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-1120/ieu-a-1120.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-1120/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 08:40:59 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1120/ieu-a-1120.vcf.gz ...
Read summary statistics for 15594303 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, 1218951 SNPs remain.
After merging with regression SNP LD, 1218951 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0469 (0.0106)
Lambda GC: 1.059
Mean Chi^2: 1.0903
Intercept: 1.0298 (0.0067)
Ratio: 0.3306 (0.0741)
Analysis finished at Wed Feb  5 08:43:36 2020
Total time elapsed: 2.0m:37.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9605,
    "inflation_factor": 1.0537,
    "mean_EFFECT": -0.1282,
    "n": 66450,
    "n_snps": 15594303,
    "n_clumped_hits": 12,
    "n_p_sig": 3914,
    "n_mono": 0,
    "n_ns": 782265,
    "n_mac": 223088,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 7260,
    "n_miss_AF_reference": 161735,
    "n_est": 64305.6604,
    "ratio_se_n": 0.9837,
    "mean_diff": 0.1425,
    "ratio_diff": 2.4471,
    "sd_y_est1": 2.6719,
    "sd_y_est2": 2.6285,
    "r2_sum1": 0.0706,
    "r2_sum2": 0.0099,
    "r2_sum3": 0.0102,
    "r2_sum4": 0.0123,
    "ldsc_nsnp_merge_refpanel_ld": 1218951,
    "ldsc_nsnp_merge_regression_ld": 1218951,
    "ldsc_observed_scale_h2_beta": 0.0469,
    "ldsc_observed_scale_h2_se": 0.0106,
    "ldsc_intercept_beta": 1.0298,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.059,
    "ldsc_mean_chisq": 1.0903,
    "ldsc_ratio": 0.33
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 TRUE
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 47 0 15594301 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 101 0 37641 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 105 0 18079 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.889041e+00 6.249766e+00 1.000e+00 4.000000e+00 7.000000e+00 1.400000e+01 2.400000e+01 ▇▆▂▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.931733e+07 5.681581e+07 5.600e+01 3.252683e+07 6.964889e+07 1.158265e+08 2.492402e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.282264e-01 2.071043e+00 -2.042e+01 -3.371000e-02 -5.100000e-05 3.323000e-02 2.050000e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.777863e-01 4.201276e+00 2.357e-04 1.863000e-02 5.439000e-02 2.116000e-01 1.000000e+03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.918182e-01 2.906958e-01 0.000e+00 2.382001e-01 4.886996e-01 7.440001e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.918352e-01 2.906877e-01 0.000e+00 2.382351e-01 4.887550e-01 7.439865e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 7260 0.9995344 NA NA NA NA NA 1.536351e-01 2.449139e-01 0.000e+00 2.002000e-03 2.003000e-02 2.066000e-01 9.999980e-01 ▇▁▁▁▁
numeric AF_reference 161735 0.9896286 NA NA NA NA NA 1.533582e-01 2.324300e-01 0.000e+00 2.595800e-03 3.075080e-02 2.126600e-01 1.000000e+00 ▇▁▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.645000e+04 0.000000e+00 6.645e+04 6.645000e+04 6.645000e+04 6.645000e+04 6.645000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C 0.01319 0.09657 0.8913000 0.8913589 0.991000 0.9930110 66450
1 14933 rs199856693 G A 0.07059 0.06168 0.2523998 0.2524349 0.047970 0.0283546 66450
1 15774 rs374029747 G A -0.01642 0.15370 0.9148999 0.9149227 0.006579 0.0119808 66450
1 16949 rs199745162 A C -0.11230 0.08532 0.1880001 0.1880998 0.016750 0.0139776 66450
1 51479 rs116400033 T A 0.01736 0.02641 0.5108001 0.5109708 0.232100 0.1281950 66450
1 52185 rs201374420 TTAA T 0.18510 1.04300 0.8592001 0.8591401 0.005882 0.0053914 66450
1 54353 rs140052487 C A -0.84400 0.41210 0.0405201 0.0405554 0.001339 0.0089856 66450
