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-1122/ieu-a-1122.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-1122/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 09:21:21 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1122/ieu-a-1122.vcf.gz ...
Read summary statistics for 15127392 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, 1218945 SNPs remain.
After merging with regression SNP LD, 1218945 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0102 (0.0109)
Lambda GC: 1.0112
Mean Chi^2: 1.0097
Intercept: 1.0182 (0.0063)
Ratio: 1.868 (0.6486)
Analysis finished at Wed Feb  5 09:23:19 2020
Total time elapsed: 1.0m:57.84s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.96,
    "inflation_factor": 1.0302,
    "mean_EFFECT": -1.0754,
    "n": 41953,
    "n_snps": 15127392,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 773315,
    "n_mac": 234663,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 933,
    "n_miss_AF_reference": 159056,
    "n_est": 40532.4676,
    "ratio_se_n": 0.9829,
    "mean_diff": 1.0674,
    "ratio_diff": 7.851,
    "sd_y_est1": 7.6096,
    "sd_y_est2": 7.4797,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1218945,
    "ldsc_nsnp_merge_regression_ld": 1218945,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0182,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0112,
    "ldsc_mean_chisq": 1.0097,
    "ldsc_ratio": 1.8763
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
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 TRUE
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 15127390 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 101 0 37280 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 105 0 18038 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.900123e+00 6.258764e+00 1.0000e+00 4.000000e+00 7.000000e+00 1.400000e+01 2.400000e+01 ▇▆▂▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.931153e+07 5.683653e+07 8.2800e+02 3.250349e+07 6.964507e+07 1.158374e+08 2.492402e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.075389e+00 4.341607e+00 -2.0390e+01 -1.436000e-01 -6.664000e-03 9.374000e-02 2.042000e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.122469e+00 9.342773e+00 3.3290e-03 6.594000e-02 1.818000e-01 7.216000e-01 1.000000e+03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.954679e-01 2.876082e-01 1.0000e-07 2.466999e-01 4.935998e-01 7.428994e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.956045e-01 2.875606e-01 0.0000e+00 2.469901e-01 4.937582e-01 7.429639e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 933 0.9999383 NA NA NA NA NA 1.582410e-01 2.470506e-01 0.0000e+00 2.482000e-03 2.325000e-02 2.178000e-01 9.999840e-01 ▇▁▁▁▁
numeric AF_reference 159056 0.9894856 NA NA NA NA NA 1.579995e-01 2.343603e-01 0.0000e+00 2.995200e-03 3.574280e-02 2.228430e-01 1.000000e+00 ▇▁▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 4.195300e+04 0.000000e+00 4.1953e+04 4.195300e+04 4.195300e+04 4.195300e+04 4.195300e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C -0.094280 0.35760 0.7921000 0.7920523 0.991000 0.9930110 41953
1 14933 rs199856693 G A -0.040750 0.22150 0.8540001 0.8540347 0.047970 0.0283546 41953
1 15774 rs374029747 G A 1.228000 0.43660 0.0048940 0.0049136 0.006579 0.0119808 41953
1 16949 rs199745162 A C -0.054860 0.27510 0.8419000 0.8419355 0.016750 0.0139776 41953
1 51479 rs116400033 T A 0.006719 0.09482 0.9435000 0.9435087 0.232100 0.1281950 41953
1 52185 rs201374420 TTAA T -20.140000 18.02000 0.2638001 0.2637178 0.005882 0.0053914 41953
1 54353 rs140052487 C A -1.301000 1.37100 0.3426999 0.3426499 0.001339 0.0089856 41953
1 54490 rs141149254 G A 0.045750 0.10530 0.6639999 0.6639450 0.166100 0.0960463 41953
