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-982/ieu-a-982.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-982/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 16:22:05 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-982/ieu-a-982.vcf.gz ...
Read summary statistics for 9282363 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, 1170690 SNPs remain.
After merging with regression SNP LD, 1170690 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1345 (0.0148)
Lambda GC: 1.1144
Mean Chi^2: 1.1421
Intercept: 1.0267 (0.0079)
Ratio: 0.1879 (0.0556)
Analysis finished at Tue Feb  4 16:23:38 2020
Total time elapsed: 1.0m:32.59s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9825,
    "inflation_factor": 1.0276,
    "mean_EFFECT": -0.0001,
    "n": 44731,
    "n_snps": 9282363,
    "n_clumped_hits": 24,
    "n_p_sig": 1080,
    "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": 253400,
    "n_miss_AF_reference": 309158,
    "n_est": 38597.9902,
    "ratio_se_n": 0.9289,
    "mean_diff": 1.0939e-06,
    "ratio_diff": 0.0382,
    "sd_y_est1": 1.417,
    "sd_y_est2": 1.3163,
    "r2_sum1": 0.0446,
    "r2_sum2": 0.0222,
    "r2_sum3": 0.0257,
    "r2_sum4": 0.0257,
    "ldsc_nsnp_merge_refpanel_ld": 1170690,
    "ldsc_nsnp_merge_regression_ld": 1170690,
    "ldsc_observed_scale_h2_beta": 0.1345,
    "ldsc_observed_scale_h2_se": 0.0148,
    "ldsc_intercept_beta": 1.0267,
    "ldsc_intercept_se": 0.0079,
    "ldsc_lambda_gc": 1.1144,
    "ldsc_mean_chisq": 1.1421,
    "ldsc_ratio": 0.1879
}

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 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 57 0 9282361 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.741171e+00 5.840027e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.827971e+07 5.631421e+07 8.2800e+02 3.208554e+07 6.846187e+07 1.139365e+08 2.492391e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.273000e-04 3.214310e-02 -1.2700e+00 -1.211100e-02 -1.790000e-04 1.173400e-02 1.342360e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.454840e-02 1.993180e-02 1.9500e-04 1.028800e-02 1.610900e-02 3.250100e-02 5.770230e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.956376e-01 2.902627e-01 0.0000e+00 2.435337e-01 4.941366e-01 7.471779e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.881383e-01 2.921555e-01 0.0000e+00 2.324671e-01 4.838549e-01 7.413405e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 253400 0.9727009 NA NA NA NA NA 2.337870e-01 2.660649e-01 7.9600e-05 2.458230e-02 1.184570e-01 3.680990e-01 9.999200e-01 ▇▂▁▁▁
numeric AF_reference 309158 0.9666940 NA NA NA NA NA 2.344785e-01 2.643032e-01 0.0000e+00 1.936900e-02 1.279950e-01 3.694090e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 4.473100e+04 0.000000e+00 4.4731e+04 4.473100e+04 4.473100e+04 4.473100e+04 4.473100e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 51479 rs116400033 T A 0.004911 0.019236 0.8030900 0.7984894 0.175736 0.1281950 44731
1 52058 rs62637813 G C 0.020419 0.057827 0.7302137 0.7240098 NA NA 44731
1 54421 rs146477069 A G 0.031451 0.051528 0.5511172 0.5416186 NA NA 44731
1 54490 rs141149254 G A -0.004011 0.020008 0.8447751 0.8411132 0.125457 0.0960463 44731
1 54676 rs2462492 C T 0.047952 0.042411 0.2694728 0.2582024 NA NA 44731
1 54753 rs143174675 T G -0.057749 0.048486 0.2447113 0.2336360 NA NA 44731
1 55164 rs3091274 C A 0.001285 0.018672 0.9463910 0.9451332 0.960700 0.9233230 44731
1 55299 rs10399749 C T 0.016499 0.017334 0.3525462 0.3411838 NA NA 44731
