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-1137/ieu-a-1137.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-1137/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 18:21:03 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1137/ieu-a-1137.vcf.gz ...
Read summary statistics for 9572131 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, 1219642 SNPs remain.
After merging with regression SNP LD, 1219642 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0897 (0.0216)
Lambda GC: 1.039
Mean Chi^2: 1.0383
Intercept: 0.9994 (0.0065)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 18:22:34 2020
Total time elapsed: 1.0m:31.46s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.948,
    "inflation_factor": 1,
    "mean_EFFECT": -2.1029,
    "n": 22068,
    "n_snps": 9572131,
    "n_clumped_hits": 2,
    "n_p_sig": 11,
    "n_mono": 0,
    "n_ns": 587412,
    "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": 123656,
    "n_est": 19819.0755,
    "ratio_se_n": 0.9477,
    "mean_diff": 2.1041,
    "ratio_diff": 2.9986,
    "sd_y_est1": 3.1677,
    "sd_y_est2": 3.0019,
    "r2_sum1": 0.0341,
    "r2_sum2": 0.0034,
    "r2_sum3": 0.0038,
    "r2_sum4": 0.0031,
    "ldsc_nsnp_merge_refpanel_ld": 1219642,
    "ldsc_nsnp_merge_regression_ld": 1219642,
    "ldsc_observed_scale_h2_beta": 0.0897,
    "ldsc_observed_scale_h2_se": 0.0216,
    "ldsc_intercept_beta": 0.9994,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.039,
    "ldsc_mean_chisq": 1.0383,
    "ldsc_ratio": -0.0157
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 TRUE
mean_EFFECT_01 TRUE
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 47 0 9572130 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 99 0 28993 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 103 0 15511 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.881323e+00 6.234285e+00 1.00000e+00 4.000000e+00 7.000000e+00 1.400000e+01 2.400000e+01 ▇▆▂▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.911780e+07 5.683442e+07 8.28000e+02 3.230646e+07 6.943251e+07 1.155297e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.102927e+00 1.122534e+02 -9.22393e+03 -3.410000e-02 1.700000e-03 3.910000e-02 8.984290e+03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.370328e+01 7.167546e+02 2.39000e-02 3.220000e-02 4.850000e-02 1.037000e-01 5.974190e+04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.002352e-01 2.879192e-01 0.00000e+00 2.516002e-01 5.000000e-01 7.493005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.002355e-01 2.879199e-01 0.00000e+00 2.515800e-01 5.000452e-01 7.492810e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.419094e-01 2.637587e-01 1.00000e-02 3.100000e-02 1.267000e-01 3.849000e-01 9.900000e-01 ▇▂▂▁▁
numeric AF_reference 123656 0.9870817 NA NA NA NA NA 2.386031e-01 2.522913e-01 1.99700e-04 3.154950e-02 1.425720e-01 3.765970e-01 9.996010e-01 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.206800e+04 0.000000e+00 2.20680e+04 2.206800e+04 2.206800e+04 2.206800e+04 2.206800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 14933 rs199856693 G A 0.0923 0.1928 0.6321003 0.6321276 0.0367 0.0283546 22068
1 15774 rs374029747 G A -1.7553 2.0179 0.3843997 0.3843743 0.0103 0.0119808 22068
1 16949 rs199745162 A C 0.1301 0.3499 0.7099994 0.7100265 0.0125 0.0139776 22068
1 51479 rs116400033 T A 0.0597 0.0825 0.4695999 0.4692890 0.2217 0.1281950 22068
1 54490 rs141149254 G A 0.0658 0.0923 0.4757995 0.4759121 0.1578 0.0960463 22068
1 55164 rs3091274 C A 0.3285 0.5596 0.5571999 0.5571859 0.9811 0.9233230 22068
1 55326 rs3107975 T C 0.2717 0.2680 0.3106998 0.3106753 0.0238 0.0459265 22068
