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-30700_irnt/ukb-d-30700_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-30700_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 14:54:41 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30700_irnt/ukb-d-30700_irnt.vcf.gz ...
Read summary statistics for 13585972 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: 0.1797 (0.0091)
Lambda GC: 1.6911
Mean Chi^2: 2.5035
Intercept: 1.1698 (0.0173)
Ratio: 0.113 (0.0115)
Analysis finished at Mon Nov 25 14:57:03 2019
Total time elapsed: 2.0m:21.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.42,
    "mean_EFFECT": 0,
    "n": 344104,
    "n_snps": 13585972,
    "n_clumped_hits": 337,
    "n_p_sig": 66392,
    "n_mono": 0,
    "n_ns": 1251782,
    "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": 569174,
    "n_est": 345442.5007,
    "ratio_se_n": 1.0019,
    "mean_diff": 6.111e-06,
    "ratio_diff": 28.1139,
    "sd_y_est1": 0.8065,
    "sd_y_est2": 0.8081,
    "r2_sum1": 0.0536,
    "r2_sum2": 0.0824,
    "r2_sum3": 0.082,
    "r2_sum4": 0.082,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1797,
    "ldsc_observed_scale_h2_se": 0.0091,
    "ldsc_intercept_beta": 1.1698,
    "ldsc_intercept_se": 0.0173,
    "ldsc_lambda_gc": 1.6911,
    "ldsc_mean_chisq": 2.5035,
    "ldsc_ratio": 0.1129
}

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 13573925 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 9.051263e+00 6.184974e+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 7.902575e+07 5.591531e+07 3.02000e+02 3.293100e+07 7.013917e+07 1.148606e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.480000e-05 1.216450e-02 -1.44370e-01 -3.761700e-03 2.570000e-05 3.814300e-03 3.016100e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.169500e-03 7.880500e-03 1.59840e-03 2.326000e-03 4.286200e-03 1.174000e-02 3.984600e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.415190e-01 3.051480e-01 0.00000e+00 1.621799e-01 4.215499e-01 7.054399e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.415185e-01 3.051482e-01 0.00000e+00 1.621816e-01 4.215530e-01 7.054433e-01 9.999999e-01 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908102e-01 2.544047e-01 1.00000e-03 7.431400e-03 6.003900e-02 2.953200e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569174 0.9581058 NA NA NA NA NA 1.963398e-01 2.471029e-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 3.441040e+05 0.000000e+00 3.44104e+05 3.441040e+05 3.441040e+05 3.441040e+05 3.441040e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0015593 0.0034053 0.6470204 0.6470215 0.1105200 0.1894970 344104
1 693731 rs12238997 A G 0.0014875 0.0032161 0.6437007 0.6437108 0.1158100 0.1417730 344104
1 707522 rs371890604 G C 0.0030300 0.0036176 0.4022703 0.4022712 0.0972400 0.1293930 344104
1 717587 rs144155419 G A 0.0008692 0.0086347 0.9198201 0.9198166 0.0156660 0.0045926 344104
1 723329 rs189787166 A T -0.0368300 0.0254330 0.1475802 0.1475839 0.0017371 0.0003994 344104
1 730087 rs148120343 T C 0.0009955 0.0044824 0.8242501 0.8242466 0.0564220 0.0127796 344104
1 731718 rs142557973 T C 0.0009702 0.0030504 0.7504504 0.7504469 0.1216900 0.1543530 344104
1 732032 rs61770163 A C 0.0024048 0.0032549 0.4600002 0.4600135 0.1211000 0.1555510 344104
1 734349 rs141242758 T C 0.0010244 0.0030520 0.7371299 0.7371358 0.1209200 0.1525560 344104
1 740284 rs61770167 C T -0.0070417 0.0139980 0.6149404 0.6149288 0.0057566 0.0023962 344104
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0025247 0.0035244 0.4737901 0.4737760 0.056199 0.0309934 344104
23 154923374 rs111332691 T A 0.0035810 0.0038695 0.3547399 0.3547357 0.044864 0.0116556 344104
23 154925045 rs509981 C T 0.0019368 0.0018638 0.2987198 0.2987269 0.245660 0.3634440 344104
23 154925895 rs538470 C T 0.0017550 0.0019065 0.3573000 0.3572932 0.242000 0.3634440 344104
23 154927581 rs644138 G A 0.0023421 0.0017528 0.1814901 0.1814823 0.302250 0.4635760 344104
23 154929412 rs557132 C T 0.0018911 0.0018643 0.3104102 0.3104037 0.245520 0.3568210 344104
23 154929637 rs35185538 CT C 0.0016562 0.0019458 0.3946999 0.3946768 0.229770 0.3011920 344104
23 154929952 rs4012982 CAA C 0.0018441 0.0019607 0.3469501 0.3469450 0.239500 0.3165560 344104
23 154930230 rs781880 A G 0.0021346 0.0018640 0.2521500 0.2521380 0.245920 0.3618540 344104
23 154930487 rs781879 T A 0.0098140 0.0063894 0.1245400 0.1245429 0.019563 0.1263580 344104

