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-1131/ieu-a-1131.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-1131/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 11:53:14 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1131/ieu-a-1131.vcf.gz ...
Read summary statistics for 9629643 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, 1219757 SNPs remain.
After merging with regression SNP LD, 1219757 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1495 (0.0195)
Lambda GC: 1.0638
Mean Chi^2: 1.0921
Intercept: 0.9989 (0.0077)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 11:54:50 2020
Total time elapsed: 1.0m:36.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9476,
    "inflation_factor": 1.064,
    "mean_EFFECT": -0.0276,
    "n": 32498,
    "n_snps": 9629643,
    "n_clumped_hits": 17,
    "n_p_sig": 864,
    "n_mono": 0,
    "n_ns": 590486,
    "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": 124346,
    "n_est": 30103.8616,
    "ratio_se_n": 0.9625,
    "mean_diff": 0.0256,
    "ratio_diff": 2.6047,
    "sd_y_est1": 2.4144,
    "sd_y_est2": 2.3238,
    "r2_sum1": 0.167,
    "r2_sum2": 0.0286,
    "r2_sum3": 0.0309,
    "r2_sum4": 0.0313,
    "ldsc_nsnp_merge_refpanel_ld": 1219757,
    "ldsc_nsnp_merge_regression_ld": 1219757,
    "ldsc_observed_scale_h2_beta": 0.1495,
    "ldsc_observed_scale_h2_se": 0.0195,
    "ldsc_intercept_beta": 0.9989,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.0638,
    "ldsc_mean_chisq": 1.0921,
    "ldsc_ratio": -0.0119
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
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 47 0 9629642 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 99 0 29141 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 103 0 15569 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.880458e+00 6.232924e+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 7.911435e+07 5.684123e+07 8.28000e+02 3.230045e+07 6.941997e+07 1.155294e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.764030e-02 5.047790e+00 -8.87301e+03 -2.710000e-02 -2.100000e-03 2.060000e-02 2.131000e+01 ▁▁▁▁▇
numeric SE 0 1.0000000 NA NA NA NA NA 1.076597e-01 2.745287e+01 1.70000e-02 2.040000e-02 3.060000e-02 6.560000e-02 5.120560e+04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.901872e-01 2.915014e-01 0.00000e+00 2.351002e-01 4.865999e-01 7.428002e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.901875e-01 2.915033e-01 0.00000e+00 2.351049e-01 4.866467e-01 7.428172e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.408322e-01 2.635920e-01 1.00000e-02 3.040000e-02 1.253000e-01 3.831000e-01 9.900000e-01 ▇▂▂▁▁
numeric AF_reference 124346 0.9870872 NA NA NA NA NA 2.373745e-01 2.521985e-01 1.99700e-04 3.072850e-02 1.407750e-01 3.748000e-01 9.996010e-01 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.249800e+04 0.000000e+00 3.24980e+04 3.249800e+04 3.249800e+04 3.249800e+04 3.249800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 14933 rs199856693 G A -0.0104 0.0970 0.9144000 0.9146172 0.0389 0.0283546 32498
1 15774 rs374029747 G A -0.1893 0.6514 0.7712994 0.7713535 0.0111 0.0119808 32498
1 16949 rs199745162 A C 0.3466 0.1631 0.0335297 0.0335802 0.0135 0.0139776 32498
1 51479 rs116400033 T A 0.0609 0.0415 0.1426002 0.1422483 0.2258 0.1281950 32498
1 54490 rs141149254 G A 0.0693 0.0468 0.1385001 0.1386681 0.1589 0.0960463 32498
1 55164 rs3091274 C A 0.0688 0.2282 0.7630992 0.7630409 0.9796 0.9233230 32498
1 55326 rs3107975 T C 0.0990 0.2144 0.6442998 0.6442579 0.0235 0.0459265 32498
