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-1132/ieu-a-1132.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-1132/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 09:23:33 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1132/ieu-a-1132.vcf.gz ...
Read summary statistics for 10179532 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, 1220208 SNPs remain.
After merging with regression SNP LD, 1220208 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1387 (0.0141)
Lambda GC: 1.1614
Mean Chi^2: 1.2678
Intercept: 1.0443 (0.0084)
Ratio: 0.1654 (0.0314)
Analysis finished at Wed Feb  5 09:25:11 2020
Total time elapsed: 1.0m:37.64s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9496,
    "inflation_factor": 1.1214,
    "mean_EFFECT": -0.0001,
    "n": 83691,
    "n_snps": 10179532,
    "n_clumped_hits": 58,
    "n_p_sig": 4882,
    "n_mono": 0,
    "n_ns": 620064,
    "n_mac": 322,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 112,
    "n_miss_AF_reference": 131545,
    "n_est": 81017.3514,
    "ratio_se_n": 0.9839,
    "mean_diff": 0.0003,
    "ratio_diff": 1.5049,
    "sd_y_est1": 2.1315,
    "sd_y_est2": 2.0972,
    "r2_sum1": 0.2384,
    "r2_sum2": 0.0525,
    "r2_sum3": 0.0542,
    "r2_sum4": 0.0561,
    "ldsc_nsnp_merge_refpanel_ld": 1220208,
    "ldsc_nsnp_merge_regression_ld": 1220208,
    "ldsc_observed_scale_h2_beta": 0.1387,
    "ldsc_observed_scale_h2_se": 0.0141,
    "ldsc_intercept_beta": 1.0443,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.1614,
    "ldsc_mean_chisq": 1.2678,
    "ldsc_ratio": 0.1654
}
 

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 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 47 0 10179530 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 99 0 30504 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 103 0 16148 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.958649e+00 6.304321e+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 7.911759e+07 5.683102e+07 8.28000e+02 3.228369e+07 6.944316e+07 1.156278e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -5.730000e-05 8.814740e-02 -1.68745e+01 -1.417000e-02 -1.500000e-04 1.386000e-02 1.780230e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.009710e-02 4.315011e+00 1.00000e-02 1.174000e-02 1.783000e-02 3.828000e-02 9.999500e+02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.809911e-01 2.943232e-01 0.00000e+00 2.215001e-01 4.750704e-01 7.362105e-01 1.000000e+00 ▇▇▇▇▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.809911e-01 2.943232e-01 0.00000e+00 2.215053e-01 4.750505e-01 7.362034e-01 1.000000e+00 ▇▇▇▇▆
numeric AF 112 0.9999890 NA NA NA NA NA 2.290606e-01 2.643845e-01 5.30000e-06 2.147150e-02 1.094490e-01 3.656260e-01 9.999890e-01 ▇▂▁▁▁
numeric AF_reference 131545 0.9870775 NA NA NA NA NA 2.273201e-01 2.511927e-01 1.99700e-04 2.436100e-02 1.261980e-01 3.578270e-01 9.996010e-01 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.369100e+04 0.000000e+00 8.36910e+04 8.369100e+04 8.369100e+04 8.369100e+04 8.369100e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C -0.04371 0.06455 0.4982703 0.4983111 0.9925440 0.9930110 83691
1 14933 rs199856693 G A 0.01032 0.04386 0.8139799 0.8139805 0.0404558 0.0283546 83691
1 15774 rs374029747 G A -0.20865 0.10505 0.0470165 0.0470114 0.0069306 0.0119808 83691
1 16949 rs199745162 A C -0.04900 0.05894 0.4057803 0.4057737 0.0196591 0.0139776 83691
1 51479 rs116400033 T A -0.01210 0.01981 0.5413797 0.5413303 0.2356130 0.1281950 83691
1 52185 rs201374420 TTAA T -0.17699 0.16476 0.2827203 0.2827200 0.0037120 0.0053914 83691
1 54490 rs141149254 G A -0.01570 0.02208 0.4768799 0.4770528 0.1739770 0.0960463 83691
1 55164 rs3091274 C A 0.10276 0.07024 0.1434399 0.1434717 0.9829230 0.9233230 83691
