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/ieu-a-import/processed/ieu-a-1007/ieu-a-1007.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/ieu-a-import/processed/ieu-a-1007/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 08:24:05 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1007/ieu-a-1007.vcf.gz ...
Read summary statistics for 6412174 SNPs.
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, 1223918 SNPs remain.
After merging with regression SNP LD, 1223918 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0905 (0.0069)
Lambda GC: 1.2365
Mean Chi^2: 1.3137
Intercept: 0.9902 (0.0101)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 08:25:13 2020
Total time elapsed: 1.0m:8.11s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9262,
    "inflation_factor": 1.222,
    "mean_EFFECT": 0,
    "n": 170911,
    "n_snps": 6412174,
    "n_clumped_hits": 10,
    "n_p_sig": 2188,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 39877,
    "n_est": 229818.8392,
    "ratio_se_n": 1.1596,
    "mean_diff": -7.7331e-07,
    "ratio_diff": 1.1251,
    "sd_y_est1": 0.9075,
    "sd_y_est2": 1.0523,
    "r2_sum1": 0.0023,
    "r2_sum2": 0.0028,
    "r2_sum3": 0.0021,
    "r2_sum4": 0.0022,
    "ldsc_nsnp_merge_refpanel_ld": 1223918,
    "ldsc_nsnp_merge_regression_ld": 1223918,
    "ldsc_observed_scale_h2_beta": 0.0905,
    "ldsc_observed_scale_h2_se": 0.0069,
    "ldsc_intercept_beta": 0.9902,
    "ldsc_intercept_se": 0.0101,
    "ldsc_lambda_gc": 1.2365,
    "ldsc_mean_chisq": 1.3137,
    "ldsc_ratio": -0.0312
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique FALSE
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 1.000000 3 57 0 6412174 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 8.697242e+00 5.777413e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.860856e+07 5.661204e+07 8.28000e+02 3.198241e+07 6.909664e+07 1.146070e+08 2.492205e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 2.940000e-05 6.514800e-03 -6.30000e-02 -4.000000e-03 0.000000e+00 4.000000e-03 8.500000e-02 ▁▃▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 5.480600e-03 2.431700e-03 3.00000e-03 4.000000e-03 4.000000e-03 6.000000e-03 2.100000e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.669281e-01 2.977737e-01 0.00000e+00 2.004001e-01 4.559004e-01 7.245994e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.701350e-01 3.020695e-01 0.00000e+00 2.112995e-01 4.532547e-01 7.388827e-01 1.000000e+00 ▇▆▆▆▇
numeric AF 0 1.000000 NA NA NA NA NA 3.052619e-01 2.541503e-01 1.11900e-02 9.142000e-02 2.220000e-01 4.701000e-01 9.888100e-01 ▇▃▂▂▁
numeric AF_reference 39877 0.993781 NA NA NA NA NA 3.043005e-01 2.479503e-01 1.99700e-04 1.002400e-01 2.322280e-01 4.644570e-01 1.000000e+00 ▇▅▂▂▁
numeric N 0 1.000000 NA NA NA NA NA 1.709110e+05 0.000000e+00 1.70911e+05 1.709110e+05 1.709110e+05 1.709110e+05 1.709110e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 662622 rs61769339 G A 0.005 0.007 0.4862001 0.4750505 0.09515 0.1475640 170911
1 704637 rs142559957 G A -0.004 0.010 0.7120000 0.6891565 0.04851 0.0473243 170911
1 705882 rs72631875 G A -0.004 0.008 0.5761002 0.6170751 0.08209 0.0315495 170911
1 714019 rs114983708 A G -0.009 0.010 0.3730001 0.3681203 0.04664 0.1383790 170911
1 714427 rs12028261 G A 0.009 0.018 0.6211007 0.6170751 0.98507 0.7727640 170911
1 715367 rs12184277 A G -0.006 0.010 0.5605005 0.5485062 0.04664 0.0281550 170911
1 719914 rs187772768 C G -0.006 0.010 0.5350003 0.5485062 0.04851 0.0277556 170911
