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-20455_irnt/ukb-d-20455_irnt.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-20455_irnt/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 15:34:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20455_irnt/ukb-d-20455_irnt.vcf.gz ...
Read summary statistics for 13529016 SNPs.
Dropped 12633 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, 1283495 SNPs remain.
After merging with regression SNP LD, 1283495 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0307 (0.0166)
Lambda GC: 1.0156
Mean Chi^2: 1.0117
Intercept: 0.9959 (0.0058)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 15:36:21 2019
Total time elapsed: 2.0m:17.84s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.019,
    "mean_EFFECT": 0.0001,
    "n": 25698,
    "n_snps": 13529016,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1249843,
    "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": 553326,
    "n_est": 25859.448,
    "ratio_se_n": 1.0031,
    "mean_diff": 4.9209e-06,
    "ratio_diff": 1.1386,
    "sd_y_est1": 0.9867,
    "sd_y_est2": 0.9898,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283495,
    "ldsc_nsnp_merge_regression_ld": 1283495,
    "ldsc_observed_scale_h2_beta": 0.0307,
    "ldsc_observed_scale_h2_se": 0.0166,
    "ldsc_intercept_beta": 0.9959,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 1.0156,
    "ldsc_mean_chisq": 1.0117,
    "ldsc_ratio": -0.3504
}

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 13517047 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56977 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33315 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051527e+00 6.184688e+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 7.901857e+07 5.591643e+07 3.02000e+02 3.292092e+07 7.012881e+07 1.148458e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.810000e-05 5.034700e-02 -5.90968e-01 -1.337030e-02 7.980000e-05 1.355080e-02 6.523450e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.617480e-02 3.482410e-02 7.03240e-03 1.040080e-02 1.904810e-02 5.182160e-02 1.839980e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.970433e-01 2.892088e-01 2.00000e-07 2.462329e-01 4.959615e-01 7.472484e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.970371e-01 2.892125e-01 2.00000e-07 2.462229e-01 4.959552e-01 7.472457e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.915610e-01 2.545824e-01 1.00000e-03 7.638000e-03 6.095300e-02 2.967560e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 553326 0.9591008 NA NA NA NA NA 1.968906e-01 2.472210e-01 0.00000e+00 5.790700e-03 8.506390e-02 3.091050e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.569800e+04 0.000000e+00 2.56980e+04 2.569800e+04 2.569800e+04 2.569800e+04 2.569800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0017985 0.0150830 0.9050890 0.9050872 0.1122210 0.1894970 25698
1 693731 rs12238997 A G 0.0057348 0.0142865 0.6881197 0.6881154 0.1175650 0.1417730 25698
1 707522 rs371890604 G C 0.0013361 0.0160621 0.9337050 0.9337037 0.0993420 0.1293930 25698
1 717587 rs144155419 G A -0.0010564 0.0388847 0.9783260 0.9783253 0.0155582 0.0045926 25698
1 723329 rs189787166 A T 0.1960400 0.1193900 0.1005991 0.1005872 0.0015960 0.0003994 25698
1 730087 rs148120343 T C -0.0004502 0.0197336 0.9818000 0.9817996 0.0585493 0.0127796 25698
1 731718 rs142557973 T C 0.0021828 0.0135478 0.8720000 0.8719990 0.1236220 0.1543530 25698
1 732032 rs61770163 A C 0.0001723 0.0144384 0.9904770 0.9904767 0.1228230 0.1555510 25698
1 734349 rs141242758 T C 0.0015991 0.0135542 0.9060849 0.9060838 0.1229240 0.1525560 25698
1 740284 rs61770167 C T -0.0229069 0.0648000 0.7237157 0.7237125 0.0054915 0.0023962 25698
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0072686 0.0154909 0.6389163 0.6389119 0.0572207 0.0309934 25698
23 154923374 rs111332691 T A 0.0084735 0.0171571 0.6213954 0.6213925 0.0440112 0.0116556 25698
23 154925045 rs509981 C T -0.0091755 0.0082390 0.2654343 0.2654230 0.2421550 0.3634440 25698
23 154925895 rs538470 C T -0.0083912 0.0084251 0.3192699 0.3192605 0.2387890 0.3634440 25698
23 154927581 rs644138 G A -0.0097787 0.0077315 0.2059582 0.2059468 0.2997660 0.4635760 25698
23 154929412 rs557132 C T -0.0090541 0.0082414 0.2719487 0.2719383 0.2420270 0.3568210 25698
23 154929637 rs35185538 CT C -0.0110725 0.0086028 0.1980811 0.1980676 0.2276420 0.3011920 25698
23 154929952 rs4012982 CAA C -0.0104857 0.0086691 0.2264629 0.2264537 0.2365650 0.3165560 25698
23 154930230 rs781880 A G -0.0087528 0.0082409 0.2881927 0.2881831 0.2424080 0.3618540 25698
23 154930487 rs781879 T A 0.0288587 0.0277111 0.2976939 0.2976839 0.0199667 0.1263580 25698

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112221 ES:SE:LP:AF:SS:ID   0.00179846:0.015083:0.0433087:0.112221:25698:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117565 ES:SE:LP:AF:SS:ID   0.0057348:0.0142865:0.162336:0.117565:25698:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.099342 ES:SE:LP:AF:SS:ID   0.00133614:0.0160621:0.0297903:0.099342:25698:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0155582    ES:SE:LP:AF:SS:ID   -0.00105644:0.0388847:0.0095164:0.0155582:25698:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00159599   ES:SE:LP:AF:SS:ID   0.19604:0.11939:0.997406:0.00159599:25698:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0585493    ES:SE:LP:AF:SS:ID   -0.000450178:0.0197336:0.00797697:0.0585493:25698:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123622 