 154929412 rs557132 C T 0.0003227 0.0017963 0.8574480 0.8574480 0.2441460 0.3568210 117882
23 154929637 rs35185538 CT C -0.0004094 0.0018740 0.8270741 0.8270746 0.2280540 0.3011920 117882
23 154929952 rs4012982 CAA C 0.0010124 0.0018904 0.5922649 0.5922631 0.2381380 0.3165560 117882
23 154930230 rs781880 A G 0.0005967 0.0017958 0.7396989 0.7396987 0.2446240 0.3618540 117882
23 154930487 rs781879 T A 0.0052247 0.0062535 0.4034484 0.4034456 0.0190093 0.1263580 117882

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111581 ES:SE:LP:AF:SS:ID   0.000776573:0.00327022:0.0902868:0.111581:117882:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116877 ES:SE:LP:AF:SS:ID   -0.0018519:0.00309278:0.260175:0.116877:117882:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981926    ES:SE:LP:AF:SS:ID   0.000202056:0.00347218:0.020636:0.0981926:117882:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157291    ES:SE:LP:AF:SS:ID   -0.00161032:0.00832794:0.0722833:0.0157291:117882:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00169177   ES:SE:LP:AF:SS:ID   0.0278941:0.0247282:0.586181:0.00169177:117882:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0567623    ES:SE:LP:AF:SS:ID   0.00227947:0.00431761:0.223635:0.0567623:117882:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122703 ES:SE:LP:AF:SS:ID   -0.00191433:0.00293649:0.288649:0.122703:117882:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12222  ES:SE:LP:AF:SS:ID   -0.00143535:0.00312953:0.18944:0.12222:117882:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121922 ES:SE:LP:AF:SS:ID   -0.00160208:0.00293837:0.2324:0.121922:117882:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00602836   ES:SE:LP:AF:SS:ID   0.0112333:0.0131244:0.406663:0.00602836:117882:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00178226   ES:SE:LP:AF:SS:ID   0.0451606:0.026405:1.05943:0.00178226:117882:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868783 ES:SE:LP:AF:SS:ID   0.00252458:0.00289704:0.416213:0.868783:117882:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00160222   ES:SE:LP:AF:SS:ID   -0.027063:0.0255279:0.538973:0.00160222:117882:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12379  ES:SE:LP:AF:SS:ID   -0.00291475:0.00286973:0.508945:0.12379:117882:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143426 ES:SE:LP:AF:SS:ID   -0.00302703:0.00284185:0.542413:0.143426:117882:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12391  ES:SE:LP:AF:SS:ID   -0.00292645:0.00286553:0.512672:0.12391:117882:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869962 ES:SE:LP:AF:SS:ID   0.00192539:0.00279099:0.309552:0.869962:117882:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874645 ES:SE:LP:AF:SS:ID   0.00254644:0.00283798:0.432297:0.874645:117882:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129609 ES:SE:LP:AF:SS:ID   -0.00170583:0.00279698:0.266049:0.129609:117882:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0368674    ES:SE:LP:AF:SS:ID   -0.0036179:0.00504275:0.325047:0.0368674:117882:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   0.00153199:0.00278813:0.234565:0.86957:117882:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869693 ES:SE:LP:AF:SS:ID   0.00161665:0.00278968:0.250074:0.869693:117882:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86956  ES:SE:LP:AF:SS:ID   0.00158286:0.00278796:0.243967:0.86956:117882:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00506018   ES:SE:LP:AF:SS:ID   -0.0263038:0.0143447:1.17587:0.00506018:117882:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00502696   ES:SE:LP:AF:SS:ID   -0.0263211:0.014383:1.1723:0.00502696:117882:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00551475   ES:SE:LP:AF:SS:ID   0.0288364:0.0139253:1.41588:0.00551475:117882:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869687 ES:SE:LP:AF:SS:ID   0.00191489:0.00278344:0.308494:0.869687:117882:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126898 ES:SE:LP:AF:SS:ID   -0.00233108:0.00284014:0.385332:0.126898:117882:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869268 ES:SE:LP:AF:SS:ID   0.00186548:0.002777:0.299525:0.869268:117882:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868472 ES:SE:LP:AF:SS:ID   0.00109608:0.00277359:0.15945:0.868472:117882:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869416 ES:SE:LP:AF:SS:ID   0.00186762:0.00277924:0.299651:0.869416:117882:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869423 ES:SE:LP:AF:SS:ID   0.00186828:0.00277944:0.299755:0.869423:117882:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869431 ES:SE:LP:AF:SS:ID   0.00186879:0.00277952:0.299843:0.869431:117882:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869858 ES:SE:LP:AF:SS:ID   0.00202167:0.00278662:0.329613:0.869858:117882:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0997694    ES:SE:LP:AF:SS:ID   -0.000434848:0.00323163:0.049168:0.0997694:117882:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00632595   ES:SE:LP:AF:SS:ID   0.0160077:0.0126336:0.687964:0.00632595:117882:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873792 ES:SE:LP:AF:SS:ID   0.00234358:0.0028292:0.389903:0.873792:117882:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863113 ES:SE:LP:AF:SS:ID   0.0011758:0.00277404:0.172844:0.863113:117882:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868567 ES:SE:LP:AF:SS:ID   0.00178437:0.00280087:0.280605:0.868567:117882:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865357 ES:SE:LP:AF:SS:ID   0.00178708:0.00280067:0.281152:0.865357:117882:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994301    ES:SE:LP:AF:SS:ID   -0.00392812:0.00335833:0.615935:0.0994301:117882:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870598 ES:SE:LP:AF:SS:ID   0.00227662:0.00283289:0.375092:0.870598:117882:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870598 ES:SE:LP:AF:SS:ID   0.002277:0.00283289:0.375173:0.870598:117882:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.8706   ES:SE:LP:AF:SS:ID   0.00228881:0.00283304:0.377629:0.8706:117882:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870994 ES:SE:LP:AF:SS:ID   0.00226919:0.00283479:0.373212:0.870994:117882:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126474 ES:SE:LP:AF:SS:ID   -0.00214951:0.00283652:0.348167:0.126474:117882:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106227 ES:SE:LP:AF:SS:ID   -0.000529001:0.00308581:0.0635436:0.106227:117882:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854511 ES:SE:LP:AF:SS:ID   0.000769116:0.00277424:0.107015:0.854511:117882:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00159212   ES:SE:LP:AF:SS:ID   0.0358219:0.0249149:0.822458:0.00159212:117882:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837943 ES:SE:LP:AF:SS:ID   0.00207144:0.00272954:0.348803:0.837943:117882:rs376645387