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-20501/ukb-d-20501.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-20501/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 17:19:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20501/ukb-d-20501.vcf.gz ...
Read summary statistics for 11973910 SNPs.
Dropped 10423 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, 1283005 SNPs remain.
After merging with regression SNP LD, 1283005 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0188 (0.0048)
Lambda GC: 1.043
Mean Chi^2: 1.0418
Intercept: 0.9978 (0.0073)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:20:50 2019
Total time elapsed: 1.0m:43.87s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9489,
    "inflation_factor": 1.0354,
    "mean_EFFECT": 4.2377e-06,
    "n": 115338,
    "n_snps": 11973910,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1183394,
    "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": 280790,
    "n_est": 115587.6172,
    "ratio_se_n": 1.0011,
    "mean_diff": 0,
    "ratio_diff": 12.7577,
    "sd_y_est1": 0.2001,
    "sd_y_est2": 0.2003,
    "r2_sum1": 0,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1283005,
    "ldsc_nsnp_merge_regression_ld": 1283005,
    "ldsc_observed_scale_h2_beta": 0.0188,
    "ldsc_observed_scale_h2_se": 0.0048,
    "ldsc_intercept_beta": 0.9978,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.043,
    "ldsc_mean_chisq": 1.0418,
    "ldsc_ratio": -0.0526
}

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 11964109 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 53328 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32134 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.069015e+00 6.184423e+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 7.889102e+07 5.598022e+07 3.02000e+02 3.269702e+07 6.991701e+07 1.147529e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.200000e-06 3.268500e-03 -3.62411e-02 -1.136900e-03 -8.900000e-06 1.114000e-03 4.356970e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.505800e-03 2.064700e-03 6.90800e-04 9.573000e-04 1.515600e-03 3.453100e-03 1.285050e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.943375e-01 2.902835e-01 0.00000e+00 2.413832e-01 4.925065e-01 7.458779e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.943361e-01 2.902843e-01 0.00000e+00 2.413803e-01 4.925062e-01 7.458771e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.151300e-01 2.594714e-01 2.59550e-03 1.554520e-02 9.308520e-02 3.421900e-01 9.974040e-01 ▇▂▁▁▁
numeric AF_reference 280790 0.9765498 NA NA NA NA NA 2.164568e-01 2.509444e-01 0.00000e+00 1.218050e-02 1.126200e-01 3.442490e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.153380e+05 0.000000e+00 1.15338e+05 1.153380e+05 1.153380e+05 1.153380e+05 1.153380e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0016559 0.0014520 0.2541283 0.2541248 0.1117160 0.1894970 115338
1 693731 rs12238997 A G -0.0017829 0.0013756 0.1949521 0.1949498 0.1167150 0.1417730 115338
1 707522 rs371890604 G C -0.0007712 0.0015434 0.6172811 0.6172818 0.0983598 0.1293930 115338
1 717587 rs144155419 G A -0.0068651 0.0036934 0.0630638 0.0630613 0.0157738 0.0045926 115338
1 730087 rs148120343 T C -0.0011341 0.0019138 0.5534673 0.5534656 0.0569094 0.0127796 115338
1 731718 rs142557973 T C -0.0013599 0.0013050 0.2973733 0.2973690 0.1226760 0.1543530 115338
1 732032 rs61770163 A C -0.0017654 0.0013910 0.2044038 0.2044019 0.1222600 0.1555510 115338
1 734349 rs141242758 T C -0.0013295 0.0013057 0.3085937 0.3085917 0.1219270 0.1525560 115338
1 740284 rs61770167 C T -0.0057881 0.0059615 0.3315943 0.3315922 0.0058483 0.0023962 115338
1 749963 rs529266287 T TAA 0.0016594 0.0012863 0.1970380 0.1970348 0.8689770 0.7641770 115338
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0018727 0.0015343 0.2222557 0.2222518 0.0554625 0.0309934 115338
23 154923374 rs111332691 T A -0.0005005 0.0016732 0.7648548 0.7648533 0.0447511 0.0116556 115338
23 154925045 rs509981 C T 0.0012046 0.0008058 0.1349469 0.1349441 0.2447140 0.3634440 115338
23 154925895 rs538470 C T 0.0014202 0.0008240 0.0848028 0.0847995 0.2410980 0.3634440 115338
23 154927581 rs644138 G A 0.0015178 0.0007582 0.0452991 0.0452970 0.3005390 0.4635760 115338
23 154929412 rs557132 C T 0.0012044 0.0008060 0.1351049 0.1351019 0.2445980 0.3568210 115338
23 154929637 rs35185538 CT C 0.0007600 0.0008418 0.3666587 0.3666564 0.2289070 0.3011920 115338
23 154929952 rs4012982 CAA C 0.0010364 0.0008482 0.2217839 0.2217836 0.2386740 0.3165560 115338
23 154930230 rs781880 A G 0.0011957 0.0008058 0.1378221 0.1378196 0.2450100 0.3618540 115338
23 154930487 rs781879 T A 0.0025686 0.0027477 0.3498928 0.3498911 0.0195762 0.1263580 115338

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111716 ES:SE:LP:AF:SS:ID   -0.0016559:0.00145205:0.594947:0.111716:115338:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116715 ES:SE:LP:AF:SS:ID   -0.00178288:0.0013756:0.710072:0.116715:115338:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983598    ES:SE:LP:AF:SS:ID   -0.000771222:0.00154335:0.209517:0.0983598:115338:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157738    ES:SE:LP:AF:SS:ID   -0.00686514:0.0036934:1.20022:0.0157738:115338:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569094    ES:SE:LP:AF:SS:ID   -0.00113407:0.0019138:0.256908:0.0569094:115338:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122676 ES:SE:LP:AF:SS:ID   -0.00135993:0.001305:0.526698:0.122676:115338:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12226  ES:SE:LP:AF:SS:ID   -0.00176537:0.00139103:0.689511:0.12226:115338:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121927 ES:SE:LP:AF:SS:ID   -0.00132946:0.00130572:0.510613:0.121927:115338:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00584827   ES:SE:LP:AF:SS:ID   -0.00578813:0.00596154:0.479393:0.00584827:115338:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.868977 ES:SE:LP:AF:SS:ID   0.00165936:0.00128628:0.70545:0.868977:115338:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123731 ES:SE:LP:AF:SS:ID   -0.00182695:0.00127446:0.818966:0.123731:115338:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143372 ES:SE:LP:AF:SS:ID   -0.00163299:0.00126067:0.709502:0.143372:115338:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123856 ES:SE:LP:AF:SS:ID   -0.00180502:0.00127268:0.806572:0.123856:115338:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869741 ES:SE:LP:AF:SS:ID   0.00137807:0.00123945:0.574781:0.869741:115338:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874514 ES:SE:LP:AF:SS:ID   0.00169509:0.00126018:0.74814:0.874514:115338:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129722 ES:SE:LP:AF:SS:ID   -0.00146387:0.0012429:0.621813:0.129722:115338:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365318    ES:SE:LP:AF:SS:ID   -0.000374952:0.00225628:0.0614733:0.0365318:115338:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869337 ES:SE:LP:AF:SS:ID   0.0014327:0.00123826:0.606843:0.869337:115338:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86941  ES:SE:LP:AF:SS:ID   0.00145175:0.00123872:0.617601:0.86941:115338:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869337 ES:SE:LP:AF:SS:ID   0.00143259:0.00123823:0.606799:0.869337:115338:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00514716   ES:SE:LP:AF:SS:ID   -0.00359567:0.0063117:0.244969:0.00514716:115338:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00511618   ES:SE:LP:AF:SS:ID   -0.00348356:0.00632573:0.235194:0.00511618:115338:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00566981   ES:SE:LP:AF:SS:ID   0.00716293:0.00611223:0.617552:0.00566981:115338:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869415 ES:SE:LP:AF:SS:ID   0.00138941:0.00123601:0.583414:0.869415:115338:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126989 ES:SE:LP:AF:SS:ID   -0.00163827:0.00126173:0.711883:0.126989:115338:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868937 ES:SE:LP:AF:SS:ID   0.00125733:0.0012328:0.511758:0.868937:115338:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868336 ES:SE:LP:AF:SS:ID   0.00143516:0.0012323:0.612297:0.868336:115338:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869126 ES:SE:LP:AF:SS:ID   0.00130239:0.00123402:0.535743:0.869126:115338:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869133 ES:SE:LP:AF:SS:ID   0.00130229:0.00123411:0.535639:0.869133:115338:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869135 ES:SE:LP:AF:SS:ID   0.00130378:0.00123411:0.536459:0.869135:115338:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869569 ES:SE:LP:AF:SS:ID   0.00136538:0.00123722:0.569:0.869569:115338:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.099537 ES:SE:LP:AF:SS:ID   -0.0009287:0.00143883:0.28514:0.099537:115338:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00652889   ES:SE:LP:AF:SS:ID   0.00671559:0.00554829:0.64564:0.00652889:115338:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873628 ES:SE:LP:AF:SS:ID   0.0015352:0.00125609:0.654366:0.873628:115338:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862925 ES:SE:LP:AF:SS:ID   0.00117626:0.00123205:0.468872:0.862925:115338:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868312 ES:SE:LP:AF:SS:ID   0.0012786:0.00124384:0.517155:0.868312:115338:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86533  ES:SE:LP:AF:SS:ID   0.00117374:0.00124403:0.461644:0.86533:115338:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997868    ES:SE:LP:AF:SS:ID   -0.00173329:0.00148623:0.613462:0.0997868:115338:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870623 ES:SE:LP:AF:SS:ID   0.001377:0.00125862:0.562354:0.870623:115338:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870623 ES:SE:LP:AF:SS:ID   0.00137702:0.00125862:0.562364:0.870623:115338:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870621 ES:SE:LP:AF:SS:ID   0.00137584:0.00125862:0.561714:0.870621:115338:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870947 ES:SE:LP:AF:SS:ID   0.00144446:0.00125917:0.599766:0.870947:115338:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126576 ES:SE:LP:AF:SS:ID   -0.00171426:0.00126025:0.760068:0.126576:115338:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106319 ES:SE:LP:AF:SS:ID   -0.00088057:0.00137001:0.283673:0.106319:115338:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85437  ES:SE:LP:AF:SS:ID   0.000823348:0.00123171:0.297706:0.85437:115338:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839089 ES:SE:LP:AF:SS:ID   -0.00055806:0.00122007:0.188837:0.839089:115338:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763104 ES:SE:LP:AF:SS:ID   0.000365554:0.000978286:0.149567:0.763104:115338:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105173 ES:SE:LP:AF:SS:ID   0.000540261:0.00135309:0.161348:0.105173:115338:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00768264   ES:SE:LP:AF:SS:ID   0.00399384:0.00501195:0.371068:0.00768264:115338:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129977 ES:SE:LP:AF:SS:ID   -0.00144696:0.0012424:0.612318:0.129977:115338:rs762168062