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-22607_2/ukb-d-22607_2.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-22607_2/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 16:35:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22607_2/ukb-d-22607_2.vcf.gz ...
Read summary statistics for 12849020 SNPs.
Dropped 11645 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, 1283346 SNPs remain.
After merging with regression SNP LD, 1283346 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.029 (0.0055)
Lambda GC: 1.0636
Mean Chi^2: 1.058
Intercept: 1.0068 (0.0064)
Ratio: 0.1167 (0.1104)
Analysis finished at Mon Nov 25 16:37:48 2019
Total time elapsed: 2.0m:30.43s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9509,
    "inflation_factor": 1.0445,
    "mean_EFFECT": 0,
    "n": 90145,
    "n_snps": 12849020,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1222474,
    "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": 401318,
    "n_est": 90448.4756,
    "ratio_se_n": 1.0017,
    "mean_diff": 0,
    "ratio_diff": 31.9812,
    "sd_y_est1": 0.2815,
    "sd_y_est2": 0.282,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283346,
    "ldsc_nsnp_merge_regression_ld": 1283346,
    "ldsc_observed_scale_h2_beta": 0.029,
    "ldsc_observed_scale_h2_se": 0.0055,
    "ldsc_intercept_beta": 1.0068,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0636,
    "ldsc_mean_chisq": 1.058,
    "ldsc_ratio": 0.1172
}

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 12838022 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 55461 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32838 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.059849e+00 6.185766e+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 7.896803e+07 5.594327e+07 3.02000e+02 3.282593e+07 7.003553e+07 1.148145e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.630000e-05 6.472100e-03 -6.87508e-02 -1.957300e-03 -2.400000e-06 1.945300e-03 8.807720e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.772600e-03 4.314900e-03 1.09450e-03 1.556400e-03 2.670200e-03 6.745800e-03 2.336180e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.935807e-01 2.902965e-01 1.00000e-07 2.409079e-01 4.906141e-01 7.449103e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.935789e-01 2.902976e-01 1.00000e-07 2.409049e-01 4.906125e-01 7.449099e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.011819e-01 2.568258e-01 1.58610e-03 1.038370e-02 7.364800e-02 3.158840e-01 9.984140e-01 ▇▂▁▁▁
numeric AF_reference 401318 0.9687666 NA NA NA NA NA 2.044007e-01 2.488339e-01 0.00000e+00 7.587900e-03 9.544730e-02 3.230830e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 9.014500e+04 0.000000e+00 9.01450e+04 9.014500e+04 9.014500e+04 9.014500e+04 9.014500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0006640 0.0023179 0.7745367 0.7745358 0.1113110 0.1894970 90145
1 693731 rs12238997 A G 0.0005602 0.0021950 0.7985741 0.7985727 0.1162900 0.1417730 90145
1 707522 rs371890604 G C -0.0008896 0.0024668 0.7183697 0.7183686 0.0977515 0.1293930 90145
1 717587 rs144155419 G A 0.0010285 0.0058873 0.8613140 0.8613135 0.0157464 0.0045926 90145
1 723329 rs189787166 A T -0.0193282 0.0172726 0.2631389 0.2631362 0.0017529 0.0003994 90145
1 730087 rs148120343 T C 0.0003238 0.0030444 0.9153089 0.9153090 0.0568458 0.0127796 90145
1 731718 rs142557973 T C 0.0002496 0.0020831 0.9046279 0.9046280 0.1221550 0.1543530 90145
1 732032 rs61770163 A C -0.0004821 0.0022214 0.8281790 0.8281787 0.1218610 0.1555510 90145
1 734349 rs141242758 T C 0.0001554 0.0020847 0.9405680 0.9405677 0.1213840 0.1525560 90145
1 740284 rs61770167 C T -0.0006980 0.0095502 0.9417350 0.9417353 0.0057634 0.0023962 90145
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0009687 0.0024352 0.6907883 0.6907865 0.0553120 0.0309934 90145
23 154923374 rs111332691 T A 0.0020046 0.0026503 0.4494351 0.4494336 0.0448888 0.0116556 90145
23 154925045 rs509981 C T 0.0009359 0.0012771 0.4636785 0.4636780 0.2445900 0.3634440 90145
23 154925895 rs538470 C T 0.0006857 0.0013056 0.5994790 0.5994762 0.2410980 0.3634440 90145
23 154927581 rs644138 G A 0.0006454 0.0012013 0.5910742 0.5910728 0.3003080 0.4635760 90145
23 154929412 rs557132 C T 0.0009527 0.0012775 0.4558249 0.4558232 0.2444460 0.3568210 90145
23 154929637 rs35185538 CT C 0.0007591 0.0013340 0.5693404 0.5693404 0.2288140 0.3011920 90145
23 154929952 rs4012982 CAA C 0.0007386 0.0013446 0.5828087 0.5828064 0.2383540 0.3165560 90145
23 154930230 rs781880 A G 0.0008573 0.0012771 0.5020408 0.5020400 0.2449110 0.3618540 90145
23 154930487 rs781879 T A 0.0019428 0.0043316 0.6537866 0.6537849 0.0196680 0.1263580 90145

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111311 ES:SE:LP:AF:SS:ID   -0.000663967:0.00231794:0.110958:0.111311:90145:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11629  ES:SE:LP:AF:SS:ID   0.000560155:0.00219501:0.0976848:0.11629:90145:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977515    ES:SE:LP:AF:SS:ID   -0.000889634:0.00246682:0.143652:0.0977515:90145:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157464    ES:SE:LP:AF:SS:ID   0.00102852:0.00588727:0.0648385:0.0157464:90145:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00175286   ES:SE:LP:AF:SS:ID   -0.0193282:0.0172726:0.579815:0.00175286:90145:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568458    ES:SE:LP:AF:SS:ID   0.00032375:0.00304435:0.0384323:0.0568458:90145:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122155 ES:SE:LP:AF:SS:ID   