1 55326 rs3107975 T C -0.035331 0.068901 0.6165254 0.6081058 0.028401 0.0459265 44731
1 58814 rs114420996 G A -0.060436 0.034647 0.0884525 0.0811006 0.101034 0.1090260 44731
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51227891 rs6010091 G A 0.006149 0.018749 0.7487365 0.7429388 0.4236280 0.4039540 44731
22 51229805 rs9616985 T C 0.012784 0.024161 0.6053367 0.5967242 0.0715195 0.0730831 44731
22 51229813 rs191731586 T C 0.001512 0.025681 0.9541349 0.9530507 0.0052506 0.0057907 44731
22 51229855 rs144549712 G A 0.025790 0.057232 0.6598831 0.6522620 0.1306280 0.1160140 44731
22 51234677 rs189571549 A C -0.011509 0.034063 0.7414195 0.7354582 0.0098648 0.0227636 44731
23 35747397 rs74987454 T C 0.142038 0.078800 0.0783394 0.0714648 NA NA 44731
23 50040891 rs192267219 C T -0.018269 0.088388 0.8400130 0.8362512 NA 0.0222517 44731
23 75822996 rs147134110 C T -0.016507 0.031351 0.6071192 0.5985254 0.0243437 0.0773510 44731
23 100784211 rs188350543 C A -0.015681 0.011143 0.1692949 0.1593529 0.7770880 0.6498010 44731
23 133445361 rs112934402 T C -0.115833 0.100743 0.2614442 0.2502316 0.0037391 NA 44731

bcf preview

1   51479   rs116400033 T   A   .   PASS    AF=0.175736 ES:SE:LP:AF:SS:ID   0.004911:0.019236:0.0952358:0.175736:44731:rs116400033
1   52058   rs62637813  G   C   .   PASS    .   ES:SE:LP:SS:ID  0.020419:0.057827:0.13655:44731:rs62637813
1   54421   rs146477069 A   G   .   PASS    .   ES:SE:LP:SS:ID  0.031451:0.051528:0.258756:44731:rs146477069
1   54490   rs141149254 G   A   .   PASS    AF=0.125457 ES:SE:LP:AF:SS:ID   -0.004011:0.020008:0.0732589:0.125457:44731:rs141149254
1   54676   rs2462492   C   T   .   PASS    .   ES:SE:LP:SS:ID  0.047952:0.042411:0.569485:44731:rs2462492
1   54753   rs143174675 T   G   .   PASS    .   ES:SE:LP:SS:ID  -0.057749:0.048486:0.611346:44731:rs143174675
1   55164   rs3091274   C   A   .   PASS    AF=0.9607   ES:SE:LP:AF:SS:ID   0.001285:0.018672:0.0239294:0.9607:44731:rs3091274
1   55299   rs10399749  C   T   .   PASS    .   ES:SE:LP:SS:ID  0.016499:0.017334:0.452784:44731:rs10399749
1   55326   rs3107975   T   C   .   PASS    AF=0.028401 ES:SE:LP:AF:SS:ID   -0.035331:0.068901:0.210049:0.028401:44731:rs3107975
1   58814   rs114420996 G   A   .   PASS    AF=0.101034 ES:SE:LP:AF:SS:ID   -0.060436:0.034647:1.05329:0.101034:44731:rs114420996
1   61987   rs76735897  A   G   .   PASS    .   ES:SE:LP:SS:ID  0.013263:0.016791:0.356095:44731:rs76735897
1   61989   rs77573425  G   C   .   PASS    .   ES:SE:LP:SS:ID  0.012347:0.016792:0.325403:44731:rs77573425
1   66162   rs62639105  A   T   .   PASS    .   ES:SE:LP:SS:ID  0.020242:0.017057:0.608289:44731:rs62639105
1   66507   rs12401368  T   A   .   PASS    .   ES:SE:LP:SS:ID  -0.017531:0.024781:0.31013:44731:rs12401368
1   73841   rs143773730 C   T   .   PASS    .   ES:SE:LP:SS:ID  0.044073:0.039691:0.555735:44731:rs143773730
1   77961   rs78385339  G   A   .   PASS    .   ES:SE:LP:SS:ID  0.065072:0.073157:0.414537:44731:rs78385339
1   79772   rs147215883 C   G   .   PASS    .   ES:SE:LP:SS:ID  -0.035839:0.033016:0.539007:44731:rs147215883
1   82163   rs139113303 G   A   .   PASS    AF=0.0603819    ES:SE:LP:AF:SS:ID   -0.091367:0.095912:0.453246:0.0603819:44731:rs139113303
1   82249   rs1851945   A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0194:0.026861:0.318216:44731:rs1851945
1   82303   rs3871776   T   C   .   PASS    .   ES:SE:LP:SS:ID  0.011094:0.032515:0.131378:44731:rs3871776
1   82316   rs4030305   A   C   .   PASS    .   ES:SE:LP:SS:ID  0.061821:0.054722:0.568881:44731:rs4030305
