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-30760_irnt/ukb-d-30760_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-30760_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 14:51:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30760_irnt/ukb-d-30760_irnt.vcf.gz ...
Read summary statistics for 13585297 SNPs.
Dropped 12712 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2632 (0.0508)
Lambda GC: 1.7159
Mean Chi^2: 2.604
Intercept: 1.1458 (0.0191)
Ratio: 0.0909 (0.0119)
Analysis finished at Mon Nov 25 14:53:24 2019
Total time elapsed: 2.0m:16.91s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.4285,
    "mean_EFFECT": 6.1542e-06,
    "n": 315133,
    "n_snps": 13585297,
    "n_clumped_hits": 272,
    "n_p_sig": 56886,
    "n_mono": 0,
    "n_ns": 1251737,
    "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": 568995,
    "n_est": 316357.6956,
    "ratio_se_n": 1.0019,
    "mean_diff": -7.1789e-07,
    "ratio_diff": 0.5365,
    "sd_y_est1": 0.9067,
    "sd_y_est2": 0.9084,
    "r2_sum1": 0.0943,
    "r2_sum2": 0.1147,
    "r2_sum3": 0.1142,
    "r2_sum4": 0.114,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.2632,
    "ldsc_observed_scale_h2_se": 0.0508,
    "ldsc_intercept_beta": 1.1458,
    "ldsc_intercept_se": 0.0191,
    "ldsc_lambda_gc": 1.7159,
    "ldsc_mean_chisq": 2.604,
    "ldsc_ratio": 0.0909
}
 

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 13573249 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33335 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051264e+00 6.184949e+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 7.902526e+07 5.591521e+07 3.02000e+02 3.293044e+07 7.013885e+07 1.148599e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 6.200000e-06 1.436530e-02 -4.41410e-01 -4.459700e-03 2.500000e-05 4.475500e-03 9.098400e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.595300e-03 9.255500e-03 1.87540e-03 2.732300e-03 5.034400e-03 1.378900e-02 4.666800e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.409948e-01 3.052056e-01 0.00000e+00 1.610601e-01 4.201496e-01 7.053798e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.409943e-01 3.052058e-01 0.00000e+00 1.610634e-01 4.201448e-01 7.053847e-01 1.000000e+00 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908198e-01 2.544077e-01 1.00000e-03 7.434100e-03 6.004500e-02 2.953300e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568995 0.9581169 NA NA NA NA NA 1.963465e-01 2.471051e-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 3.151330e+05 0.000000e+00 3.15133e+05 3.151330e+05 3.151330e+05 3.151330e+05 3.151330e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0046519 0.0040001 0.2448499 0.2448514 0.1105400 0.1894970 315133
1 693731 rs12238997 A G 0.0042819 0.0037788 0.2571503 0.2571565 0.1158500 0.1417730 315133
1 707522 rs371890604 G C 0.0049159 0.0042518 0.2476099 0.2476024 0.0972120 0.1293930 315133
1 717587 rs144155419 G A 0.0133160 0.0101240 0.1884200 0.1884123 0.0157110 0.0045926 315133
1 723329 rs189787166 A T 0.0094069 0.0299070 0.7531093 0.7531122 0.0017335 0.0003994 315133
1 730087 rs148120343 T C 0.0092645 0.0052642 0.0784224 0.0784237 0.0564740 0.0127796 315133
1 731718 rs142557973 T C 0.0036808 0.0035844 0.3044802 0.3044702 0.1217300 0.1543530 315133
1 732032 rs61770163 A C 0.0041353 0.0038252 0.2796701 0.2796670 0.1210900 0.1555510 315133
1 734349 rs141242758 T C 0.0036730 0.0035863 0.3057602 0.3057525 0.1209500 0.1525560 315133
1 740284 rs61770167 C T 0.0016375 0.0164430 0.9206700 0.9206727 0.0057544 0.0023962 315133
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0026947 0.0041393 0.5150400 0.5150440 0.056084 0.0309934 315133
23 154923374 rs111332691 T A -0.0007857 0.0045293 0.8622901 0.8622885 0.045008 0.0116556 315133
23 154925045 rs509981 C T 0.0124000 0.0021864 0.0000000 0.0000000 0.245770 0.3634440 315133
23 154925895 rs538470 C T 0.0122670 0.0022366 0.0000000 0.0000000 0.242060 0.3634440 315133
23 154927581 rs644138 G A 0.0116130 0.0020565 0.0000000 0.0000000 0.302240 0.4635760 315133
23 154929412 rs557132 C T 0.0124050 0.0021870 0.0000000 0.0000000 0.245620 0.3568210 315133
23 154929637 rs35185538 CT C 0.0135360 0.0022822 0.0000000 0.0000000 0.230010 0.3011920 315133
23 154929952 rs4012982 CAA C 0.0126020 0.0023000 0.0000000 0.0000000 0.239560 0.3165560 315133
23 154930230 rs781880 A G 0.0123360 0.0021868 0.0000000 0.0000000 0.246000 0.3618540 315133
23 154930487 rs781879 T A 0.0047336 0.0075170 0.5288798 0.5288783 0.019473 0.1263580 315133

