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-30240_irnt/ukb-d-30240_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-30240_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 14:58:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30240_irnt/ukb-d-30240_irnt.vcf.gz ...
Read summary statistics for 13586217 SNPs.
Dropped 12711 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1785 (0.0138)
Lambda GC: 1.614
Mean Chi^2: 2.4185
Intercept: 1.1444 (0.019)
Ratio: 0.1018 (0.0134)
Analysis finished at Mon Nov 25 15:01:43 2019
Total time elapsed: 2.0m:49.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3906,
    "mean_EFFECT": -0,
    "n": 344728,
    "n_snps": 13586217,
    "n_clumped_hits": 288,
    "n_p_sig": 75994,
    "n_mono": 0,
    "n_ns": 1251786,
    "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": 569217,
    "n_est": 346033.3941,
    "ratio_se_n": 1.0019,
    "mean_diff": 4.841e-07,
    "ratio_diff": 1.1421,
    "sd_y_est1": 1.0017,
    "sd_y_est2": 1.0036,
    "r2_sum1": 0.0965,
    "r2_sum2": 0.0962,
    "r2_sum3": 0.0958,
    "r2_sum4": 0.0959,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1785,
    "ldsc_observed_scale_h2_se": 0.0138,
    "ldsc_intercept_beta": 1.1444,
    "ldsc_intercept_se": 0.019,
    "ldsc_lambda_gc": 1.614,
    "ldsc_mean_chisq": 2.4185,
    "ldsc_ratio": 0.1018
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 13574170 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57082 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051358e+00 6.184962e+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 7.902498e+07 5.591474e+07 3.02000e+02 3.293100e+07 7.013848e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.670000e-05 1.512710e-02 -2.47739e-01 -4.635600e-03 5.500000e-06 4.634700e-03 3.792290e-01 ▁▇▃▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.013780e-02 9.779400e-03 1.98280e-03 2.886200e-03 5.318700e-03 1.456810e-02 4.973640e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.448301e-01 3.044287e-01 0.00000e+00 1.670760e-01 4.263969e-01 7.082278e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.448296e-01 3.044290e-01 0.00000e+00 1.670755e-01 4.263967e-01 7.082273e-01 9.999999e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908069e-01 2.544041e-01 1.00000e-03 7.430400e-03 6.003430e-02 2.953250e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569217 0.9581033 NA NA NA NA NA 1.963367e-01 2.471015e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.447280e+05 0.000000e+00 3.44728e+05 3.447280e+05 3.447280e+05 3.447280e+05 3.447280e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0023853 0.0042249 0.5723636 0.5723633 0.1106300 0.1894970 344728
1 693731 rs12238997 A G -0.0008394 0.0039921 0.8334580 0.8334577 0.1158140 0.1417730 344728
1 707522 rs371890604 G C -0.0000681 0.0044901 0.9878990 0.9878989 0.0972246 0.1293930 344728
1 717587 rs144155419 G A -0.0084053 0.0106916 0.4317745 0.4317764 0.0157293 0.0045926 344728
1 723329 rs189787166 A T 0.0077171 0.0317651 0.8080499 0.8080498 0.0017197 0.0003994 344728
1 730087 rs148120343 T C -0.0028889 0.0055572 0.6031731 0.6031726 0.0564851 0.0127796 344728
1 731718 rs142557973 T C -0.0002043 0.0037860 0.9569561 0.9569556 0.1217310 0.1543530 344728
1 732032 rs61770163 A C -0.0005154 0.0040392 0.8984700 0.8984696 0.1211220 0.1555510 344728
1 734349 rs141242758 T C -0.0000364 0.0037880 0.9923360 0.9923363 0.1209620 0.1525560 344728
1 740284 rs61770167 C T 0.0098348 0.0173439 0.5706805 0.5706805 0.0057743 0.0023962 344728
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0033785 0.0043713 0.4395963 0.4395963 0.0561572 0.0309934 344728
23 154923374 rs111332691 T A 0.0023416 0.0048041 0.6259620 0.6259621 0.0447962 0.0116556 344728
23 154925045 rs509981 C T -0.0056513 0.0023119 0.0145077 0.0145070 0.2456200 0.3634440 344728
23 154925895 rs538470 C T -0.0056656 0.0023648 0.0165836 0.0165834 0.2419510 0.3634440 344728
23 154927581 rs644138 G A -0.0042616 0.0021742 0.0499885 0.0499878 0.3021760 0.4635760 344728
23 154929412 rs557132 C T -0.0055731 0.0023126 0.0159562 0.0159556 0.2454740 0.3568210 344728
23 154929637 rs35185538 CT C -0.0054182 0.0024136 0.0247754 0.0247745 0.2297020 0.3011920 344728
23 154929952 rs4012982 CAA C -0.0057521 0.0024324 0.0180401 0.0180395 0.2394380 0.3165560 344728
23 154930230 rs781880 A G -0.0058320 0.0023121 0.0116592 0.0116585 0.2458850 0.3618540 344728
23 154930487 rs781879 T A 0.0053380 0.0079370 0.5012357 0.5012352 0.0195263 0.1263580 344728

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11063  ES:SE:LP:AF:SS:ID   -0.00238527:0.0042249:0.242328:0.11063:344728:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115814 ES:SE:LP:AF:SS:ID   -0.000839417:0.00399211:0.0791163:0.115814:344728:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972246    ES:SE:LP:AF:SS:ID   -6.81019e-05:0.00449012:0.00528745:0.0972246:344728:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157293    ES:SE:LP:AF:SS:ID   -0.00840526:0.0106916:0.364743:0.0157293:344728:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00171967   ES:SE:LP:AF:SS:ID   0.0077171:0.0317651:0.0925618:0.00171967:344728:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564851    ES:SE:LP:AF:SS:ID   -0.00288888:0.00555721:0.219558:0.0564851:344728:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121731 ES:SE:LP:AF:SS:ID   -0.000204347:0.003786:0.019108:0.121731:344728:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121122 