1   82609   rs149189449 C   G   .   PASS    AF=0.0604614    ES:SE:LP:AF:SS:ID   0.010659:0.035008:0.115665:0.0604614:44731:rs149189449
1   82676   rs185237834 T   G   .   PASS    .   ES:SE:LP:SS:ID  -0.019841:0.034215:0.243237:44731:rs185237834
1   82734   rs4030331   T   C   .   PASS    .   ES:SE:LP:SS:ID  -0.032103:0.022044:0.809921:44731:rs4030331
1   84002   rs28850140  G   A   .   PASS    .   ES:SE:LP:SS:ID  0.111616:0.040308:2.1638:44731:rs28850140
1   84010   rs186443818 G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.092391:0.095565:0.462118:44731:rs186443818
1   84244   rs191297051 A   C   .   PASS    .   ES:SE:LP:SS:ID  -0.017443:0.034171:0.208929:44731:rs191297051
1   85597   rs192472955 A   C   .   PASS    .   ES:SE:LP:SS:ID  0.012686:0.017349:0.323173:44731:rs192472955
1   86018   rs142878000 C   G   .   PASS    .   ES:SE:LP:SS:ID  -0.023955:0.032716:0.323712:44731:rs142878000
1   86028   rs114608975 T   C   .   PASS    AF=0.0540971    ES:SE:LP:AF:SS:ID   0.003034:0.02725:0.0393476:0.0540971:44731:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0630072    ES:SE:LP:AF:SS:ID   0.005445:0.027206:0.0731325:0.0630072:44731:rs116504101
1   86303   rs2949417   G   T   .   PASS    .   ES:SE:LP:SS:ID  -0.022184:0.032828:0.293051:44731:rs2949417
1   86331   rs115209712 A   G   .   PASS    AF=0.110183 ES:SE:LP:AF:SS:ID   -0.019003:0.032836:0.242634:0.110183:44731:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.00906921   ES:SE:LP:AF:SS:ID   0.044805:0.090942:0.200374:0.00906921:44731:rs188486692
1   87190   rs1524602   G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.043418:0.029811:0.809996:44731:rs1524602
1   87409   rs139490478 C   T   .   PASS    AF=0.0637232    ES:SE:LP:AF:SS:ID   -0.091827:0.099278:0.436124:0.0637232:44731:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.24463  ES:SE:LP:AF:SS:ID   -0.033078:0.030123:0.547444:0.24463:44731:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.0574383    ES:SE:LP:AF:SS:ID   0.010598:0.032771:0.123711:0.0574383:44731:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.0560064    ES:SE:LP:AF:SS:ID   0.044709:0.040623:0.549123:0.0560064:44731:rs143215837
1   88188   rs148331237 C   A   .   PASS    AF=0.00445505   ES:SE:LP:AF:SS:ID   -0.005295:0.087968:0.0208597:0.00445505:44731:rs148331237
1   88236   rs186918018 C   T   .   PASS    AF=0.00731901   ES:SE:LP:AF:SS:ID   -0.055716:0.093503:0.251335:0.00731901:44731:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.0566428    ES:SE:LP:AF:SS:ID   0.01737:0.032384:0.221564:0.0566428:44731:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.0881464    ES:SE:LP:AF:SS:ID   -0.048467:0.038402:0.662144:0.0881464:44731:rs55700207
1   88370   rs185487977 G   A   .   PASS    AF=0.00238663   ES:SE:LP:AF:SS:ID   -0.14133:0.137079:0.503135:0.00238663:44731:rs185487977
1   88710   rs186575039 C   G   .   PASS    AF=0.0631663    ES:SE:LP:AF:SS:ID   -0.078864:0.099099:0.359488:0.0631663:44731:rs186575039
1   89946   rs138808727 A   T   .   PASS    AF=0.170485 ES:SE:LP:AF:SS:ID   0.006396:0.019205:0.127845:0.170485:44731:rs138808727
1   91190   rs143856811 G   A   .   PASS    AF=0.0647574    ES:SE:LP:AF:SS:ID   -0.091054:0.091034:0.483305:0.0647574:44731:rs143856811
1   92633   rs149776517 C   T   .   PASS    AF=0.0186953    ES:SE:LP:AF:SS:ID   0.038471:0.132255:0.109947:0.0186953:44731:rs149776517
1   92858   rs147061536 G   T   .   PASS    AF=0.183055 ES:SE:LP:AF:SS:ID   0.009949:0.019255:0.211939:0.183055:44731:rs147061536
1   98929   rs12184306  A   G   .   PASS    .   ES:SE:LP:SS:ID  0.015877:0.017606:0.421981:44731:rs12184306