1 55545 rs28396308 C T -0.0965 0.0423 0.0224300 0.0225293 0.2353 0.2392170 32498
1 57292 rs201418760 C T 0.0928 0.2232 0.6774995 0.6775779 0.0216 0.0337460 32498
1 58814 rs114420996 G A -0.0400 0.0646 0.5354994 0.5357879 0.0952 0.1090260 32498
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 32498
23 154925045 rs509981 C T -0.0371 0.0623 0.5521003 0.5515055 0.2504 0.3634440 32498
23 154925895 rs538470 C T -0.0357 0.0650 0.5833994 0.5828471 0.2473 0.3634440 32498
23 154927185 rs185685661 T C -0.0456 0.1092 0.6764006 0.6762525 0.1403 0.1796030 32498
23 154927199 rs645904 C T -0.0358 0.0622 0.5647003 0.5649108 0.2502 0.3674170 32498
23 154927581 rs644138 G A -0.0260 0.0604 0.6671999 0.6668585 0.3030 0.4635760 32498
23 154929412 rs557132 C T -0.0329 0.0621 0.5964005 0.5962571 0.2499 0.3568210 32498
23 154929952 rs4012982 CAA C -0.0347 0.0622 0.5769006 0.5769278 0.2503 0.3165560 32498
23 154930230 rs781880 A G -0.0356 0.0625 0.5686002 0.5689490 0.2495 0.3618540 32498
24 13537468 rs7203107 A G -0.0305 0.1911 0.8731000 0.8731944 0.9831 NA 32498

bcf preview

1   14933   rs199856693 G   A   .   PASS    AF=0.0389   ES:SE:LP:AF:SS:ID   -0.0104:0.097:0.0388638:0.0389:32498:rs199856693
1   15774   rs374029747 G   A   .   PASS    AF=0.0111   ES:SE:LP:AF:SS:ID   -0.1893:0.6514:0.112777:0.0111:32498:rs374029747
1   16949   rs199745162 A   C   .   PASS    AF=0.0135   ES:SE:LP:AF:SS:ID   0.3466:0.1631:1.47457:0.0135:32498:rs199745162
1   51479   rs116400033 T   A   .   PASS    AF=0.2258   ES:SE:LP:AF:SS:ID   0.0609:0.0415:0.84588:0.2258:32498:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.1589   ES:SE:LP:AF:SS:ID   0.0693:0.0468:0.85855:0.1589:32498:rs141149254
1   55164   rs3091274   C   A   .   PASS    AF=0.9796   ES:SE:LP:AF:SS:ID   0.0688:0.2282:0.117419:0.9796:32498:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.0235   ES:SE:LP:AF:SS:ID   0.099:0.2144:0.190912:0.0235:32498:rs3107975
1   55545   rs28396308  C   T   .   PASS    AF=0.2353   ES:SE:LP:AF:SS:ID   -0.0965:0.0423:1.64917:0.2353:32498:rs28396308
1   57292   rs201418760 C   T   .   PASS    AF=0.0216   ES:SE:LP:AF:SS:ID   0.0928:0.2232:0.169091:0.0216:32498:rs201418760
1   58814   rs114420996 G   A   .   PASS    AF=0.0952   ES:SE:LP:AF:SS:ID   -0.04:0.0646:0.271241:0.0952:32498:rs114420996
1   61920   rs62637820  G   A   .   PASS    AF=0.0264   ES:SE:LP:AF:SS:ID   -0.0275:0.1102:0.0952845:0.0264:32498:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.0202   ES:SE:LP:AF:SS:ID   0.137:0.1699:0.376854:0.0202:32498:rs200092917
1   64649   rs181431124 A   C   .   PASS    AF=0.0247   ES:SE:LP:AF:SS:ID   -0.0207:0.113:0.0682371:0.0247:32498:rs181431124
1   66219   rs181028663 A   T   .   PASS    AF=0.0176   ES:SE:LP:AF:SS:ID   -0.1281:0.1412:0.438541:0.0176:32498:rs181028663
1   68082   rs367789441 T   C   .   PASS    AF=0.0601   ES:SE:LP:AF:SS:ID   0.1647:0.0731:1.61368:0.0601:32498:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0443   ES:SE:LP:AF:SS:ID   -0.105:0.0807:0.713768:0.0443:32498:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0641   ES:SE:LP:AF:SS:ID   0.1263:0.0711:1.12125:0.0641:32498:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.7489   ES:SE:LP:AF:SS:ID   0.0912:0.0408:1.59244:0.7489:32498:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.0278   ES:SE:LP:AF:SS:ID   -0.0053:0.115:0.0163286:0.0278:32498:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.0278   ES:SE:LP:AF:SS:ID   -0.0053:0.115:0.0163286:0.0278:32498:rs13328684
1   76854   rs367666799 A   G   .   PASS    AF=0.066    ES:SE:LP:AF:SS:ID   -0.105:0.0709:0.857611:0.066:32498:rs367666799