ES:SE:LP:AF:SS:ID   -0.000515376:0.00403916:0.0464964:0.121122:344728:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120962 ES:SE:LP:AF:SS:ID   -3.63842e-05:0.003788:0.00334125:0.120962:344728:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00577433   ES:SE:LP:AF:SS:ID   0.00983485:0.0173439:0.243607:0.00577433:344728:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187951   ES:SE:LP:AF:SS:ID   0.000207687:0.032756:0.00220267:0.00187951:344728:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869781 ES:SE:LP:AF:SS:ID   0.00152669:0.00373486:0.165764:0.869781:344728:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153602   ES:SE:LP:AF:SS:ID   -0.00262435:0.0337388:0.0277972:0.00153602:344728:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122887 ES:SE:LP:AF:SS:ID   -0.00145538:0.00369832:0.158683:0.122887:344728:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142713 ES:SE:LP:AF:SS:ID   0.00103928:0.0036556:0.110036:0.142713:344728:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123004 ES:SE:LP:AF:SS:ID   -0.00148279:0.00369316:0.162377:0.123004:344728:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870907 ES:SE:LP:AF:SS:ID   0.000667595:0.00359904:0.0691309:0.870907:344728:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875493 ES:SE:LP:AF:SS:ID   0.000933773:0.00365852:0.0977017:0.875493:344728:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128618 ES:SE:LP:AF:SS:ID   -0.0013022:0.00360799:0.14378:0.128618:344728:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363562    ES:SE:LP:AF:SS:ID   -0.00563462:0.00654685:0.409576:0.0363562:344728:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8705   ES:SE:LP:AF:SS:ID   0.000896152:0.00359525:0.0951979:0.8705:344728:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870603 ES:SE:LP:AF:SS:ID   0.000975058:0.00359685:0.104398:0.870603:344728:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870495 ES:SE:LP:AF:SS:ID   0.000862879:0.0035951:0.091344:0.870495:344728:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050587    ES:SE:LP:AF:SS:ID   -0.0142993:0.018426:0.358797:0.0050587:344728:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00502543   ES:SE:LP:AF:SS:ID   -0.0142024:0.0184754:0.354517:0.00502543:344728:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558653   ES:SE:LP:AF:SS:ID   0.0110351:0.0178698:0.270116:0.00558653:344728:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870578 ES:SE:LP:AF:SS:ID   0.000604033:0.00358879:0.0623121:0.870578:344728:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125958 ES:SE:LP:AF:SS:ID   -0.000896437:0.0036621:0.0933305:0.125958:344728:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870143 ES:SE:LP:AF:SS:ID   0.000494417:0.00358013:0.0505314:0.870143:344728:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869424 ES:SE:LP:AF:SS:ID   0.000571205:0.00357679:0.0589266:0.869424:344728:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870297 ES:SE:LP:AF:SS:ID   0.000546057:0.00358324:0.0560714:0.870297:344728:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870302 ES:SE:LP:AF:SS:ID   0.000542954:0.00358349:0.0557301:0.870302:344728:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870311 ES:SE:LP:AF:SS:ID   0.000552237:0.00358361:0.056738:0.870311:344728:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870753 ES:SE:LP:AF:SS:ID   0.000710926:0.00359273:0.0741003:0.870753:344728:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0987466    ES:SE:LP:AF:SS:ID   0.000480788:0.00417691:0.0417415:0.0987466:344728:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064811    ES:SE:LP:AF:SS:ID   0.0102202:0.01614:0.278527:0.0064811:344728:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874657 ES:SE:LP:AF:SS:ID   0.00123604:0.00364627:0.133938:0.874657:344728:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864055 ES:SE:LP:AF:SS:ID   0.000464192:0.00357577:0.047347:0.864055:344728:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   0.000485383:0.00361045:0.0491213:0.869437:344728:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866397 ES:SE:LP:AF:SS:ID   0.000605726:0.0036114:0.0620816:0.866397:344728:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987146    ES:SE:LP:AF:SS:ID   0.00107662:0.00432466:0.0950676:0.0987146:344728:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   0.00124545:0.00365237:0.134834:0.871574:344728:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   0.00124581:0.00365237:0.134878:0.871574:344728:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871573 ES:SE:LP:AF:SS:ID   0.00127545:0.00365244:0.138504:0.871573:344728:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871944 ES:SE:LP:AF:SS:ID   0.00121301:0.00365452:0.130798:0.871944:344728:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125545 ES:SE:LP:AF:SS:ID   -0.00148284:0.0036573:0.164215:0.125545:344728:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105344 ES:SE:LP:AF:SS:ID   0.00141947:0.0039827:0.141743:0.105344:344728:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855407 ES:SE:LP:AF:SS:ID   0.000617392:0.00357494:0.0640461:0.855407:344728:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164172   ES:SE:LP:AF:SS:ID   0.00212263:0.0318215:0.023734:0.00164172:344728:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838259 ES:SE:LP:AF:SS:ID   -0.00409268:0.00351924:0.611096:0.838259:344728:rs376645387