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-1230/ieu-a-1230.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-1230/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 16:57:19 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1230/ieu-a-1230.vcf.gz ...
Read summary statistics for 15122124 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, 1218949 SNPs remain.
After merging with regression SNP LD, 1218949 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0097 (0.0124)
Lambda GC: 1.0195
Mean Chi^2: 1.0242
Intercept: 1.016 (0.0063)
Ratio: 0.661 (0.2607)
Analysis finished at Tue Feb  4 16:59:46 2020
Total time elapsed: 2.0m:27.79s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.96,
    "inflation_factor": 1.0542,
    "mean_EFFECT": -0.5829,
    "n": 42895,
    "n_snps": 15122124,
    "n_clumped_hits": 3,
    "n_p_sig": 131,
    "n_mono": 0,
    "n_ns": 772655,
    "n_mac": 244989,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 1194,
    "n_miss_AF_reference": 158839,
    "n_est": 41289.7965,
    "ratio_se_n": 0.9811,
    "mean_diff": 0.5783,
    "ratio_diff": 5.6792,
    "sd_y_est1": 5.5751,
    "sd_y_est2": 5.4698,
    "r2_sum1": 0.1026,
    "r2_sum2": 0.0033,
    "r2_sum3": 0.0034,
    "r2_sum4": 0.0036,
    "ldsc_nsnp_merge_refpanel_ld": 1218949,
    "ldsc_nsnp_merge_regression_ld": 1218949,
    "ldsc_observed_scale_h2_beta": 0.0097,
    "ldsc_observed_scale_h2_se": 0.0124,
    "ldsc_intercept_beta": 1.016,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0195,
    "ldsc_mean_chisq": 1.0242,
    "ldsc_ratio": 0.6612
}

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 15122122 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 101 0 37292 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 105 0 18032 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.902287e+00 6.259564e+00 1.00000 4.000000e+00 7.000000e+00 1.400000e+01 2.400000e+01 ▇▆▂▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.931131e+07 5.683846e+07 828.00000 3.250234e+07 6.965193e+07 1.158380e+08 2.492402e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -5.828586e-01 3.234614e+00 -20.39000 -9.249000e-02 -3.092000e-03 7.261000e-02 2.040000e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.046663e+00 4.569148e+00 0.01184 4.793000e-02 1.315000e-01 4.894000e-01 1.000000e+03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.923718e-01 2.883748e-01 0.00000 2.419001e-01 4.885995e-01 7.406005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.924567e-01 2.883314e-01 0.00000 2.420902e-01 4.887274e-01 7.406551e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 1194 0.9999210 NA NA NA NA NA 1.582763e-01 2.470367e-01 0.00000 2.491200e-03 2.330000e-02 2.179000e-01 9.999840e-01 ▇▁▁▁▁
numeric AF_reference 158839 0.9894963 NA NA NA NA NA 1.580256e-01 2.343561e-01 0.00000 2.995200e-03 3.574280e-02 2.230430e-01 1.000000e+00 ▇▁▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 4.289500e+04 0.000000e+00 42895.00000 4.289500e+04 4.289500e+04 4.289500e+04 4.289500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C -0.04428 0.23820 0.8525000 0.8525277 0.991000 0.9930110 42895