1 54490 rs141149254 G A 0.01101 0.02973 0.7110007 0.7111344 0.166100 0.0960463 66450
1 55164 rs3091274 C A 0.03126 0.08842 0.7237007 0.7236837 0.980700 0.9233230 66450
1 55326 rs3107975 T C 0.06836 0.17160 0.6903002 0.6903587 0.028260 0.0459265 66450
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154925895 rs538470 C T -0.012870 0.01818 0.4790005 0.4789944 0.252700 0.3634440 66450
23 154926376 rs116490668 C T -0.178000 0.30630 0.5612004 0.5611531 0.001859 0.0349669 66450
23 154926843 rs192521690 T C 0.342200 0.25790 0.1846001 0.1845514 0.002532 0.0007947 66450
23 154927185 rs185685661 T C -0.011170 0.03071 0.7160000 0.7160632 0.139300 0.1796030 66450
23 154927199 rs645904 C T -0.011640 0.01756 0.5074999 0.5074137 0.248000 0.3674170 66450
23 154927581 rs644138 G A -0.013300 0.01716 0.4384005 0.4383052 0.299900 0.4635760 66450
23 154929412 rs557132 C T -0.009855 0.01758 0.5750995 0.5750837 0.250400 0.3568210 66450
23 154929952 rs4012982 CAA C -0.010750 0.01759 0.5412003 0.5411051 0.250900 0.3165560 66450
23 154930230 rs781880 A G -0.011040 0.01769 0.5327004 0.5325741 0.249000 0.3618540 66450
24 13537468 rs7203107 A G 0.096720 0.09555 0.3114003 0.3114210 0.985590 NA 66450

bcf preview

1   10616   rs376342519 CCGCCGTTGCAAAGGCGCGCCG  C   .   PASS    AF=0.991    ES:SE:LP:AF:SS:ID   0.01319:0.09657:0.0499761:0.991:66450:rs376342519
1   14933   rs199856693 G   A   .   PASS    AF=0.04797  ES:SE:LP:AF:SS:ID   0.07059:0.06168:0.597911:0.04797:66450:rs199856693
1   15774   rs374029747 G   A   .   PASS    AF=0.006579 ES:SE:LP:AF:SS:ID   -0.01642:0.1537:0.0386264:0.006579:66450:rs374029747
1   16949   rs199745162 A   C   .   PASS    AF=0.01675  ES:SE:LP:AF:SS:ID   -0.1123:0.08532:0.725842:0.01675:66450:rs199745162
1   51479   rs116400033 T   A   .   PASS    AF=0.2321   ES:SE:LP:AF:SS:ID   0.01736:0.02641:0.291749:0.2321:66450:rs116400033
1   52185   rs201374420 TTAA    T   .   PASS    AF=0.005882 ES:SE:LP:AF:SS:ID   0.1851:1.043:0.0659057:0.005882:66450:rs201374420
1   54353   rs140052487 C   A   .   PASS    AF=0.001339 ES:SE:LP:AF:SS:ID   -0.844:0.4121:1.39233:0.001339:66450:rs140052487
1   54490   rs141149254 G   A   .   PASS    AF=0.1661   ES:SE:LP:AF:SS:ID   0.01101:0.02973:0.14813:0.1661:66450:rs141149254
1   55164   rs3091274   C   A   .   PASS    AF=0.9807   ES:SE:LP:AF:SS:ID   0.03126:0.08842:0.140441:0.9807:66450:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.02826  ES:SE:LP:AF:SS:ID   0.06836:0.1716:0.160962:0.02826:66450:rs3107975
1   55545   rs28396308  C   T   .   PASS    AF=0.2248   ES:SE:LP:AF:SS:ID   0.006546:0.02928:0.0845474:0.2248:66450:rs28396308
1   57183   rs368339209 A   G   .   PASS    AF=0.0007041    ES:SE:LP:AF:SS:ID   -0.5857:0.5469:0.546376:0.0007041:66450:rs368339209
1   57292   rs201418760 C   T   .   PASS    AF=0.02393  ES:SE:LP:AF:SS:ID   0.0395:0.0838:0.195588:0.02393:66450:rs201418760
1   58814   rs114420996 G   A   .   PASS    AF=0.1003   ES:SE:LP:AF:SS:ID   -0.002272:0.04159:0.0193604:0.1003:66450:rs114420996
1   61543   rs201849102 T   C   .   PASS    AF=0.0003079    ES:SE:LP:AF:SS:ID   -1.98:1.334:0.860751:0.0003079:66450:rs201849102
1   61743   rs184286948 G   C   .   PASS    AF=0.009155 ES:SE:LP:AF:SS:ID   -0.02803:0.1257:0.0842837:0.009155:66450:rs184286948
1   61920   rs62637820  G   A   .   PASS    AF=0.02945  ES:SE:LP:AF:SS:ID   0.001763:0.07109:0.0086853:0.02945:66450:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.0207   ES:SE:LP:AF:SS:ID   0.1939:0.09029:1.49771:0.0207:66450:rs200092917
1   64649   rs181431124 A   C   .   PASS    AF=0.02715  ES:SE:LP:AF:SS:ID   0.03538:0.0774:0.188693:0.02715:66450:rs181431124
1   66219   rs181028663 A   T   .   PASS    AF=0.01624  ES:SE:LP:AF:SS:ID   0.1028:0.09575:0.548521:0.01624:66450:rs181028663
