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-2664_5/ukb-d-2664_5.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-2664_5/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 17:08:57 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-2664_5/ukb-d-2664_5.vcf.gz ...
Read summary statistics for 13574904 SNPs.
Dropped 12698 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, 1283496 SNPs remain.
After merging with regression SNP LD, 1283496 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0422 (0.0043)
Lambda GC: 1.094
Mean Chi^2: 1.1124
Intercept: 1.0015 (0.0067)
Ratio: 0.0137 (0.0598)
Analysis finished at Mon Nov 25 17:11:21 2019
Total time elapsed: 2.0m:24.21s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.06,
    "mean_EFFECT": 9.206e-06,
    "n": 134033,
    "n_snps": 13574904,
    "n_clumped_hits": 2,
    "n_p_sig": 10,
    "n_mono": 0,
    "n_ns": 1251420,
    "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": 566482,
    "n_est": 134701.8169,
    "ratio_se_n": 1.0025,
    "mean_diff": 0,
    "ratio_diff": 7.7655,
    "sd_y_est1": 0.494,
    "sd_y_est2": 0.4952,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0009,
    "r2_sum3": 0.0009,
    "r2_sum4": 0.0009,
    "ldsc_nsnp_merge_refpanel_ld": 1283496,
    "ldsc_nsnp_merge_regression_ld": 1283496,
    "ldsc_observed_scale_h2_beta": 0.0422,
    "ldsc_observed_scale_h2_se": 0.0043,
    "ldsc_intercept_beta": 1.0015,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.094,
    "ldsc_mean_chisq": 1.1124,
    "ldsc_ratio": 0.0133
}

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 13562870 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 33330 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051369e+00 6.184960e+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 7.902389e+07 5.591502e+07 3.02000e+02 3.292891e+07 7.013613e+07 1.148579e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 9.200000e-06 1.118950e-02 -1.42950e-01 -3.046000e-03 7.600000e-06 3.047000e-03 1.347000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.999500e-03 7.714000e-03 1.53700e-03 2.282300e-03 4.199600e-03 1.148620e-02 3.965610e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.903920e-01 2.918792e-01 0.00000e+00 2.348432e-01 4.874084e-01 7.437637e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.903908e-01 2.918799e-01 0.00000e+00 2.348407e-01 4.874066e-01 7.437630e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.909515e-01 2.544317e-01 1.00000e-03 7.466600e-03 6.021270e-02 2.956410e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 566482 0.9582699 NA NA NA NA NA 1.964429e-01 2.471196e-01 0.00000e+00 5.591000e-03 8.446490e-02 3.083070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.340330e+05 0.000000e+00 1.34033e+05 1.340330e+05 1.340330e+05 1.340330e+05 1.340330e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0004421 0.0033358 0.8945751 0.8945746 0.1108750 0.1894970 134033
1 693731 rs12238997 A G 0.0003941 0.0031486 0.9003940 0.9003937 0.1162060 0.1417730 134033
1 707522 rs371890604 G C -0.0023631 0.0035467 0.5052345 0.5052337 0.0975793 0.1293930 134033
1 717587 rs144155419 G A 0.0060261 0.0084241 0.4743971 0.4743963 0.0158040 0.0045926 134033
1 723329 rs189787166 A T -0.0151821 0.0255687 0.5526638 0.5526614 0.0016598 0.0003994 134033
1 730087 rs148120343 T C -0.0059470 0.0044045 0.1769518 0.1769493 0.0564609 0.0127796 134033
1 731718 rs142557973 T C -0.0007207 0.0029867 0.8093260 0.8093260 0.1220990 0.1543530 134033
1 732032 rs61770163 A C -0.0012180 0.0031860 0.7022472 0.7022462 0.1216070 0.1555510 134033
1 734349 rs141242758 T C -0.0008865 0.0029878 0.7666921 0.7666915 0.1213600 0.1525560 134033
1 740284 rs61770167 C T 0.0029330 0.0138474 0.8322580 0.8322580 0.0056841 0.0023962 134033
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0020121 0.0033919 0.5530393 0.5530385 0.0562252 0.0309934 134033
23 154923374 rs111332691 T A -0.0009202 0.0037229 0.8047750 0.8047740 0.0445972 0.0116556 134033
23 154925045 rs509981 C T -0.0007663 0.0017891 0.6684178 0.6684174 0.2467450 0.3634440 134033
23 154925895 rs538470 C T -0.0008518 0.0018298 0.6415596 0.6415579 0.2431150 0.3634440 134033
23 154927581 rs644138 G A -0.0011611 0.0016839 0.4904876 0.4904831 0.3034400 0.4635760 134033
23 154929412 rs557132 C T -0.0007849 0.0017898 0.6609978 0.6609973 0.2465880 0.3568210 134033
23 154929637 rs35185538 CT C -0.0008331 0.0018648 0.6550523 0.6550529 0.2305740 0.3011920 134033
23 154929952 rs4012982 CAA C -0.0010193 0.0018808 0.5878331 0.5878322 0.2404630 0.3165560 134033
23 154930230 rs781880 A G -0.0008572 0.0017894 0.6319155 0.6319148 0.2469830 0.3618540 134033
23 154930487 rs781879 T A 0.0051403 0.0060955 0.3990672 0.3990655 0.0199986 0.1263580 134033

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110875 ES:SE:LP:AF:SS:ID   0.000442051:0.00333578:0.0483832:0.110875:134033:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116206 ES:SE:LP:AF:SS:ID   0.000394089:0.00314858:0.0455674:0.116206:134033:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0975793    ES:SE:LP:AF:SS:ID   -0.00236308:0.00354669:0.296507:0.0975793:134033:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015804 ES:SE:LP:AF:SS:ID   0.00602614:0.00842411:0.323858:0.015804:134033:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00165976   ES:SE:LP:AF:SS:ID   -0.0151821:0.0255687:0.257539:0.00165976:134033:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564609    ES:SE:LP:AF:SS:ID   -0.00594695:0.00440447:0.752145:0.0564609:134033:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122099 ES:SE:LP:AF:SS:ID   -0.000720668:0.00298666:0.0918765:0.122099:134033:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121607 ES:SE:LP:AF:SS:ID   -0.00121798:0.00318601:0.15351:0.121607:134033:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12136  ES:SE:LP:AF:SS:ID   -0.000886505:0.00298783:0.115379:0.12136:134033:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00568407   ES:SE:LP:AF:SS:ID   0.00293297:0.0138474:0.079742:0.00568407:134033:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00185254   ES:SE:LP:AF:SS:ID   0.00453275:0.0262087:0.0641437:0.00185254:134033:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869196 ES:SE:LP:AF:SS:ID   -0.0001761:0.00294505:0.0212176:0.869196:134033:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153552   ES:SE:LP:AF:SS:ID   0.0163991:0.0267479:0.267758:0.00153552:134033:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123507 ES:SE:LP:AF:SS:ID   0.000638713:0.00291662:0.0826741:0.123507:134033:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143367 ES:SE:LP:AF:SS:ID   0.00175755:0.00288134:0.266098:0.143367:134033:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123629 ES:SE:LP:AF:SS:ID   0.000735267:0.00291264:0.0965291:0.123629:134033:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870443 ES:SE:LP:AF:SS:ID   -0.000572385:0.00284024:0.0755724:0.870443:134033:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874774 ES:SE:LP:AF:SS:ID   -0.00117509:0.00288515:0.165073:0.874774:134033:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129057 ES:SE:LP:AF:SS:ID   0.000329905:0.00284703:0.0420337:0.129057:134033:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036118 ES:SE:LP:AF:SS:ID   0.00756996:0.0051953:0.838342:0.036118:134033:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870069 ES:SE:LP:AF:SS:ID   -0.000575093:0.00283753:0.0760357:0.870069:134033:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870146 ES:SE:LP:AF:SS:ID   -0.000557423:0.00283833:0.0735012:0.870146:134033:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870071 ES:SE:LP:AF:SS:ID   -0.000583187:0.00283748:0.0771926:0.870071:134033:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00508305   ES:SE:LP:AF:SS:ID   0.0209388:0.0145485:0.823668:0.00508305:134033:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00504745   ES:SE:LP:AF:SS:ID   0.0209346:0.0145874:0.820287:0.00504745:134033:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00570971   ES:SE:LP:AF:SS:ID   -0.0228653:0.0139747:0.992235:0.00570971:134033:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   -0.000627998:0.00283212:0.0838009:0.87014:134033:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126479 ES:SE:LP:AF:SS:ID   0.000176411:0.00288739:0.0216907:0.126479:134033:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869704 ES:SE:LP:AF:SS:ID   -0.000636172:0.00282518:0.0852127:0.869704:134033:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869014 ES:SE:LP:AF:SS:ID   -0.000359462:0.00282291:0.0463978:0.869014:134033:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86985  ES:SE:LP:AF:SS:ID   -0.000558798:0.00282769:0.0739942:0.86985:134033:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869853 ES:SE:LP:AF:SS:ID   -0.000555135:0.00282789:0.0734672:0.869853:134033:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869862 ES:SE:LP:AF:SS:ID   -0.000543215:0.00282795:0.0717711:0.869862:134033:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870293 ES:SE:LP:AF:SS:ID   -0.000682096:0.00283503:0.0915852:0.870293:134033:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991946    ES:SE:LP:AF:SS:ID   -0.0013899:0.00329676:0.171778:0.0991946:134033:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00663777   ES:SE:LP:AF:SS:ID   -0.0211654:0.0125978:1.03179:0.00663777:134033:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874064 ES:SE:LP:AF:SS:ID   -0.00104141:0.00287602:0.144312:0.874064:134033:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863716 ES:SE:LP:AF:SS:ID   -0.000839995:0.00282219:0.115783:0.863716:134033:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868938 ES:SE:LP:AF:SS:ID   -0.000542672:0.00284764:0.0711619:0.868938:134033:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865877 ES:SE:LP:AF:SS:ID   -0.000441468:0.00284969:0.0570569:0.865877:134033:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0991097    ES:SE:LP:AF:SS:ID   0.00207464:0.00341121:0.265146:0.0991097:134033:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871    ES:SE:LP:AF:SS:ID   -0.000867984:0.00288076:0.117371:0.871:134033:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871    ES:SE:LP:AF:SS:ID   -0.000867905:0.00288076:0.117359:0.871:134033:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871001 ES:SE:LP:AF:SS:ID   -0.000853947:0.00288089:0.115255:0.871001:134033:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871387 ES:SE:LP:AF:SS:ID   -0.000840947:0.00288271:0.113227:0.871387:134033:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126105 ES:SE:LP:AF:SS:ID   0.000655936:0.00288382:0.0861485:0.126105:134033:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105767 ES:SE:LP:AF:SS:ID   -0.00180312:0.00314327:0.247023:0.105767:134033:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85509  ES:SE:LP:AF:SS:ID   0.000156485:0.00282103:0.0196493:0.85509:134033:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00157626   ES:SE:LP:AF:SS:ID   -0.0163753:0.0257027:0.280619:0.00157626:134033:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838236 ES:SE:LP:AF:SS:ID   -0.00190572:0.00278468:0.306493:0.838236:134033:rs376645387