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11052  ES:SE:LP:AF:SS:ID   0.0015593:0.0034053:0.189082:0.11052:344104:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   0.0014875:0.0032161:0.191316:0.11581:344104:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.09724  ES:SE:LP:AF:SS:ID   0.00303:0.0036176:0.395482:0.09724:344104:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015666 ES:SE:LP:AF:SS:ID   0.00086921:0.0086347:0.0362971:0.015666:344104:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017371    ES:SE:LP:AF:SS:ID   -0.03683:0.025433:0.830972:0.0017371:344104:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056422 ES:SE:LP:AF:SS:ID   0.00099548:0.0044824:0.083941:0.056422:344104:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12169  ES:SE:LP:AF:SS:ID   0.00097018:0.0030504:0.124678:0.12169:344104:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.1211   ES:SE:LP:AF:SS:ID   0.0024048:0.0032549:0.337242:0.1211:344104:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12092  ES:SE:LP:AF:SS:ID   0.0010244:0.003052:0.132456:0.12092:344104:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057566    ES:SE:LP:AF:SS:ID   -0.0070417:0.013998:0.211167:0.0057566:344104:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018599    ES:SE:LP:AF:SS:ID   -0.038951:0.026551:0.846582:0.0018599:344104:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86981  ES:SE:LP:AF:SS:ID   -5.343e-05:0.003009:0.00619797:0.86981:344104:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.001521 ES:SE:LP:AF:SS:ID   0.004008:0.027337:0.0538229:0.001521:344104:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12288  ES:SE:LP:AF:SS:ID   4.7337e-05:0.0029798:0.00553767:0.12288:344104:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1427   ES:SE:LP:AF:SS:ID   -9.7089e-06:0.002945:0.0011437:0.1427:344104:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   0.00014068:0.0029756:0.016694:0.12299:344104:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87097  ES:SE:LP:AF:SS:ID   0.0001176:0.0029001:0.0142817:0.87097:344104:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87552  ES:SE:LP:AF:SS:ID   -0.00027995:0.0029478:0.0341683:0.87552:344104:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12857  ES:SE:LP:AF:SS:ID   0.00018476:0.0029072:0.0225828:0.12857:344104:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036304 ES:SE:LP:AF:SS:ID   0.011736:0.0052792:1.58153:0.036304:344104:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   3.3656e-05:0.0028971:0.00404469:0.87056:344104:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   -0.00016589:0.0028984:0.0202878:0.87066:344104:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   6.4374e-05:0.002897:0.00776912:0.87056:344104:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050467    ES:SE:LP:AF:SS:ID   -0.0058975:0.014863:0.160195:0.0050467:344104:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050136    ES:SE:LP:AF:SS:ID   -0.0056817:0.014903:0.153032:0.0050136:344104:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055492    ES:SE:LP:AF:SS:ID   -0.0014069:0.014455:0.0350525:0.0055492:344104:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   1.7826e-05:0.002892:0.002142:0.87064:344104:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   0.00062959:0.0029507:0.0803781:0.12592:344104:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   0.00012324:0.0028851:0.0150543:0.87021:344104:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   -9.3189e-05:0.0028825:0.0113474:0.86949:344104:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   3.8487e-05:0.0028875:0.00464126:0.87036:344104:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   3.3625e-05:0.0028877:0.00405345:0.87037:344104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   2.0165e-05:0.0028878:0.00242578:0.87038:344104:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87082  ES:SE:LP:AF:SS:ID   4.5615e-05:0.0028951:0.00549368:0.87082:344104:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098786 ES:SE:LP:AF:SS:ID   -0.00090076:0.0033648:0.102962:0.098786:344104:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064349    ES:SE:LP:AF:SS:ID   -0.0017571:0.013061:0.0491583:0.0064349:344104:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.8747   ES:SE:LP:AF:SS:ID   0.00012031:0.002938:0.0144209:0.8747:344104:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86412  ES:SE:LP:AF:SS:ID   -0.00015472:0.0028818:0.0190064:0.86412:344104:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   -0.00013557:0.0029092:0.0164504:0.8695:344104:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.0005005:0.0029098:0.0637678:0.86644:344104:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098744 ES:SE:LP:AF:SS:ID   -0.0032185:0.0034833:0.44916:0.098744:344104:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.00031116:0.0029431:0.0381994:0.87162:344104:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.00031101:0.0029431:0.0381804:0.87162:344104:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.00030848:0.0029431:0.0378581:0.87162:344104:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87199  ES:SE:LP:AF:SS:ID   -0.0001101:0.0029448:0.0131522:0.87199:344104:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12551  ES:SE:LP:AF:SS:ID   0.00037594:0.0029468:0.0464916:0.12551:344104:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   0.00016086:0.0032088:0.0177197:0.10539:344104:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85546  ES:SE:LP:AF:SS:ID   -0.00044761:0.0028806:0.0572382:0.85546:344104:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016559    ES:SE:LP:AF:SS:ID   -0.040648:0.025497:0.955108:0.0016559:344104:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83825  ES:SE:LP:AF:SS:ID   -0.0020011:0.0028363:0.318316:0.83825:344104:rs376645387