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-1129/ieu-a-1129.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-1129/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 09:37:25 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1129/ieu-a-1129.vcf.gz ...
Read summary statistics for 10179588 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: 0.1151 (0.011)
Lambda GC: 1.1719
Mean Chi^2: 1.2842
Intercept: 1.0475 (0.0089)
Ratio: 0.167 (0.0312)
Analysis finished at Wed Feb  5 09:39:11 2020
Total time elapsed: 1.0m:46.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9496,
    "inflation_factor": 1.1259,
    "mean_EFFECT": 0.0001,
    "n": 106776,
    "n_snps": 10179588,
    "n_clumped_hits": 61,
    "n_p_sig": 4997,
    "n_mono": 0,
    "n_ns": 620069,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 710,
    "n_miss_AF_reference": 131545,
    "n_est": 103176.8937,
    "ratio_se_n": 0.983,
    "mean_diff": 0.0001,
    "ratio_diff": 0.8709,
    "sd_y_est1": 2.1419,
    "sd_y_est2": 2.1055,
    "r2_sum1": 0.1924,
    "r2_sum2": 0.0419,
    "r2_sum3": 0.0434,
    "r2_sum4": 0.0448,
    "ldsc_nsnp_merge_refpanel_ld": 1220208,
    "ldsc_nsnp_merge_regression_ld": 1220208,
    "ldsc_observed_scale_h2_beta": 0.1151,
    "ldsc_observed_scale_h2_se": 0.011,
    "ldsc_intercept_beta": 1.0475,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.1719,
    "ldsc_mean_chisq": 1.2842,
    "ldsc_ratio": 0.1671
}

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 10179586 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 16150 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.958649e+00 6.304324e+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 7.911755e+07 5.683103e+07 8.28000e+02 3.228365e+07 6.944315e+07 1.156278e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.429000e-04 8.727270e-02 -1.72427e+01 -1.263000e-02 -1.200000e-04 1.238000e-02 1.713200e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.784190e-02 4.427618e+00 8.89000e-03 1.044000e-02 1.586000e-02 3.404000e-02 9.999500e+02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.802056e-01 2.946793e-01 0.00000e+00 2.203500e-01 4.741797e-01 7.354006e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.802056e-01 2.946795e-01 0.00000e+00 2.203405e-01 4.741797e-01 7.354049e-01 1.000000e+00 ▇▇▇▆▆
numeric AF 710 0.9999303 NA NA NA NA NA 2.290717e-01 2.643851e-01 1.00000e-04 2.150000e-02 1.095000e-01 3.656000e-01 9.999000e-01 ▇▂▁▁▁
numeric AF_reference 131545 0.9870776 NA NA NA NA NA 2.273191e-01 2.511926e-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 1.067760e+05 0.000000e+00 1.06776e+05 1.067760e+05 1.067760e+05 1.067760e+05 1.067760e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C 0.00009 0.05784 0.9987000 0.9987585 0.9925 0.9930110 106776
1 14933 rs199856693 G A 0.01994 0.03882 0.6074506 0.6074948 0.0405 0.0283546 106776
1 15774 rs374029747 G A -0.26478 0.09349 0.0046255 0.0046233 0.0069 0.0119808 106776
1 16949 rs199745162 A C -0.04187 0.05199 0.4206801 0.4206194 0.0197 0.0139776 106776
1 51479 rs116400033 T A -0.01864 0.01764 0.2906899 0.2906534 0.2356 0.1281950 106776
1 52185 rs201374420 TTAA T -0.03336 0.14241 0.8147699 0.8147884 0.0037 0.0053914 106776
1 54490 rs141149254 G A -0.03548 0.01969 0.0715715 0.0715564 0.1740 0.0960463 106776
1 55164 rs3091274 C A 0.09058 0.06232 0.1460599 0.1460944 0.9829 0.9233230 106776
1 55326 rs3107975 T C 0.08920 0.05824 0.1256099 0.1256228 0.0199 0.0459265 106776
1 55545 rs28396308 C T 0.00630 0.01807 0.7274900 0.7273565 0.2294 0.2392170 106776