1 14933 rs199856693 G A -0.13150 0.16750 0.4324999 0.4324098 0.047970 0.0283546 42895
1 15774 rs374029747 G A 0.01944 0.39130 0.9604001 0.9603770 0.006579 0.0119808 42895
1 16949 rs199745162 A C -0.66960 0.24310 0.0058700 0.0058796 0.016750 0.0139776 42895
1 51479 rs116400033 T A -0.08083 0.06979 0.2467999 0.2467870 0.232100 0.1281950 42895
1 52185 rs201374420 TTAA T 0.47180 0.84020 0.5743994 0.5744343 0.005882 0.0053914 42895
1 54353 rs140052487 C A 0.09232 0.91910 0.9199999 0.9199902 0.001339 0.0089856 42895
1 54490 rs141149254 G A -0.15140 0.07876 0.0546198 0.0545686 0.166100 0.0960463 42895
1 55164 rs3091274 C A -0.17520 0.22150 0.4289997 0.4289611 0.980700 0.9233230 42895
1 55326 rs3107975 T C 0.21910 0.20780 0.2916997 0.2917093 0.028260 0.0459265 42895
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154925045 rs509981 C T -0.02851 0.04486 0.5249996 0.5250810 0.250000 0.3634440 42895
23 154925895 rs538470 C T -0.02247 0.04634 0.6276998 0.6277514 0.252700 0.3634440 42895
23 154926376 rs116490668 C T 0.43620 0.71700 0.5429002 0.5429433 0.001859 0.0349669 42895
23 154927185 rs185685661 T C -0.07098 0.07869 0.3670997 0.3670459 0.139300 0.1796030 42895
23 154927199 rs645904 C T -0.03000 0.04491 0.5041004 0.5041319 0.248000 0.3674170 42895
23 154927581 rs644138 G A -0.01833 0.04379 0.6754995 0.6755167 0.299900 0.4635760 42895
23 154929412 rs557132 C T -0.02707 0.04496 0.5471004 0.5471137 0.250400 0.3568210 42895
23 154929952 rs4012982 CAA C -0.02764 0.04500 0.5390996 0.5390685 0.250900 0.3165560 42895
23 154930230 rs781880 A G -0.03126 0.04525 0.4896999 0.4896732 0.249000 0.3618540 42895
24 13537468 rs7203107 A G 0.26660 0.23910 0.2648000 0.2648441 0.985590 NA 42895

bcf preview

1   10616   rs376342519 CCGCCGTTGCAAAGGCGCGCCG  C   .   PASS    AF=0.991    ES:SE:LP:AF:SS:ID   -0.04428:0.2382:0.0693056:0.991:42895:rs376342519
1   14933   rs199856693 G   A   .   PASS    AF=0.04797  ES:SE:LP:AF:SS:ID   -0.1315:0.1675:0.364014:0.04797:42895:rs199856693
1   15774   rs374029747 G   A   .   PASS    AF=0.006579 ES:SE:LP:AF:SS:ID   0.01944:0.3913:0.0175478:0.006579:42895:rs374029747
1   16949   rs199745162 A   C   .   PASS    AF=0.01675  ES:SE:LP:AF:SS:ID   -0.6696:0.2431:2.23136:0.01675:42895:rs199745162
1   51479   rs116400033 T   A   .   PASS    AF=0.2321   ES:SE:LP:AF:SS:ID   -0.08083:0.06979:0.607655:0.2321:42895:rs116400033
1   52185   rs201374420 TTAA    T   .   PASS    AF=0.005882 ES:SE:LP:AF:SS:ID   0.4718:0.8402:0.240786:0.005882:42895:rs201374420
1   54353   rs140052487 C   A   .   PASS    AF=0.001339 ES:SE:LP:AF:SS:ID   0.09232:0.9191:0.0362122:0.001339:42895:rs140052487
1   54490   rs141149254 G   A   .   PASS    AF=0.1661   ES:SE:LP:AF:SS:ID   -0.1514:0.07876:1.26265:0.1661:42895:rs141149254
1   55164   rs3091274   C   A   .   PASS    AF=0.9807   ES:SE:LP:AF:SS:ID   -0.1752:0.2215:0.367543:0.9807:42895:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.02826  ES:SE:LP:AF:SS:ID   0.2191:0.2078:0.535064:0.02826:42895:rs3107975