1 55326 rs3107975 T C 0.08421 0.06548 0.1984002 0.1984286 0.0198551 0.0459265 83691
1 55545 rs28396308 C T -0.00070 0.02026 0.9725401 0.9724379 0.2294300 0.2392170 83691
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154925045 rs509981 C T -0.00232 0.01183 0.8444000 0.8445228 0.238955 0.3634440 83691
23 154925895 rs538470 C T -0.00104 0.01188 0.9304701 0.9302406 0.246312 0.3634440 83691
23 154927185 rs185685661 T C 0.01855 0.02200 0.3991499 0.3991268 0.111979 0.1796030 83691
23 154927199 rs645904 C T -0.00195 0.01184 0.8694099 0.8691833 0.239551 0.3674170 83691
23 154927581 rs644138 G A -0.00284 0.01141 0.8034601 0.8034347 0.286904 0.4635760 83691
23 154928151 rs144607509 C T -0.01415 0.06153 0.8180800 0.8181158 0.021457 0.0084768 83691
23 154929412 rs557132 C T -0.00229 0.01184 0.8463800 0.8466362 0.238374 0.3568210 83691
23 154929952 rs4012982 CAA C 0.01146 0.01746 0.5117502 0.5115942 0.190981 0.3165560 83691
23 154930230 rs781880 A G -0.00246 0.01185 0.8355499 0.8355453 0.238265 0.3618540 83691
24 13537468 rs7203107 A G -0.08727 0.07645 0.2536699 0.2536493 0.991260 NA 83691

bcf preview

1   10616   rs376342519 CCGCCGTTGCAAAGGCGCGCCG  C   .   PASS    AF=0.992544 ES:SE:LP:AF:SS:ID   -0.04371:0.06455:0.302535:0.992544:83691:rs376342519
1   14933   rs199856693 G   A   .   PASS    AF=0.0404558    ES:SE:LP:AF:SS:ID   0.01032:0.04386:0.0893863:0.0404558:83691:rs199856693
1   15774   rs374029747 G   A   .   PASS    AF=0.00693057   ES:SE:LP:AF:SS:ID   -0.20865:0.10505:1.32775:0.00693057:83691:rs374029747
1   16949   rs199745162 A   C   .   PASS    AF=0.0196591    ES:SE:LP:AF:SS:ID   -0.049:0.05894:0.391709:0.0196591:83691:rs199745162
1   51479   rs116400033 T   A   .   PASS    AF=0.235613 ES:SE:LP:AF:SS:ID   -0.0121:0.01981:0.266498:0.235613:83691:rs116400033
1   52185   rs201374420 TTAA    T   .   PASS    AF=0.003712 ES:SE:LP:AF:SS:ID   -0.17699:0.16476:0.548643:0.003712:83691:rs201374420
1   54490   rs141149254 G   A   .   PASS    AF=0.173977 ES:SE:LP:AF:SS:ID   -0.0157:0.02208:0.321591:0.173977:83691:rs141149254
1   55164   rs3091274   C   A   .   PASS    AF=0.982923 ES:SE:LP:AF:SS:ID   0.10276:0.07024:0.84333:0.982923:83691:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.0198551    ES:SE:LP:AF:SS:ID   0.08421:0.06548:0.702458:0.0198551:83691:rs3107975
1   55545   rs28396308  C   T   .   PASS    AF=0.22943  ES:SE:LP:AF:SS:ID   -0.0007:0.02026:0.0120925:0.22943:83691:rs28396308
1   57292   rs201418760 C   T   .   PASS    AF=0.0197977    ES:SE:LP:AF:SS:ID   0.07179:0.06561:0.562424:0.0197977:83691:rs201418760
1   58814   rs114420996 G   A   .   PASS    AF=0.0949069    ES:SE:LP:AF:SS:ID   -0.0128:0.02907:0.1807:0.0949069:83691:rs114420996
1   61743   rs184286948 G   C   .   PASS    AF=0.00908972   ES:SE:LP:AF:SS:ID   -0.04849:0.09206:0.223016:0.00908972:83691:rs184286948
1   61920   rs62637820  G   A   .   PASS    AF=0.0281947    ES:SE:LP:AF:SS:ID   0.02161:0.0499:0.177165:0.0281947:83691:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.0214865    ES:SE:LP:AF:SS:ID   -0.0036:0.06138:0.0207795:0.0214865:83691:rs200092917
1   64649   rs181431124 A   C   .   PASS    AF=0.0240029    ES:SE:LP:AF:SS:ID   0.04417:0.05481:0.37643:0.0240029:83691:rs181431124
1   66219   rs181028663 A   T   .   PASS    AF=0.0146975    ES:SE:LP:AF:SS:ID   -0.09386:0.07016:0.742369:0.0146975:83691:rs181028663
1   68082   rs367789441 T   C   .   PASS    AF=0.0771585    ES:SE:LP:AF:SS:ID   -0.00669:0.03159:0.0796888:0.0771585:83691:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0438477    ES:SE:LP:AF:SS:ID   0.03833:0.03809:0.502642:0.0438477:83691:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0819229    ES:SE:LP:AF:SS:ID   -0.00896:0.03077:0.112946:0.0819229:83691:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.754936 ES:SE:LP:AF:SS:ID   0.00393:0.0197:0.0747343:0.754936:83691:rs200676709