1 55545 rs28396308 C T -0.0775 0.0838 0.3551003 0.3550590 0.2389 0.2392170 22068
1 57292 rs201418760 C T 0.3708 0.2831 0.1902002 0.1902687 0.0214 0.0337460 22068
1 58814 rs114420996 G A -0.0487 0.1289 0.7053993 0.7055701 0.0951 0.1090260 22068
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0300 0.1385 0.8284000 0.8285150 0.0514 0.0309934 22068
23 154925045 rs509981 C T -0.0371 0.0623 0.5521003 0.5515055 0.2504 0.3634440 22068
23 154925895 rs538470 C T -0.0357 0.0650 0.5833994 0.5828471 0.2473 0.3634440 22068
23 154927185 rs185685661 T C -0.0456 0.1092 0.6764006 0.6762525 0.1403 0.1796030 22068
23 154927199 rs645904 C T -0.0358 0.0622 0.5647003 0.5649108 0.2502 0.3674170 22068
23 154927581 rs644138 G A -0.0260 0.0604 0.6671999 0.6668585 0.3030 0.4635760 22068
23 154929412 rs557132 C T -0.0329 0.0621 0.5964005 0.5962571 0.2499 0.3568210 22068
23 154929952 rs4012982 CAA C -0.0347 0.0622 0.5769006 0.5769278 0.2503 0.3165560 22068
23 154930230 rs781880 A G -0.0356 0.0625 0.5686002 0.5689490 0.2495 0.3618540 22068
24 13537468 rs7203107 A G -0.3453 0.2839 0.2239000 0.2238808 0.9853 NA 22068

bcf preview

1   14933   rs199856693 G   A   .   PASS    AF=0.0367   ES:SE:LP:AF:SS:ID   0.0923:0.1928:0.199214:0.0367:22068:rs199856693
1   15774   rs374029747 G   A   .   PASS    AF=0.0103   ES:SE:LP:AF:SS:ID   -1.7553:2.0179:0.415217:0.0103:22068:rs374029747
1   16949   rs199745162 A   C   .   PASS    AF=0.0125   ES:SE:LP:AF:SS:ID   0.1301:0.3499:0.148742:0.0125:22068:rs199745162
1   51479   rs116400033 T   A   .   PASS    AF=0.2217   ES:SE:LP:AF:SS:ID   0.0597:0.0825:0.328272:0.2217:22068:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.1578   ES:SE:LP:AF:SS:ID   0.0658:0.0923:0.322576:0.1578:22068:rs141149254
1   55164   rs3091274   C   A   .   PASS    AF=0.9811   ES:SE:LP:AF:SS:ID   0.3285:0.5596:0.253989:0.9811:22068:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.0238   ES:SE:LP:AF:SS:ID   0.2717:0.268:0.507659:0.0238:22068:rs3107975
1   55545   rs28396308  C   T   .   PASS    AF=0.2389   ES:SE:LP:AF:SS:ID   -0.0775:0.0838:0.449649:0.2389:22068:rs28396308
1   57292   rs201418760 C   T   .   PASS    AF=0.0214   ES:SE:LP:AF:SS:ID   0.3708:0.2831:0.720789:0.0214:22068:rs201418760
1   58814   rs114420996 G   A   .   PASS    AF=0.0951   ES:SE:LP:AF:SS:ID   -0.0487:0.1289:0.151565:0.0951:22068:rs114420996
1   61920   rs62637820  G   A   .   PASS    AF=0.0269   ES:SE:LP:AF:SS:ID   0.0445:0.2154:0.0777418:0.0269:22068:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.0189   ES:SE:LP:AF:SS:ID   -0.2767:0.6087:0.187488:0.0189:22068:rs200092917
1   64649   rs181431124 A   C   .   PASS    AF=0.0255   ES:SE:LP:AF:SS:ID   0.0976:0.2177:0.184622:0.0255:22068:rs181431124
1   66219   rs181028663 A   T   .   PASS    AF=0.0182   ES:SE:LP:AF:SS:ID   0.383:0.2391:0.962175:0.0182:22068:rs181028663
1   68082   rs367789441 T   C   .   PASS    AF=0.0615   ES:SE:LP:AF:SS:ID   -0.1533:0.1538:0.496209:0.0615:22068:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0443   ES:SE:LP:AF:SS:ID   0.0496:0.1538:0.126621:0.0443:22068:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0655   ES:SE:LP:AF:SS:ID   -0.1603:0.1481:0.55424:0.0655:22068:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.7496   ES:SE:LP:AF:SS:ID   -0.0246:0.0796:0.120961:0.7496:22068:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.0265   ES:SE:LP:AF:SS:ID   -0.1073:0.2409:0.183162:0.0265:22068:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.0265   ES:SE:LP:AF:SS:ID   -0.1073:0.2409:0.183162:0.0265:22068:rs13328684