1   82163   rs139113303 G   A   .   PASS    AF=0.0657   ES:SE:LP:AF:SS:ID   -0.1098:0.0711:0.912574:0.0657:32498:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0661   ES:SE:LP:AF:SS:ID   -0.1053:0.0709:0.861697:0.0661:32498:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.356    ES:SE:LP:AF:SS:ID   0.0069:0.0369:0.0693566:0.356:32498:rs201754587
1   86028   rs114608975 T   C   .   PASS    AF=0.0492   ES:SE:LP:AF:SS:ID   -0.0196:0.0823:0.0906045:0.0492:32498:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0666   ES:SE:LP:AF:SS:ID   -0.0958:0.0713:0.746904:0.0666:32498:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.1067   ES:SE:LP:AF:SS:ID   -0.1019:0.0605:1.03466:0.1067:32498:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.0135   ES:SE:LP:AF:SS:ID   0.3054:0.4346:0.316773:0.0135:32498:rs188486692
1   87360   rs180907504 C   T   .   PASS    AF=0.0196   ES:SE:LP:AF:SS:ID   0.035:0.1618:0.0814979:0.0196:32498:rs180907504
1   87409   rs139490478 C   T   .   PASS    AF=0.0682   ES:SE:LP:AF:SS:ID   -0.1066:0.0706:0.882729:0.0682:32498:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.2132   ES:SE:LP:AF:SS:ID   0.039:0.0418:0.454322:0.2132:32498:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.0596   ES:SE:LP:AF:SS:ID   0.1681:0.0736:1.65131:0.0596:32498:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.0588   ES:SE:LP:AF:SS:ID   0.1623:0.074:1.5496:0.0588:32498:rs143215837
1   88236   rs186918018 C   T   .   PASS    AF=0.0109   ES:SE:LP:AF:SS:ID   0.0094:0.2274:0.0144837:0.0109:32498:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.0594   ES:SE:LP:AF:SS:ID   0.136:0.0738:1.18329:0.0594:32498:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.0802   ES:SE:LP:AF:SS:ID   -0.0333:0.0677:0.205512:0.0802:32498:rs55700207
1   88710   rs186575039 C   G   .   PASS    AF=0.0681   ES:SE:LP:AF:SS:ID   -0.1068:0.0706:0.885389:0.0681:32498:rs186575039
1   89599   rs375955515 A   T   .   PASS    AF=0.0681   ES:SE:LP:AF:SS:ID   -0.1068:0.0706:0.885389:0.0681:32498:rs375955515
1   89946   rs138808727 A   T   .   PASS    AF=0.2308   ES:SE:LP:AF:SS:ID   0.0262:0.0413:0.27951:0.2308:32498:rs138808727
1   91190   rs143856811 G   A   .   PASS    AF=0.0697   ES:SE:LP:AF:SS:ID   -0.1278:0.0701:1.16602:0.0697:32498:rs143856811
1   91421   rs28619159  T   C   .   PASS    AF=0.0119   ES:SE:LP:AF:SS:ID   -0.2094:0.2274:0.44721:0.0119:32498:rs28619159
1   91515   rs376723915 A   C   .   PASS    AF=0.5542   ES:SE:LP:AF:SS:ID   0.0191:0.0353:0.230844:0.5542:32498:rs376723915
1   92633   rs149776517 C   T   .   PASS    AF=0.031    ES:SE:LP:AF:SS:ID   -0.051:0.0965:0.223807:0.031:32498:rs149776517
1   92858   rs147061536 G   T   .   PASS    AF=0.2388   ES:SE:LP:AF:SS:ID   0.0298:0.0409:0.331148:0.2388:32498:rs147061536
1   99671   rs146209971 A   T   .   PASS    AF=0.0107   ES:SE:LP:AF:SS:ID   -0.0203:0.2365:0.0307239:0.0107:32498:rs146209971
1   99687   rs139153227 C   T   .   PASS    AF=0.0561   ES:SE:LP:AF:SS:ID   0.1457:0.0751:1.28191:0.0561:32498:rs139153227
1   99719   rs183898652 C   T   .   PASS    AF=0.0107   ES:SE:LP:AF:SS:ID   -0.0265:0.2218:0.0434474:0.0107:32498:rs183898652
1   115729  rs199999500 GCACA   G   .   PASS    AF=0.0136   ES:SE:LP:AF:SS:ID   0.2957:0.1715:1.07207:0.0136:32498:rs199999500
1   115746  rs147538909 C   T   .   PASS    AF=0.0431   ES:SE:LP:AF:SS:ID   -0.154:0.0886:1.08486:0.0431:32498:rs147538909
1   129010  rs377161483 AATG    A   .   PASS    AF=0.5504   ES:SE:LP:AF:SS:ID   -0.0712:0.035:1.37748:0.5504:32498:rs377161483