1   72297   rs200651397 G   GTAT    .   PASS    AF=0.00546232   ES:SE:LP:AF:SS:ID   0.10443:0.11498:0.439197:0.00546232:83691:rs200651397
1   74790   rs13328700  C   G   .   PASS    AF=0.0320033    ES:SE:LP:AF:SS:ID   0.04009:0.04002:0.49964:0.0320033:83691:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.0320033    ES:SE:LP:AF:SS:ID   0.04009:0.04002:0.49964:0.0320033:83691:rs13328684
1   76854   rs367666799 A   G   .   PASS    AF=0.0672412    ES:SE:LP:AF:SS:ID   -0.02031:0.0334:0.265056:0.0672412:83691:rs367666799
1   82163   rs139113303 G   A   .   PASS    AF=0.0665446    ES:SE:LP:AF:SS:ID   -0.02615:0.03357:0.360514:0.0665446:83691:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0669174    ES:SE:LP:AF:SS:ID   -0.028:0.0335:0.394361:0.0669174:83691:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.331938 ES:SE:LP:AF:SS:ID   0.01332:0.01823:0.332332:0.331938:83691:rs201754587
1   84139   rs183605470 A   T   .   PASS    AF=0.0188246    ES:SE:LP:AF:SS:ID   0.00971:0.06544:0.0545363:0.0188246:83691:rs183605470
1   86028   rs114608975 T   C   .   PASS    AF=0.0463484    ES:SE:LP:AF:SS:ID   0.04958:0.0409:0.647065:0.0463484:83691:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0684708    ES:SE:LP:AF:SS:ID   -0.01856:0.03315:0.239887:0.0684708:83691:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.10333  ES:SE:LP:AF:SS:ID   0.01913:0.02847:0.299703:0.10333:83691:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.008657 ES:SE:LP:AF:SS:ID   0.00812:0.0946:0.0307612:0.008657:83691:rs188486692
1   87360   rs180907504 C   T   .   PASS    AF=0.0203922    ES:SE:LP:AF:SS:ID   -0.03887:0.06327:0.268443:0.0203922:83691:rs180907504
1   87409   rs139490478 C   T   .   PASS    AF=0.0695736    ES:SE:LP:AF:SS:ID   -0.01974:0.03293:0.260515:0.0695736:83691:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.206193 ES:SE:LP:AF:SS:ID   -0.04275:0.01945:1.5534:0.206193:83691:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.0748128    ES:SE:LP:AF:SS:ID   -0.00892:0.03219:0.106893:0.0748128:83691:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.0742194    ES:SE:LP:AF:SS:ID   -0.00524:0.03232:0.059922:0.0742194:83691:rs143215837
1   88188   rs148331237 C   A   .   PASS    AF=0.00796695   ES:SE:LP:AF:SS:ID   -0.06266:0.09345:0.298812:0.00796695:83691:rs148331237
1   88236   rs186918018 C   T   .   PASS    AF=0.0123822    ES:SE:LP:AF:SS:ID   -0.08412:0.0862:0.482619:0.0123822:83691:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.0738751    ES:SE:LP:AF:SS:ID   -0.00872:0.03236:0.103683:0.0738751:83691:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.0835214    ES:SE:LP:AF:SS:ID   0.01689:0.03173:0.225834:0.0835214:83691:rs55700207
1   88710   rs186575039 C   G   .   PASS    AF=0.0695547    ES:SE:LP:AF:SS:ID   -0.01992:0.03293:0.263476:0.0695547:83691:rs186575039
1   89599   rs375955515 A   T   .   PASS    AF=0.0695547    ES:SE:LP:AF:SS:ID   -0.01992:0.03293:0.263476:0.0695547:83691:rs375955515
1   89946   rs138808727 A   T   .   PASS    AF=0.232784 ES:SE:LP:AF:SS:ID   -0.01269:0.01985:0.281889:0.232784:83691:rs138808727
1   91190   rs143856811 G   A   .   PASS    AF=0.0701592    ES:SE:LP:AF:SS:ID   -0.03169:0.0333:0.466838:0.0701592:83691:rs143856811
1   91421   rs28619159  T   C   .   PASS    AF=0.0122252    ES:SE:LP:AF:SS:ID   -0.06439:0.05465:0.62202:0.0122252:83691:rs28619159
1   91515   rs376723915 A   C   .   PASS    AF=0.55822  ES:SE:LP:AF:SS:ID   -0.0004:0.01694:0.00826902:0.55822:83691:rs376723915
1   92633   rs149776517 C   T   .   PASS    AF=0.031027 ES:SE:LP:AF:SS:ID   -0.04879:0.04846:0.503001:0.031027:83691:rs149776517
1   92858   rs147061536 G   T   .   PASS    AF=0.2399   ES:SE:LP:AF:SS:ID   -0.0156:0.01959:0.370754:0.2399:83691:rs147061536