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-22614_0/ukb-d-22614_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-22614_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 16:46:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22614_0/ukb-d-22614_0.vcf.gz ...
Read summary statistics for 13566476 SNPs.
Dropped 12678 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: 0.0007 (0.005)
Lambda GC: 0.9993
Mean Chi^2: 1.0026
Intercept: 1.0015 (0.0062)
Ratio: 0.576 (2.3482)
Analysis finished at Mon Nov 25 16:49:01 2019
Total time elapsed: 2.0m:42.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0124,
    "mean_EFFECT": -2.8308e-06,
    "n": 87998,
    "n_snps": 13566476,
    "n_clumped_hits": 0,
    "n_p_sig": 84,
    "n_mono": 0,
    "n_ns": 1251205,
    "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": 562977,
    "n_est": 88300.9014,
    "ratio_se_n": 1.0017,
    "mean_diff": -0,
    "ratio_diff": 122.71,
    "sd_y_est1": 0.0779,
    "sd_y_est2": 0.078,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0007,
    "ldsc_observed_scale_h2_se": 0.005,
    "ldsc_intercept_beta": 1.0015,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 0.9993,
    "ldsc_mean_chisq": 1.0026,
    "ldsc_ratio": 0.5769
}

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 13554462 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57043 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 9.051379e+00 6.184995e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902458e+07 5.591632e+07 3.0200e+02 3.292822e+07 7.013524e+07 1.148617e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.800000e-06 2.160500e-03 -3.7084e-02 -5.322000e-04 2.600000e-05 6.183000e-04 2.634900e-02 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.554300e-03 1.497800e-03 3.0670e-04 4.441000e-04 8.169000e-04 2.232000e-03 7.573800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.985714e-01 2.876681e-01 0.0000e+00 2.487511e-01 4.973533e-01 7.473482e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.985696e-01 2.876691e-01 0.0000e+00 2.487486e-01 4.973507e-01 7.473486e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910725e-01 2.544759e-01 1.0000e-03 7.500800e-03 6.030710e-02 2.957920e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 562977 0.9585023 NA NA NA NA NA 1.965270e-01 2.471465e-01 0.0000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.799800e+04 0.000000e+00 8.7998e+04 8.799800e+04 8.799800e+04 8.799800e+04 8.799800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0011465 0.0006482 0.0769626 0.0769589 0.1114960 0.1894970 87998
1 693731 rs12238997 A G -0.0013448 0.0006141 0.0285411 0.0285383 0.1165300 0.1417730 87998
1 707522 rs371890604 G C -0.0006418 0.0006902 0.3524528 0.3524502 0.0979575 0.1293930 87998
1 717587 rs144155419 G A -0.0013492 0.0016462 0.4124697 0.4124662 0.0157767 0.0045926 87998
1 723329 rs189787166 A T -0.0057859 0.0047960 0.2276638 0.2276596 0.0017824 0.0003994 87998
1 730087 rs148120343 T C -0.0004460 0.0008517 0.6005166 0.6005146 0.0570081 0.0127796 87998
1 731718 rs142557973 T C -0.0012618 0.0005826 0.0303208 0.0303180 0.1224500 0.1543530 87998
1 732032 rs61770163 A C -0.0010056 0.0006215 0.1056380 0.1056339 0.1220280 0.1555510 87998
1 734349 rs141242758 T C -0.0013027 0.0005830 0.0254607 0.0254587 0.1216690 0.1525560 87998
1 740284 rs61770167 C T -0.0023819 0.0026663 0.3716892 0.3716868 0.0057907 0.0023962 87998
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0001951 0.0006835 0.7752665 0.7752668 0.0551068 0.0309934 87998
23 154923374 rs111332691 T A 0.0020477 0.0007425 0.0058208 0.0058196 0.0448647 0.0116556 87998
23 154925045 rs509981 C T 0.0001807 0.0003578 0.6135642 0.6135636 0.2446380 0.3634440 87998
23 154925895 rs538470 C T 0.0001860 0.0003658 0.6111559 0.6111543 0.2411250 0.3634440 87998
23 154927581 rs644138 G A 0.0000832 0.0003366 0.8048770 0.8048758 0.3001550 0.4635760 87998
23 154929412 rs557132 C T 0.0001776 0.0003579 0.6197920 0.6197909 0.2444910 0.3568210 87998
23 154929637 rs35185538 CT C 0.0000433 0.0003738 0.9078471 0.9078465 0.2288010 0.3011920 87998
23 154929952 rs4012982 CAA C 0.0001005 0.0003766 0.7895034 0.7895031 0.2384500 0.3165560 87998
23 154930230 rs781880 A G 0.0001560 0.0003578 0.6628374 0.6628362 0.2449290 0.3618540 87998
23 154930487 rs781879 T A -0.0003295 0.0012089 0.7851705 0.7851692 0.0197684 0.1263580 87998

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111496 ES:SE:LP:AF:SS:ID   -0.00114647:0.000648232:1.11372:0.111496:87998:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11653  ES:SE:LP:AF:SS:ID   -0.00134476:0.0006141:1.54453:0.11653:87998:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0979575    ES:SE:LP:AF:SS:ID   -0.000641774:0.000690193:0.452899:0.0979575:87998:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157767    ES:SE:LP:AF:SS:ID   -0.00134917:0.00164621:0.384608:0.0157767:87998:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00178242   ES:SE:LP:AF:SS:ID   -0.00578594:0.004796:0.642706:0.00178242:87998:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570081    ES:SE:LP:AF:SS:ID   -0.000445997:0.000851691:0.221475:0.0570081:87998:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12245  ES:SE:LP:AF:SS:ID   -0.00126179:0.000582568:1.51826:0.12245:87998:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122028 ES:SE:LP:AF:SS:ID   -0.00100561:0.000621463:0.97618:0.122028:87998:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121669 ES:SE:LP:AF:SS:ID   -0.00130273:0.000583041:1.59413:0.121669:87998:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00579073   ES:SE:LP:AF:SS:ID   -0.00238189:0.00266634:0.42982:0.00579073:87998:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00184367   ES:SE:LP:AF:SS:ID   0.00626728:0.00507881:0.66313:0.00184367:87998:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868837 ES:SE:LP:AF:SS:ID   0.000984587:0.000573607:1.06511:0.868837:87998:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00159984   ES:SE:LP:AF:SS:ID   -0.00132558:0.00506816:0.100361:0.00159984:87998:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123774 ES:SE:LP:AF:SS:ID   -0.0010671:0.000568713:1.21744:0.123774:87998:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143283 ES:SE:LP:AF:SS:ID   -0.00100171:0.000562905:1.12404:0.143283:87998:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123911 ES:SE:LP:AF:SS:ID   -0.00106432:0.000567879:1.21534:0.123911:87998:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.86982  ES:SE:LP:AF:SS:ID   0.00125173:0.00055329:1.62563:0.86982:87998:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874474 ES:SE:LP:AF:SS:ID   0.00092508:0.00056235:1.00014:0.874474:87998:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129597 ES:SE:LP:AF:SS:ID   -0.00128982:0.000555011:1.69615:0.129597:87998:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0357167    ES:SE:LP:AF:SS:ID   -0.00220228:0.00101567:1.52087:0.0357167:87998:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869462 ES:SE:LP:AF:SS:ID   0.00123417:0.000552821:1.59202:0.869462:87998:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869541 ES:SE:LP:AF:SS:ID   0.00124199:0.000553068:1.60679:0.869541:87998:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869458 ES:SE:LP:AF:SS:ID   0.00123466:0.000552796:1.59312:0.869458:87998:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00530476   ES:SE:LP:AF:SS:ID   -0.000647363:0.00276597:0.088869:0.00530476:87998:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00526955   ES:SE:LP:AF:SS:ID   -0.000646279:0.00277294:0.0884642:0.00526955:87998:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00561078   ES:SE:LP:AF:SS:ID   0.000523841:0.00273454:0.0715611:0.00561078:87998:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869456 ES:SE:LP:AF:SS:ID   0.00125517:0.000551676:1.64022:0.869456:87998:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126997 ES:SE:LP:AF:SS:ID   -0.00116496:0.000563158:1.41358:0.126997:87998:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86898  ES:SE:LP:AF:SS:ID   0.00123749:0.000550236:1.61058:0.86898:87998:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868353 ES:SE:LP:AF:SS:ID   0.00121777:0.000549864:1.57211:0.868353:87998:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869132 ES:SE:LP:AF:SS:ID   0.00125105:0.000550741:1.63611:0.869132:87998:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869137 ES:SE:LP:AF:SS:ID   0.00125147:0.000550776:1.63682:0.869137:87998:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86914  ES:SE:LP:AF:SS:ID   0.00125248:0.000550782:1.63886:0.86914:87998:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869616 ES:SE:LP:AF:SS:ID   0.00124454:0.000552263:1.61568:0.869616:87998:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.099274 ES:SE:LP:AF:SS:ID   -0.000864434:0.000642861:0.747788:0.099274:87998:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00645507   ES:SE:LP:AF:SS:ID   -0.000586595:0.00249066:0.0894786:0.00645507:87998:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873585 ES:SE:LP:AF:SS:ID   0.00103641:0.000560449:1.19094:0.873585:87998:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862972 ES:SE:LP:AF:SS:ID   0.00126696:0.000549723:1.67398:0.862972:87998:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868391 ES:SE:LP:AF:SS:ID   0.00135485:0.000555174:1.8335:0.868391:87998:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865279 ES:SE:LP:AF:SS:ID   0.00130669:0.000555245:1.73032:0.865279:87998:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0995469    ES:SE:LP:AF:SS:ID   -0.00153054:0.000664874:1.67085:0.0995469:87998:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.00108574:0.000561618:1.274:0.87056:87998:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.00108574:0.000561618:1.274:0.87056:87998:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870557 ES:SE:LP:AF:SS:ID   0.00108579:0.00056162:1.27409:0.870557:87998:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870925 ES:SE:LP:AF:SS:ID   0.00110568:0.000561885:1.30898:0.870925:87998:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126601 ES:SE:LP:AF:SS:ID   -0.00115947:0.000562501:1.40582:0.126601:87998:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106143 ES:SE:LP:AF:SS:ID   -0.00120589:0.000611431:1.31349:0.106143:87998:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854323 ES:SE:LP:AF:SS:ID   0.0011879:0.000549565:1.51347:0.854323:87998:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00169407   ES:SE:LP:AF:SS:ID   -0.00521076:0.0048107:0.554801:0.00169407:87998:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839279 ES:SE:LP:AF:SS:ID   0.000919725:0.000543436:1.04302:0.839279:87998:rs376645387