1 720381 rs116801199 G T -0.007 0.011 0.5018998 0.5245394 0.04291 0.0359425 170911
1 721290 rs12565286 G C -0.006 0.010 0.5619996 0.5485062 0.04664 0.0371406 170911
1 721757 rs189147642 T A -0.007 0.010 0.5143006 0.4839273 0.04851 0.0281550 170911
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219387 rs9616832 T C 0.005 0.008 0.5184000 0.5319711 0.07463 0.0654952 170911
22 51219704 rs147475742 G A 0.007 0.010 0.4763005 0.4839273 0.04851 0.0473243 170911
22 51221731 rs115055839 T C 0.006 0.008 0.4431003 0.4532547 0.07836 0.0625000 170911
22 51222052 rs2879915 G A 0.003 0.005 0.5064004 0.5485062 0.21640 0.2194490 170911
22 51224600 rs187908482 G A 0.000 0.007 0.9458000 1.0000000 0.09515 0.0387380 170911
22 51227891 rs6010091 G A 0.004 0.004 0.2817001 0.3173105 0.34700 0.4039540 170911
22 51229805 rs9616985 T C 0.002 0.008 0.8245999 0.8025873 0.07836 0.0730831 170911
22 51229855 rs144549712 G A -0.006 0.006 0.2791997 0.3173105 0.13250 0.1160140 170911
22 51237063 rs3896457 T C 0.005 0.005 0.2703000 0.3173105 0.23320 0.2050720 170911
23 100784211 rs188350543 C A -0.005 0.004 0.2263002 0.2112995 0.72200 0.6498010 170911

bcf preview

1   662622  rs61769339  G   A   .   PASS    AF=0.09515  ES:SE:LP:AF:SS:ID   0.005:0.007:0.313185:0.09515:170911:rs61769339
1   704637  rs142559957 G   A   .   PASS    AF=0.04851  ES:SE:LP:AF:SS:ID   -0.004:0.01:0.14752:0.04851:170911:rs142559957
1   705882  rs72631875  G   A   .   PASS    AF=0.08209  ES:SE:LP:AF:SS:ID   -0.004:0.008:0.239502:0.08209:170911:rs72631875
1   714019  rs114983708 A   G   .   PASS    AF=0.04664  ES:SE:LP:AF:SS:ID   -0.009:0.01:0.428291:0.04664:170911:rs114983708
1   714427  rs12028261  G   A   .   PASS    AF=0.98507  ES:SE:LP:AF:SS:ID   0.009:0.018:0.206838:0.98507:170911:rs12028261
1   715367  rs12184277  A   G   .   PASS    AF=0.04664  ES:SE:LP:AF:SS:ID   -0.006:0.01:0.251424:0.04664:170911:rs12184277
1   719914  rs187772768 C   G   .   PASS    AF=0.04851  ES:SE:LP:AF:SS:ID   -0.006:0.01:0.271646:0.04851:170911:rs187772768
1   720381  rs116801199 G   T   .   PASS    AF=0.04291  ES:SE:LP:AF:SS:ID   -0.007:0.011:0.299383:0.04291:170911:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.04664  ES:SE:LP:AF:SS:ID   -0.006:0.01:0.250264:0.04664:170911:rs12565286
1   721757  rs189147642 T   A   .   PASS    AF=0.04851  ES:SE:LP:AF:SS:ID   -0.007:0.01:0.288783:0.04851:170911:rs189147642
1   722670  rs116030099 T   C   .   PASS    AF=0.1082   ES:SE:LP:AF:SS:ID   0.005:0.007:0.313096:0.1082:170911:rs116030099
1   723307  rs28659788  C   G   .   PASS    AF=0.04104  ES:SE:LP:AF:SS:ID   -0.007:0.011:0.299383:0.04104:170911:rs28659788
1   723742  rs28375378  T   C   .   PASS    AF=0.03918  ES:SE:LP:AF:SS:ID   -0.008:0.011:0.339324:0.03918:170911:rs28375378
1   723819  rs11804171  T   A   .   PASS    AF=0.04851  ES:SE:LP:AF:SS:ID   -0.005:0.01:0.19071:0.04851:170911:rs11804171
1   723891  rs2977670   G   C   .   PASS    AF=0.9459   ES:SE:LP:AF:SS:ID   0.005:0.009:0.221559:0.9459:170911:rs2977670
1   726794  rs28454925  C   G   .   PASS    AF=0.04851  ES:SE:LP:AF:SS:ID   -0.007:0.01:0.334888:0.04851:170911:rs28454925
1   727841  rs116587930 G   A   .   PASS    AF=0.06157  ES:SE:LP:AF:SS:ID   0.009:0.009:0.4642:0.06157:170911:rs116587930
1   729679  rs4951859   C   G   .   PASS    AF=0.8489   ES:SE:LP:AF:SS:ID   0.001:0.006:0.0614302:0.8489:170911:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.06157  ES:SE:LP:AF:SS:ID   0.008:0.009:0.438779:0.06157:170911:rs148120343
1   732809  rs12131618  T   C   .   PASS    AF=0.05224  ES:SE:LP:AF:SS:ID   -0.007:0.01:0.327995:0.05224:170911:rs12131618