0.00024959:0.00208309:0.04353:0.122155:90145:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121861 ES:SE:LP:AF:SS:ID   -0.000482126:0.00222139:0.0818758:0.121861:90145:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121384 ES:SE:LP:AF:SS:ID   0.000155429:0.00208472:0.0266098:0.121384:90145:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00576344   ES:SE:LP:AF:SS:ID   -0.000698013:0.00955018:0.0260713:0.00576344:90145:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00181816   ES:SE:LP:AF:SS:ID   0.00348695:0.0183145:0.0710918:0.00181816:90145:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869117 ES:SE:LP:AF:SS:ID   -0.000958455:0.00205091:0.193642:0.869117:90145:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00159834   ES:SE:LP:AF:SS:ID   -0.0291111:0.0181266:0.965452:0.00159834:90145:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123502 ES:SE:LP:AF:SS:ID   0.000387601:0.00203324:0.0711875:0.123502:90145:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143012 ES:SE:LP:AF:SS:ID   0.000254187:0.00201276:0.0459964:0.143012:90145:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123637 ES:SE:LP:AF:SS:ID   0.000328853:0.00203029:0.0598188:0.123637:90145:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870111 ES:SE:LP:AF:SS:ID   6.80202e-05:0.00197828:0.0120787:0.870111:90145:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874755 ES:SE:LP:AF:SS:ID   -0.000349901:0.00201043:0.0645774:0.874755:90145:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129319 ES:SE:LP:AF:SS:ID   -8.85117e-05:0.00198446:0.015732:0.129319:90145:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358644    ES:SE:LP:AF:SS:ID   0.00787716:0.00362134:1.52846:0.0358644:90145:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869758 ES:SE:LP:AF:SS:ID   7.01097e-05:0.00197663:0.0124651:0.869758:90145:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869836 ES:SE:LP:AF:SS:ID   6.99386e-05:0.0019775:0.0124289:0.869836:90145:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869754 ES:SE:LP:AF:SS:ID   6.56466e-05:0.00197654:0.0116618:0.869754:90145:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00532358   ES:SE:LP:AF:SS:ID   -0.00227326:0.00985803:0.0874453:0.00532358:90145:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00528889   ES:SE:LP:AF:SS:ID   -0.00259729:0.00988251:0.100896:0.00528889:90145:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00566273   ES:SE:LP:AF:SS:ID   -0.00247236:0.00972479:0.0972815:0.00566273:90145:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869737 ES:SE:LP:AF:SS:ID   -3.46137e-05:0.00197248:0.00612353:0.869737:90145:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126726 ES:SE:LP:AF:SS:ID   -3.12409e-05:0.00201344:0.00541012:0.126726:90145:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869261 ES:SE:LP:AF:SS:ID   9.08875e-05:0.00196734:0.0163052:0.869261:90145:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86865  ES:SE:LP:AF:SS:ID   0.000301642:0.00196607:0.0564733:0.86865:90145:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869414 ES:SE:LP:AF:SS:ID   7.8108e-05:0.00196914:0.0139636:0.869414:90145:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   7.6996e-05:0.00196927:0.0137605:0.869419:90145:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869421 ES:SE:LP:AF:SS:ID   7.59817e-05:0.00196928:0.0135763:0.869421:90145:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869904 ES:SE:LP:AF:SS:ID   -1.08198e-05:0.00197457:0.0019029:0.869904:90145:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0990489    ES:SE:LP:AF:SS:ID   0.000181318:0.00229753:0.028215:0.0990489:90145:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00650816   ES:SE:LP:AF:SS:ID   -0.00326845:0.00885361:0.147517:0.00650816:90145:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873894 ES:SE:LP:AF:SS:ID   -0.00018257:0.00200385:0.0327301:0.873894:90145:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863267 ES:SE:LP:AF:SS:ID   -0.000405952:0.00196557:0.0775984:0.863267:90145:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868697 ES:SE:LP:AF:SS:ID   6.56259e-06:0.00198506:0.00114718:0.868697:90145:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865579 ES:SE:LP:AF:SS:ID   8.2017e-05:0.0019854:0.0145515:0.865579:90145:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993705    ES:SE:LP:AF:SS:ID   0.00100164:0.00237626:0.171741:0.0993705:90145:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870867 ES:SE:LP:AF:SS:ID   -4.21196e-05:0.00200809:0.00732898:0.870867:90145:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870867 ES:SE:LP:AF:SS:ID   -4.22953e-05:0.00200809:0.0073599:0.870867:90145:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870864 ES:SE:LP:AF:SS:ID   -4.14378e-05:0.00200809:0.0072093:0.870864:90145:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87123  ES:SE:LP:AF:SS:ID   5.4429e-05:0.00200905:0.00948977:0.87123:90145:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126315 ES:SE:LP:AF:SS:ID   0.000113046:0.00201122:0.0199166:0.126315:90145:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105889 ES:SE:LP:AF:SS:ID   -0.000803402:0.00218601:0.146769:0.105889:90145:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854607 ES:SE:LP:AF:SS:ID   0.000305443:0.00196487:0.0572649:0.854607:90145:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00166577   ES:SE:LP:AF:SS:ID   -0.0184075:0.0173255:0.540556:0.00166577:90145:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839373 ES:SE:LP:AF:SS:ID   -0.00127865:0.00194121:0.292346:0.839373:90145:rs376645387