1   76854   rs367666799 A   G   .   PASS    AF=0.0675   ES:SE:LP:AF:SS:ID   -0.2293:0.1423:0.969805:0.0675:22068:rs367666799
1   82163   rs139113303 G   A   .   PASS    AF=0.0674   ES:SE:LP:AF:SS:ID   -0.2273:0.142:0.960586:0.0674:22068:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0677   ES:SE:LP:AF:SS:ID   -0.2157:0.1414:0.895513:0.0677:22068:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.356    ES:SE:LP:AF:SS:ID   0.0947:0.073:0.710857:0.356:22068:rs201754587
1   86028   rs114608975 T   C   .   PASS    AF=0.0504   ES:SE:LP:AF:SS:ID   0.013:0.1598:0.0291884:0.0504:22068:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0684   ES:SE:LP:AF:SS:ID   -0.2376:0.1434:1.01068:0.0684:22068:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.1094   ES:SE:LP:AF:SS:ID   -0.1894:0.1217:0.921906:0.1094:22068:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.0135   ES:SE:LP:AF:SS:ID   0.2379:0.7589:0.122686:0.0135:22068:rs188486692
1   87360   rs180907504 C   T   .   PASS    AF=0.0193   ES:SE:LP:AF:SS:ID   -0.3051:0.5362:0.244659:0.0193:22068:rs180907504
1   87409   rs139490478 C   T   .   PASS    AF=0.0704   ES:SE:LP:AF:SS:ID   -0.2444:0.1413:1.07655:0.0704:22068:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.214    ES:SE:LP:AF:SS:ID   0.005:0.0825:0.0215456:0.214:22068:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.0611   ES:SE:LP:AF:SS:ID   -0.173:0.1555:0.574955:0.0611:22068:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.0602   ES:SE:LP:AF:SS:ID   -0.1817:0.1568:0.608007:0.0602:22068:rs143215837
1   88236   rs186918018 C   T   .   PASS    AF=0.011    ES:SE:LP:AF:SS:ID   -0.599:1.1935:0.21056:0.011:22068:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.0605   ES:SE:LP:AF:SS:ID   -0.1802:0.1569:0.600672:0.0605:22068:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.0808   ES:SE:LP:AF:SS:ID   -0.0333:0.1325:0.0959881:0.0808:22068:rs55700207
1   88710   rs186575039 C   G   .   PASS    AF=0.0703   ES:SE:LP:AF:SS:ID   -0.2429:0.1413:1.06707:0.0703:22068:rs186575039
1   89599   rs375955515 A   T   .   PASS    AF=0.0703   ES:SE:LP:AF:SS:ID   -0.2429:0.1413:1.06707:0.0703:22068:rs375955515
1   89946   rs138808727 A   T   .   PASS    AF=0.2272   ES:SE:LP:AF:SS:ID   0.0397:0.082:0.201833:0.2272:22068:rs138808727
1   91190   rs143856811 G   A   .   PASS    AF=0.0714   ES:SE:LP:AF:SS:ID   -0.2804:0.1419:1.31731:0.0714:22068:rs143856811
1   91421   rs28619159  T   C   .   PASS    AF=0.0114   ES:SE:LP:AF:SS:ID   -0.0035:0.3857:0.00313823:0.0114:22068:rs28619159
1   91515   rs376723915 A   C   .   PASS    AF=0.5551   ES:SE:LP:AF:SS:ID   -0.0322:0.0704:0.18876:0.5551:22068:rs376723915
1   92633   rs149776517 C   T   .   PASS    AF=0.0304   ES:SE:LP:AF:SS:ID   0.162:0.1834:0.423543:0.0304:22068:rs149776517
1   92858   rs147061536 G   T   .   PASS    AF=0.2348   ES:SE:LP:AF:SS:ID   0.0232:0.0816:0.110082:0.2348:22068:rs147061536
1   99671   rs146209971 A   T   .   PASS    AF=0.0108   ES:SE:LP:AF:SS:ID   -0.1708:0.9811:0.0645935:0.0108:22068:rs146209971
1   99687   rs139153227 C   T   .   PASS    AF=0.0569   ES:SE:LP:AF:SS:ID   -0.169:0.1606:0.533726:0.0569:22068:rs139153227
1   99719   rs183898652 C   T   .   PASS    AF=0.0109   ES:SE:LP:AF:SS:ID   0.0055:0.8073:0.00239521:0.0109:22068:rs183898652
1   115729  rs199999500 GCACA   G   .   PASS    AF=0.0146   ES:SE:LP:AF:SS:ID   0.0729:0.2961:0.0938805:0.0146:22068:rs199999500
1   115746  rs147538909 C   T   .   PASS    AF=0.0444   ES:SE:LP:AF:SS:ID   -0.2912:0.1824:0.957424:0.0444:22068:rs147538909
1   129010  rs377161483 AATG    A   .   PASS    AF=0.5527   ES:SE:LP:AF:SS:ID   -0.1242:0.0692:1.1393:0.5527:22068:rs377161483