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154925045 rs509981 C T -0.00102 0.01052 0.9226001 0.9227596 0.2390 0.3634440 106776
23 154925895 rs538470 C T -0.00008 0.01056 0.9941300 0.9939555 0.2463 0.3634440 106776
23 154927185 rs185685661 T C 0.02143 0.01955 0.2729097 0.2730071 0.1120 0.1796030 106776
23 154927199 rs645904 C T -0.00073 0.01053 0.9449900 0.9447303 0.2396 0.3674170 106776
23 154927581 rs644138 G A -0.00034 0.01014 0.9736001 0.9732515 0.2869 0.4635760 106776
23 154928151 rs144607509 C T -0.02688 0.05518 0.6261105 0.6261641 0.0215 0.0084768 106776
23 154929412 rs557132 C T -0.00098 0.01053 0.9257399 0.9258500 0.2384 0.3568210 106776
23 154929952 rs4012982 CAA C 0.01446 0.01551 0.3513104 0.3511806 0.1910 0.3165560 106776
23 154930230 rs781880 A G -0.00109 0.01054 0.9178200 0.9176332 0.2383 0.3618540 106776
24 13537468 rs7203107 A G -0.05847 0.06927 0.3985704 0.3986200 0.9913 NA 106776

bcf preview

1   10616   rs376342519 CCGCCGTTGCAAAGGCGCGCCG  C   .   PASS    AF=0.9925   ES:SE:LP:AF:SS:ID   9e-05:0.05784:0.00056495:0.9925:106776:rs376342519
1   14933   rs199856693 G   A   .   PASS    AF=0.0405   ES:SE:LP:AF:SS:ID   0.01994:0.03882:0.216489:0.0405:106776:rs199856693
1   15774   rs374029747 G   A   .   PASS    AF=0.0069   ES:SE:LP:AF:SS:ID   -0.26478:0.09349:2.33484:0.0069:106776:rs374029747
1   16949   rs199745162 A   C   .   PASS    AF=0.0197   ES:SE:LP:AF:SS:ID   -0.04187:0.05199:0.376048:0.0197:106776:rs199745162
1   51479   rs116400033 T   A   .   PASS    AF=0.2356   ES:SE:LP:AF:SS:ID   -0.01864:0.01764:0.53657:0.2356:106776:rs116400033
1   52185   rs201374420 TTAA    T   .   PASS    AF=0.0037   ES:SE:LP:AF:SS:ID   -0.03336:0.14241:0.088965:0.0037:106776:rs201374420
1   54490   rs141149254 G   A   .   PASS    AF=0.174    ES:SE:LP:AF:SS:ID   -0.03548:0.01969:1.14526:0.174:106776:rs141149254
1   55164   rs3091274   C   A   .   PASS    AF=0.9829   ES:SE:LP:AF:SS:ID   0.09058:0.06232:0.835469:0.9829:106776:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.0199   ES:SE:LP:AF:SS:ID   0.0892:0.05824:0.900976:0.0199:106776:rs3107975
1   55545   rs28396308  C   T   .   PASS    AF=0.2294   ES:SE:LP:AF:SS:ID   0.0063:0.01807:0.138173:0.2294:106776:rs28396308
1   57292   rs201418760 C   T   .   PASS    AF=0.0198   ES:SE:LP:AF:SS:ID   0.08191:0.05823:0.797239:0.0198:106776:rs201418760
1   58814   rs114420996 G   A   .   PASS    AF=0.0949   ES:SE:LP:AF:SS:ID   -0.0202:0.02596:0.359886:0.0949:106776:rs114420996
1   61743   rs184286948 G   C   .   PASS    AF=0.0091   ES:SE:LP:AF:SS:ID   -0.07671:0.08253:0.452681:0.0091:106776:rs184286948
1   61920   rs62637820  G   A   .   PASS    AF=0.0282   ES:SE:LP:AF:SS:ID   0.02587:0.04456:0.250604:0.0282:106776:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.0215   ES:SE:LP:AF:SS:ID   0.02094:0.05435:0.15489:0.0215:106776:rs200092917
1   64649   rs181431124 A   C   .   PASS    AF=0.024    ES:SE:LP:AF:SS:ID   0.04342:0.04895:0.425946:0.024:106776:rs181431124
1   66219   rs181028663 A   T   .   PASS    AF=0.0147   ES:SE:LP:AF:SS:ID   -0.07224:0.06188:0.614304:0.0147:106776:rs181028663
1   68082   rs367789441 T   C   .   PASS    AF=0.0772   ES:SE:LP:AF:SS:ID   0.00511:0.02804:0.0677749:0.0772:106776:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0438   ES:SE:LP:AF:SS:ID   0.02187:0.03388:0.285075:0.0438:106776:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0819   ES:SE:LP:AF:SS:ID   0.0038:0.0273:0.0509029:0.0819:106776:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.7549   ES:SE:LP:AF:SS:ID   0.00329:0.01755:0.0698051:0.7549:106776:rs200676709