1   734349  rs141242758 T   C   .   PASS    AF=0.1045   ES:SE:LP:AF:SS:ID   0.002:0.007:0.105075:0.1045:170911:rs141242758
1   735985  rs12405651  G   A   .   PASS    AF=0.03358  ES:SE:LP:AF:SS:ID   -0.005:0.012:0.157953:0.03358:170911:rs12405651
1   736289  rs79010578  T   A   .   PASS    AF=0.1269   ES:SE:LP:AF:SS:ID   -0.003:0.006:0.223662:0.1269:170911:rs79010578
1   736736  rs10454457  A   G   .   PASS    AF=0.03918  ES:SE:LP:AF:SS:ID   -0.007:0.011:0.284414:0.03918:170911:rs10454457
1   739528  rs3094317   G   A   .   PASS    AF=0.91791  ES:SE:LP:AF:SS:ID   0.005:0.008:0.267606:0.91791:170911:rs3094317
1   746727  rs144595511 G   A   .   PASS    AF=0.04478  ES:SE:LP:AF:SS:ID   -0.007:0.01:0.30777:0.04478:170911:rs144595511
1   748141  rs2427893   G   A   .   PASS    AF=0.01679  ES:SE:LP:AF:SS:ID   -0.007:0.017:0.183494:0.01679:170911:rs2427893
1   752478  rs146277091 G   A   .   PASS    AF=0.04104  ES:SE:LP:AF:SS:ID   -0.004:0.011:0.140561:0.04104:170911:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.8451   ES:SE:LP:AF:SS:ID   0.002:0.005:0.137392:0.8451:170911:rs3094315
1   752617  rs149886465 C   A   .   PASS    AF=0.04478  ES:SE:LP:AF:SS:ID   -0.005:0.01:0.204537:0.04478:170911:rs149886465
1   752721  rs3131972   A   G   .   PASS    AF=0.8414   ES:SE:LP:AF:SS:ID   0.002:0.005:0.188358:0.8414:170911:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.8228   ES:SE:LP:AF:SS:ID   0.001:0.005:0.0479344:0.8228:170911:rs3131971
1   753474  rs2073814   C   G   .   PASS    AF=0.8358   ES:SE:LP:AF:SS:ID   0:0.005:0.0180003:0.8358:170911:rs2073814
1   753541  rs2073813   G   A   .   PASS    AF=0.1213   ES:SE:LP:AF:SS:ID   0.001:0.007:0.045661:0.1213:170911:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.05037  ES:SE:LP:AF:SS:ID   -0.005:0.01:0.189364:0.05037:170911:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.05037  ES:SE:LP:AF:SS:ID   0:0.01:0.0169152:0.05037:170911:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   -0.001:0.006:0.0397195:0.8787:170911:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   -0.001:0.006:0.0316105:0.8787:170911:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8638   ES:SE:LP:AF:SS:ID   -0.001:0.006:0.0387213:0.8638:170911:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8414   ES:SE:LP:AF:SS:ID   0.001:0.005:0.0478374:0.8414:170911:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.8302   ES:SE:LP:AF:SS:ID   0:0.005:0.0198602:0.8302:170911:rs3131966
1   755890  rs3115858   A   T   .   PASS    AF=0.8713   ES:SE:LP:AF:SS:ID   -0.001:0.006:0.0656026:0.8713:170911:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.8451   ES:SE:LP:AF:SS:ID   -0.001:0.005:0.0344691:0.8451:170911:rs3131962
1   756912  rs6699990   A   G   .   PASS    AF=0.02612  ES:SE:LP:AF:SS:ID   -0.009:0.014:0.286678:0.02612:170911:rs6699990
1   757640  rs3115853   G   A   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   0:0.006:0.0177288:0.8787:170911:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   -0.001:0.006:0.0457092:0.8787:170911:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8769   ES:SE:LP:AF:SS:ID   -0.001:0.006:0.0474982:0.8769:170911:rs4951862
1   758048  rs3131957   A   G   .   PASS    AF=0.1343   ES:SE:LP:AF:SS:ID   -0.005:0.006:0.370794:0.1343:170911:rs3131957
1   758144  rs3131956   A   G   .   PASS    AF=0.8489   ES:SE:LP:AF:SS:ID   0:0.005:0.0283995:0.8489:170911:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8731   ES:SE:LP:AF:SS:ID   -0.001:0.006:0.0441199:0.8731:170911:rs3131954