1 55164 rs3091274 C A -0.048260 0.31160 0.8769001 0.8769175 0.980700 0.9233230 41953
1 55326 rs3107975 T C -0.251600 0.79070 0.7503001 0.7503339 0.028260 0.0459265 41953
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154925045 rs509981 C T -0.001886 0.06075 0.9752000 0.9752334 0.250000 0.3634440 41953
23 154925895 rs538470 C T 0.014880 0.06281 0.8127001 0.8127305 0.252700 0.3634440 41953
23 154926376 rs116490668 C T -1.398000 1.13900 0.2197000 0.2196751 0.001859 0.0349669 41953
23 154927185 rs185685661 T C 0.044280 0.10430 0.6710996 0.6711687 0.139300 0.1796030 41953
23 154927199 rs645904 C T 0.004081 0.06078 0.9465000 0.9464672 0.248000 0.3674170 41953
23 154927581 rs644138 G A 0.019570 0.05914 0.7406994 0.7407127 0.299900 0.4635760 41953
23 154929412 rs557132 C T 0.004416 0.06082 0.9421000 0.9421183 0.250400 0.3568210 41953
23 154929952 rs4012982 CAA C 0.003975 0.06089 0.9478999 0.9479497 0.250900 0.3165560 41953
23 154930230 rs781880 A G 0.006190 0.06114 0.9194000 0.9193575 0.249000 0.3618540 41953
24 13537468 rs7203107 A G -0.112800 0.34520 0.7437997 0.7438441 0.985590 NA 41953

bcf preview

1   10616   rs376342519 CCGCCGTTGCAAAGGCGCGCCG  C   .   PASS    AF=0.991    ES:SE:LP:AF:SS:ID   -0.09428:0.3576:0.10122:0.991:41953:rs376342519
1   14933   rs199856693 G   A   .   PASS    AF=0.04797  ES:SE:LP:AF:SS:ID   -0.04075:0.2215:0.0685421:0.04797:41953:rs199856693
1   15774   rs374029747 G   A   .   PASS    AF=0.006579 ES:SE:LP:AF:SS:ID   1.228:0.4366:2.31034:0.006579:41953:rs374029747
1   16949   rs199745162 A   C   .   PASS    AF=0.01675  ES:SE:LP:AF:SS:ID   -0.05486:0.2751:0.0747395:0.01675:41953:rs199745162
1   51479   rs116400033 T   A   .   PASS    AF=0.2321   ES:SE:LP:AF:SS:ID   0.006719:0.09482:0.0252581:0.2321:41953:rs116400033
1   52185   rs201374420 TTAA    T   .   PASS    AF=0.005882 ES:SE:LP:AF:SS:ID   -20.14:18.02:0.578725:0.005882:41953:rs201374420
1   54353   rs140052487 C   A   .   PASS    AF=0.001339 ES:SE:LP:AF:SS:ID   -1.301:1.371:0.465086:0.001339:41953:rs140052487
1   54490   rs141149254 G   A   .   PASS    AF=0.1661   ES:SE:LP:AF:SS:ID   0.04575:0.1053:0.177832:0.1661:41953:rs141149254
1   55164   rs3091274   C   A   .   PASS    AF=0.9807   ES:SE:LP:AF:SS:ID   -0.04826:0.3116:0.0570499:0.9807:41953:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.02826  ES:SE:LP:AF:SS:ID   -0.2516:0.7907:0.124765:0.02826:41953:rs3107975
1   55545   rs28396308  C   T   .   PASS    AF=0.2248   ES:SE:LP:AF:SS:ID   -0.03471:0.1017:0.135015:0.2248:41953:rs28396308
1   57183   rs368339209 A   G   .   PASS    AF=0.0007041    ES:SE:LP:AF:SS:ID   0.5251:1.369:0.154034:0.0007041:41953:rs368339209
1   57292   rs201418760 C   T   .   PASS    AF=0.02393  ES:SE:LP:AF:SS:ID   -0.2584:0.7839:0.129772:0.02393:41953:rs201418760
1   58814   rs114420996 G   A   .   PASS    AF=0.1003   ES:SE:LP:AF:SS:ID   0.1746:0.1406:0.668978:0.1003:41953:rs114420996
1   61543   rs201849102 T   C   .   PASS    AF=0.0003079    ES:SE:LP:AF:SS:ID   -3.01:9.477:0.124476:0.0003079:41953:rs201849102
1   61743   rs184286948 G   C   .   PASS    AF=0.009155 ES:SE:LP:AF:SS:ID   0.3155:0.4235:0.34075:0.009155:41953:rs184286948
1   61920   rs62637820  G   A   .   PASS    AF=0.02945  ES:SE:LP:AF:SS:ID   0.04708:0.2482:0.0708366:0.02945:41953:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.0207   ES:SE:LP:AF:SS:ID   0.2988:0.3068:0.481354:0.0207:41953:rs200092917
1   64649   rs181431124 A   C   .   PASS    AF=0.02715  ES:SE:LP:AF:SS:ID   0.1569:0.2678:0.253366:0.02715:41953:rs181431124
1   66219   rs181028663 A   T   .   PASS    AF=0.01624  ES:SE:LP:AF:SS:ID   -0.1009:0.3367:0.116623:0.01624:41953:rs181028663