ES:SE:LP:AF:SS:ID   0.00218282:0.0135478:0.0594835:0.123622:25698:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122823 ES:SE:LP:AF:SS:ID   0.000172336:0.0144384:0.0041556:0.122823:25698:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122924 ES:SE:LP:AF:SS:ID   0.00159912:0.0135542:0.0428311:0.122924:25698:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00549146   ES:SE:LP:AF:SS:ID   -0.0229069:0.0648:0.140432:0.00549146:25698:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00155662   ES:SE:LP:AF:SS:ID   -0.0921457:0.136348:0.301756:0.00155662:25698:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868352 ES:SE:LP:AF:SS:ID   0.00894405:0.0133762:0.297809:0.868352:25698:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00161705   ES:SE:LP:AF:SS:ID   -0.166628:0.117455:0.806842:0.00161705:25698:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124661 ES:SE:LP:AF:SS:ID   -0.00316209:0.0132412:0.0908415:0.124661:25698:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145501 ES:SE:LP:AF:SS:ID   0.00813243:0.0130673:0.27269:0.145501:25698:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124789 ES:SE:LP:AF:SS:ID   -0.00314969:0.0132231:0.0905879:0.124789:25698:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869226 ES:SE:LP:AF:SS:ID   -0.00266783:0.012899:0.0777163:0.869226:25698:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873703 ES:SE:LP:AF:SS:ID   0.00383211:0.0130798:0.113769:0.873703:25698:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130323 ES:SE:LP:AF:SS:ID   0.00367806:0.0129414:0.109997:0.130323:25698:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0361701    ES:SE:LP:AF:SS:ID   0.0220854:0.0236737:0.454849:0.0361701:25698:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868877 ES:SE:LP:AF:SS:ID   -0.00311385:0.0128894:0.0919946:0.868877:25698:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868934 ES:SE:LP:AF:SS:ID   -0.00351785:0.0128957:0.105122:0.868934:25698:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868863 ES:SE:LP:AF:SS:ID   -0.0032004:0.012889:0.0947974:0.868863:25698:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00475241   ES:SE:LP:AF:SS:ID   0.000107891:0.0687164:0.000544512:0.00475241:25698:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00471609   ES:SE:LP:AF:SS:ID   -0.00107599:0.068868:0.00544794:0.00471609:25698:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00499009   ES:SE:LP:AF:SS:ID   0.0798799:0.0686414:0.611641:0.00499009:25698:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868918 ES:SE:LP:AF:SS:ID   -0.00444889:0.0128616:0.137024:0.868918:25698:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127575 ES:SE:LP:AF:SS:ID   0.00178812:0.0131261:0.049809:0.127575:25698:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868472 ES:SE:LP:AF:SS:ID   -0.00437552:0.0128318:0.134829:0.868472:25698:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867832 ES:SE:LP:AF:SS:ID   -0.00305393:0.0128327:0.0904985:0.867832:25698:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868567 ES:SE:LP:AF:SS:ID   -0.00440051:0.0128435:0.135559:0.868567:25698:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868574 ES:SE:LP:AF:SS:ID   -0.00438465:0.0128445:0.134996:0.868574:25698:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868579 ES:SE:LP:AF:SS:ID   -0.00439187:0.0128447:0.135244:0.868579:25698:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869067 ES:SE:LP:AF:SS:ID   -0.00483708:0.0128746:0.150496:0.869067:25698:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100415 ES:SE:LP:AF:SS:ID   -0.00265277:0.0149615:0.0658709:0.100415:25698:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00598055   ES:SE:LP:AF:SS:ID   0.0523646:0.0610673:0.407621:0.00598055:25698:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872812 ES:SE:LP:AF:SS:ID   0.00115036:0.0130443:0.0316441:0.872812:25698:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86252  ES:SE:LP:AF:SS:ID   -0.00353634:0.0128411:0.106228:0.86252:25698:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867718 ES:SE:LP:AF:SS:ID   -0.00462623:0.012939:0.142252:0.867718:25698:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864609 ES:SE:LP:AF:SS:ID   -0.00539366:0.0129402:0.169529:0.864609:25698:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0998351    ES:SE:LP:AF:SS:ID   0.00131753:0.0154412:0.0305827:0.0998351:25698:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869465 ES:SE:LP:AF:SS:ID   0.00243527:0.0130587:0.0695273:0.869465:25698:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869465 ES:SE:LP:AF:SS:ID   0.00243705:0.0130587:0.0695818:0.869465:25698:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869462 ES:SE:LP:AF:SS:ID   0.0024389:0.0130588:0.0696379:0.869462:25698:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869883 ES:SE:LP:AF:SS:ID   0.00114687:0.0130673:0.0314876:0.869883:25698:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127382 ES:SE:LP:AF:SS:ID   0.00161518:0.0131005:0.0448522:0.127382:25698:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107325 ES:SE:LP:AF:SS:ID   0.00849864:0.0142522:0.258866:0.107325:25698:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854225 ES:SE:LP:AF:SS:ID   -0.00319498:0.0128454:0.0949736:0.854225:25698:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00154433   ES:SE:LP:AF:SS:ID   0.190496:0.118769:0.963599:0.00154433:25698:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838151 ES:SE:LP:AF:SS:ID   0.00708792:0.0127284:0.238351:0.838151:25698:rs376645387