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11054  ES:SE:LP:AF:SS:ID   0.0046519:0.0040001:0.6111:0.11054:315133:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11585  ES:SE:LP:AF:SS:ID   0.0042819:0.0037788:0.589813:0.11585:315133:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097212 ES:SE:LP:AF:SS:ID   0.0049159:0.0042518:0.606232:0.097212:315133:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015711 ES:SE:LP:AF:SS:ID   0.013316:0.010124:0.724873:0.015711:315133:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017335    ES:SE:LP:AF:SS:ID   0.0094069:0.029907:0.123142:0.0017335:315133:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056474 ES:SE:LP:AF:SS:ID   0.0092645:0.0052642:1.10556:0.056474:315133:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12173  ES:SE:LP:AF:SS:ID   0.0036808:0.0035844:0.516441:0.12173:315133:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12109  ES:SE:LP:AF:SS:ID   0.0041353:0.0038252:0.553354:0.12109:315133:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12095  ES:SE:LP:AF:SS:ID   0.003673:0.0035863:0.514619:0.12095:315133:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057544    ES:SE:LP:AF:SS:ID   0.0016375:0.016443:0.035896:0.0057544:315133:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018569    ES:SE:LP:AF:SS:ID   0.035075:0.031208:0.583276:0.0018569:315133:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86974  ES:SE:LP:AF:SS:ID   -0.0029293:0.0035355:0.390011:0.86974:315133:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015184    ES:SE:LP:AF:SS:ID   -0.031337:0.032135:0.482171:0.0015184:315133:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12292  ES:SE:LP:AF:SS:ID   0.0031553:0.0035017:0.434684:0.12292:315133:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14273  ES:SE:LP:AF:SS:ID   0.002256:0.0034605:0.288657:0.14273:315133:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12304  ES:SE:LP:AF:SS:ID   0.003038:0.0034968:0.414584:0.12304:315133:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87096  ES:SE:LP:AF:SS:ID   -0.0039494:0.0034084:0.60806:0.87096:315133:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87548  ES:SE:LP:AF:SS:ID   -0.0030044:0.003464:0.413683:0.87548:315133:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12859  ES:SE:LP:AF:SS:ID   0.0035852:0.0034166:0.531608:0.12859:315133:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036316 ES:SE:LP:AF:SS:ID   -0.0025213:0.0062007:0.16476:0.036316:315133:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   -0.0040083:0.0034047:0.621457:0.87054:315133:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   -0.0043138:0.0034064:0.687421:0.87066:315133:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   -0.0039983:0.0034046:0.619355:0.87054:315133:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050347    ES:SE:LP:AF:SS:ID   -0.00098353:0.017472:0.0199466:0.0050347:315133:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050013    ES:SE:LP:AF:SS:ID   -0.00035038:0.017519:0.00698725:0.0050013:315133:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055145    ES:SE:LP:AF:SS:ID   -0.0037122:0.017033:0.0822477:0.0055145:315133:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   -0.0041285:0.003399:0.648764:0.87064:315133:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12593  ES:SE:LP:AF:SS:ID   0.0039016:0.0034676:0.584142:0.12593:315133:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   -0.0045032:0.0033909:0.734805:0.87021:315133:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   -0.0039786:0.0033878:0.619355:0.86948:315133:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   -0.0043217:0.0033937:0.692804:0.87035:315133:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   -0.0043362:0.003394:0.695984:0.87036:315133:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   -0.0043564:0.0033941:0.700471:0.87037:315133:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87081  ES:SE:LP:AF:SS:ID   -0.0041972:0.0034027:0.66276:0.87081:315133:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098804 ES:SE:LP:AF:SS:ID   0.0035341:0.0039546:0.430041:0.098804:315133:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.006394 ES:SE:LP:AF:SS:ID   -0.0078575:0.015395:0.214827:0.006394:315133:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87466  ES:SE:LP:AF:SS:ID   -0.003994:0.0034525:0.606723:0.87466:315133:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86409  ES:SE:LP:AF:SS:ID   -0.0038838:0.0033868:0.599497:0.86409:315133:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   -0.0042556:0.0034189:0.671152:0.86948:315133:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86643  ES:SE:LP:AF:SS:ID   -0.0038625:0.0034196:0.58722:0.86643:315133:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0988   ES:SE:LP:AF:SS:ID   0.0025254:0.0040922:0.269904:0.0988:315133:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87159  ES:SE:LP:AF:SS:ID   -0.0041438:0.0034583:0.636708:0.87159:315133:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87159  ES:SE:LP:AF:SS:ID   -0.0041442:0.0034583:0.636783:0.87159:315133:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87159  ES:SE:LP:AF:SS:ID   -0.0041604:0.0034584:0.640202:0.87159:315133:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87195  ES:SE:LP:AF:SS:ID   -0.0041821:0.0034603:0.644338:0.87195:315133:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12555  ES:SE:LP:AF:SS:ID   0.0037122:0.0034628:0.54711:0.12555:315133:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10538  ES:SE:LP:AF:SS:ID   0.0043274:0.0037719:0.599859:0.10538:315133:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85542  ES:SE:LP:AF:SS:ID   -0.005301:0.0033852:0.930443:0.85542:315133:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016515    ES:SE:LP:AF:SS:ID   0.013582:0.02999:0.186673:0.0016515:315133:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83823  ES:SE:LP:AF:SS:ID   0.0029326:0.0033301:0.421923:0.83823:315133:rs376645387