1   68082   rs367789441 T   C   .   PASS    AF=0.06526  ES:SE:LP:AF:SS:ID   -0.03789:0.04589:0.388171:0.06526:66450:rs367789441
1   68596   rs372212855 T   G   .   PASS    AF=0.003797 ES:SE:LP:AF:SS:ID   -0.2369:0.179:0.731422:0.003797:66450:rs372212855
1   69428   rs140739101 T   G   .   PASS    AF=0.04215  ES:SE:LP:AF:SS:ID   0.01891:0.05709:0.130534:0.04215:66450:rs140739101
1   69534   rs190717287 T   C   .   PASS    AF=0.0003164    ES:SE:LP:AF:SS:ID   -0.9178:0.6698:0.768021:0.0003164:66450:rs190717287
1   69761   rs200505207 A   T   .   PASS    AF=0.06821  ES:SE:LP:AF:SS:ID   -0.03183:0.0446:0.322849:0.06821:66450:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.7661   ES:SE:LP:AF:SS:ID   -0.007436:0.02873:0.0991961:0.7661:66450:rs200676709
1   72297   rs200651397 G   GTAT    .   PASS    AF=0.006341 ES:SE:LP:AF:SS:ID   -0.1236:0.1641:0.345535:0.006341:66450:rs200651397
1   74790   rs13328700  C   G   .   PASS    AF=0.03421  ES:SE:LP:AF:SS:ID   0.1011:0.05807:1.08847:0.03421:66450:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.03421  ES:SE:LP:AF:SS:ID   0.1011:0.05807:1.08847:0.03421:66450:rs13328684
1   76854   rs367666799 A   G   .   PASS    AF=0.06856  ES:SE:LP:AF:SS:ID   0.0278:0.04902:0.243668:0.06856:66450:rs367666799
1   78942   rs372315362 C   G   .   PASS    AF=0.01116  ES:SE:LP:AF:SS:ID   -1.268:0.8444:0.875822:0.01116:66450:rs372315362
1   80454   rs144226842 G   C   .   PASS    AF=0.0004404    ES:SE:LP:AF:SS:ID   1.373:3.709:0.148008:0.0004404:66450:rs144226842
1   81590   rs202072409 AC  A   .   PASS    AF=0.004955 ES:SE:LP:AF:SS:ID   0.3867:0.9459:0.16577:0.004955:66450:rs202072409
1   82163   rs139113303 G   A   .   PASS    AF=0.06791  ES:SE:LP:AF:SS:ID   0.03017:0.04935:0.266803:0.06791:66450:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.06818  ES:SE:LP:AF:SS:ID   0.03024:0.04924:0.268331:0.06818:66450:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.3501   ES:SE:LP:AF:SS:ID   0.02772:0.02635:0.533429:0.3501:66450:rs201754587
1   84139   rs183605470 A   T   .   PASS    AF=0.02132  ES:SE:LP:AF:SS:ID   -0.1193:0.09651:0.664542:0.02132:66450:rs183605470
1   86028   rs114608975 T   C   .   PASS    AF=0.04742  ES:SE:LP:AF:SS:ID   0.005404:0.05564:0.0349865:0.04742:66450:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.06995  ES:SE:LP:AF:SS:ID   0.03733:0.04884:0.352031:0.06995:66450:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.1018   ES:SE:LP:AF:SS:ID   0.04376:0.04092:0.54546:0.1018:66450:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.00763  ES:SE:LP:AF:SS:ID   0.1122:0.1288:0.416008:0.00763:66450:rs188486692
1   87360   rs180907504 C   T   .   PASS    AF=0.01853  ES:SE:LP:AF:SS:ID   0.1208:0.09317:0.710188:0.01853:66450:rs180907504
1   87409   rs139490478 C   T   .   PASS    AF=0.07088  ES:SE:LP:AF:SS:ID   0.02605:0.04844:0.228633:0.07088:66450:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.2022   ES:SE:LP:AF:SS:ID   0.0112:0.02815:0.160648:0.2022:66450:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.06423  ES:SE:LP:AF:SS:ID   -0.05169:0.04655:0.573651:0.06423:66450:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.06377  ES:SE:LP:AF:SS:ID   -0.04602:0.04678:0.487716:0.06377:66450:rs143215837
1   88188   rs148331237 C   A   .   PASS    AF=0.007142 ES:SE:LP:AF:SS:ID   -0.09863:0.1286:0.353498:0.007142:66450:rs148331237
1   88236   rs186918018 C   T   .   PASS    AF=0.01279  ES:SE:LP:AF:SS:ID   -0.09279:0.2077:0.183692:0.01279:66450:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.06376  ES:SE:LP:AF:SS:ID   -0.04851:0.04697:0.520425:0.06376:66450:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.08209  ES:SE:LP:AF:SS:ID   -0.03639:0.04577:0.370081:0.08209:66450:rs55700207