1   68082   rs367789441 T   C   .   PASS    AF=0.06526  ES:SE:LP:AF:SS:ID   0.04371:0.1623:0.103639:0.06526:41953:rs367789441
1   68596   rs372212855 T   G   .   PASS    AF=0.003797 ES:SE:LP:AF:SS:ID   0.06845:0.578:0.0430156:0.003797:41953:rs372212855
1   69428   rs140739101 T   G   .   PASS    AF=0.04215  ES:SE:LP:AF:SS:ID   -0.1266:0.2048:0.270592:0.04215:41953:rs140739101
1   69534   rs190717287 T   C   .   PASS    AF=0.0003164    ES:SE:LP:AF:SS:ID   -15.35:9.365:0.995249:0.0003164:41953:rs190717287
1   69761   rs200505207 A   T   .   PASS    AF=0.06821  ES:SE:LP:AF:SS:ID   0.02274:0.1581:0.0527624:0.06821:41953:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.7661   ES:SE:LP:AF:SS:ID   0.03708:0.1014:0.145937:0.7661:41953:rs200676709
1   72297   rs200651397 G   GTAT    .   PASS    AF=0.006341 ES:SE:LP:AF:SS:ID   0.5414:0.5127:0.536107:0.006341:41953:rs200651397
1   74790   rs13328700  C   G   .   PASS    AF=0.03421  ES:SE:LP:AF:SS:ID   0.1095:0.2036:0.228633:0.03421:41953:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.03421  ES:SE:LP:AF:SS:ID   0.1095:0.2036:0.228633:0.03421:41953:rs13328684
1   76854   rs367666799 A   G   .   PASS    AF=0.06856  ES:SE:LP:AF:SS:ID   0.03373:0.1649:0.0768078:0.06856:41953:rs367666799
1   78942   rs372315362 C   G   .   PASS    AF=0.01116  ES:SE:LP:AF:SS:ID   2.963:1.602:1.19206:0.01116:41953:rs372315362
1   82163   rs139113303 G   A   .   PASS    AF=0.06791  ES:SE:LP:AF:SS:ID   0.04406:0.1661:0.101878:0.06791:41953:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.06818  ES:SE:LP:AF:SS:ID   0.05118:0.1653:0.121019:0.06818:41953:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.3501   ES:SE:LP:AF:SS:ID   0.06681:0.09243:0.328087:0.3501:41953:rs201754587
1   84139   rs183605470 A   T   .   PASS    AF=0.02132  ES:SE:LP:AF:SS:ID   0.7039:0.2966:1.7535:0.02132:41953:rs183605470
1   86028   rs114608975 T   C   .   PASS    AF=0.04742  ES:SE:LP:AF:SS:ID   0.1982:0.2034:0.481749:0.04742:41953:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.06995  ES:SE:LP:AF:SS:ID   -0.01013:0.1769:0.0203151:0.06995:41953:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.1018   ES:SE:LP:AF:SS:ID   -0.1632:0.1488:0.564156:0.1018:41953:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.00763  ES:SE:LP:AF:SS:ID   0.03421:0.4785:0.0254883:0.00763:41953:rs188486692
1   87360   rs180907504 C   T   .   PASS    AF=0.01853  ES:SE:LP:AF:SS:ID   0.3768:0.2924:0.704433:0.01853:41953:rs180907504
1   87409   rs139490478 C   T   .   PASS    AF=0.07088  ES:SE:LP:AF:SS:ID   -0.03709:0.1754:0.0796158:0.07088:41953:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.2022   ES:SE:LP:AF:SS:ID   -0.004454:0.09808:0.0160131:0.2022:41953:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.06423  ES:SE:LP:AF:SS:ID   0.02313:0.1657:0.0510982:0.06423:41953:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.06377  ES:SE:LP:AF:SS:ID   0.03906:0.166:0.089429:0.06377:41953:rs143215837
1   88188   rs148331237 C   A   .   PASS    AF=0.007142 ES:SE:LP:AF:SS:ID   0.08693:0.4489:0.072373:0.007142:41953:rs148331237
1   88236   rs186918018 C   T   .   PASS    AF=0.01279  ES:SE:LP:AF:SS:ID   0.07571:0.8704:0.0311903:0.01279:41953:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.06376  ES:SE:LP:AF:SS:ID   0.07149:0.1661:0.175874:0.06376:41953:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.08209  ES:SE:LP:AF:SS:ID   0.2214:0.1535:0.826231:0.08209:41953:rs55700207
1   88710   rs186575039 C   G   .   PASS    AF=0.07086  ES:SE:LP:AF:SS:ID   -0.03729:0.1754:0.0800855:0.07086:41953:rs186575039
1   89599   rs375955515 A   T   .   PASS    AF=0.07086  ES:SE:LP:AF:SS:ID   -0.03729:0.1754:0.0800855:0.07086:41953:rs375955515