1   72297   rs200651397 G   GTAT    .   PASS    AF=0.0055   ES:SE:LP:AF:SS:ID   0.13318:0.10181:0.719308:0.0055:106776:rs200651397
1   74790   rs13328700  C   G   .   PASS    AF=0.032    ES:SE:LP:AF:SS:ID   0.04531:0.03567:0.690391:0.032:106776:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.032    ES:SE:LP:AF:SS:ID   0.04531:0.03567:0.690391:0.032:106776:rs13328684
1   76854   rs367666799 A   G   .   PASS    AF=0.0672   ES:SE:LP:AF:SS:ID   -0.00336:0.02957:0.0411877:0.0672:106776:rs367666799
1   82163   rs139113303 G   A   .   PASS    AF=0.0665   ES:SE:LP:AF:SS:ID   -0.00949:0.02971:0.125263:0.0665:106776:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0669   ES:SE:LP:AF:SS:ID   -0.01134:0.02965:0.153496:0.0669:106776:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.3319   ES:SE:LP:AF:SS:ID   0.01904:0.0162:0.620133:0.3319:106776:rs201754587
1   84139   rs183605470 A   T   .   PASS    AF=0.0188   ES:SE:LP:AF:SS:ID   -0.01353:0.05855:0.0876238:0.0188:106776:rs183605470
1   86028   rs114608975 T   C   .   PASS    AF=0.0463   ES:SE:LP:AF:SS:ID   0.02386:0.0365:0.28957:0.0463:106776:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0685   ES:SE:LP:AF:SS:ID   -0.01068:0.02939:0.144844:0.0685:106776:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.1033   ES:SE:LP:AF:SS:ID   0.01894:0.0253:0.342839:0.1033:106776:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.0087   ES:SE:LP:AF:SS:ID   0.06552:0.0825:0.36946:0.0087:106776:rs188486692
1   87360   rs180907504 C   T   .   PASS    AF=0.0204   ES:SE:LP:AF:SS:ID   -0.02064:0.05607:0.147038:0.0204:106776:rs180907504
1   87409   rs139490478 C   T   .   PASS    AF=0.0696   ES:SE:LP:AF:SS:ID   -0.00866:0.02918:0.11538:0.0696:106776:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.2062   ES:SE:LP:AF:SS:ID   -0.03673:0.0173:1.47224:0.2062:106776:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.0748   ES:SE:LP:AF:SS:ID   0.004:0.02857:0.0513181:0.0748:106776:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.0742   ES:SE:LP:AF:SS:ID   0.00612:0.02868:0.0803781:0.0742:106776:rs143215837
1   88188   rs148331237 C   A   .   PASS    AF=0.008    ES:SE:LP:AF:SS:ID   -0.13808:0.08341:1.00945:0.008:106776:rs148331237
1   88236   rs186918018 C   T   .   PASS    AF=0.0124   ES:SE:LP:AF:SS:ID   -0.13352:0.07773:1.06627:0.0124:106776:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.0739   ES:SE:LP:AF:SS:ID   0.00268:0.02872:0.0334969:0.0739:106776:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.0835   ES:SE:LP:AF:SS:ID   0.01932:0.02835:0.304983:0.0835:106776:rs55700207
1   88710   rs186575039 C   G   .   PASS    AF=0.0696   ES:SE:LP:AF:SS:ID   -0.00889:0.02918:0.118844:0.0696:106776:rs186575039
1   89599   rs375955515 A   T   .   PASS    AF=0.0696   ES:SE:LP:AF:SS:ID   -0.00889:0.02918:0.118844:0.0696:106776:rs375955515
1   89946   rs138808727 A   T   .   PASS    AF=0.2328   ES:SE:LP:AF:SS:ID   -0.01422:0.01766:0.376151:0.2328:106776:rs138808727
1   91190   rs143856811 G   A   .   PASS    AF=0.0702   ES:SE:LP:AF:SS:ID   -0.0137:0.02944:0.192675:0.0702:106776:rs143856811
1   91421   rs28619159  T   C   .   PASS    AF=0.0122   ES:SE:LP:AF:SS:ID   -0.08992:0.04861:1.19128:0.0122:106776:rs28619159
1   91515   rs376723915 A   C   .   PASS    AF=0.5582   ES:SE:LP:AF:SS:ID   0.00542:0.01507:0.143144:0.5582:106776:rs376723915
1   92633   rs149776517 C   T   .   PASS    AF=0.031    ES:SE:LP:AF:SS:ID   -0.0405:0.04302:0.460322:0.031:106776:rs149776517
1   92858   rs147061536 G   T   .   PASS    AF=0.2399   ES:SE:LP:AF:SS:ID   -0.01704:0.01742:0.484113:0.2399:106776:rs147061536