1   55545   rs28396308  C   T   .   PASS    AF=0.2248   ES:SE:LP:AF:SS:ID   0.1204:0.07508:0.962972:0.2248:42895:rs28396308
1   57183   rs368339209 A   G   .   PASS    AF=0.0007041    ES:SE:LP:AF:SS:ID   -3.885:2.662:0.840433:0.0007041:42895:rs368339209
1   57292   rs201418760 C   T   .   PASS    AF=0.02393  ES:SE:LP:AF:SS:ID   0.3262:0.2011:0.980053:0.02393:42895:rs201418760
1   58814   rs114420996 G   A   .   PASS    AF=0.1003   ES:SE:LP:AF:SS:ID   0.1407:0.1058:0.735891:0.1003:42895:rs114420996
1   61543   rs201849102 T   C   .   PASS    AF=0.0003079    ES:SE:LP:AF:SS:ID   -17.9:13.52:0.731656:0.0003079:42895:rs201849102
1   61743   rs184286948 G   C   .   PASS    AF=0.009155 ES:SE:LP:AF:SS:ID   0.2818:0.3063:0.446602:0.009155:42895:rs184286948
1   61920   rs62637820  G   A   .   PASS    AF=0.02945  ES:SE:LP:AF:SS:ID   0.02121:0.1869:0.0411495:0.02945:42895:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.0207   ES:SE:LP:AF:SS:ID   0.1988:0.2256:0.422393:0.0207:42895:rs200092917
1   64649   rs181431124 A   C   .   PASS    AF=0.02715  ES:SE:LP:AF:SS:ID   0.0721:0.2024:0.141643:0.02715:42895:rs181431124
1   66219   rs181028663 A   T   .   PASS    AF=0.01624  ES:SE:LP:AF:SS:ID   0.1517:0.2411:0.27638:0.01624:42895:rs181028663
1   68082   rs367789441 T   C   .   PASS    AF=0.06526  ES:SE:LP:AF:SS:ID   0.09028:0.1171:0.355758:0.06526:42895:rs367789441
1   68596   rs372212855 T   G   .   PASS    AF=0.003797 ES:SE:LP:AF:SS:ID   -0.6671:0.4963:0.747633:0.003797:42895:rs372212855
1   69428   rs140739101 T   G   .   PASS    AF=0.04215  ES:SE:LP:AF:SS:ID   -0.03021:0.1507:0.0751524:0.04215:42895:rs140739101
1   69534   rs190717287 T   C   .   PASS    AF=0.0003164    ES:SE:LP:AF:SS:ID   1.219:1.361:0.431329:0.0003164:42895:rs190717287
1   69761   rs200505207 A   T   .   PASS    AF=0.06821  ES:SE:LP:AF:SS:ID   0.04896:0.1146:0.174444:0.06821:42895:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.7661   ES:SE:LP:AF:SS:ID   -0.05575:0.07397:0.345823:0.7661:42895:rs200676709
1   72297   rs200651397 G   GTAT    .   PASS    AF=0.006341 ES:SE:LP:AF:SS:ID   0.1978:0.4187:0.196065:0.006341:42895:rs200651397
1   74790   rs13328700  C   G   .   PASS    AF=0.03421  ES:SE:LP:AF:SS:ID   0.1077:0.148:0.330869:0.03421:42895:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.03421  ES:SE:LP:AF:SS:ID   0.1077:0.148:0.330869:0.03421:42895:rs13328684
1   76854   rs367666799 A   G   .   PASS    AF=0.06856  ES:SE:LP:AF:SS:ID   0.02321:0.1264:0.0683896:0.06856:42895:rs367666799
1   82163   rs139113303 G   A   .   PASS    AF=0.06791  ES:SE:LP:AF:SS:ID   0.03206:0.1272:0.0963133:0.06791:42895:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.06818  ES:SE:LP:AF:SS:ID   0.01294:0.1271:0.0366845:0.06818:42895:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.3501   ES:SE:LP:AF:SS:ID   0.1086:0.0684:0.948847:0.3501:42895:rs201754587
1   84139   rs183605470 A   T   .   PASS    AF=0.02132  ES:SE:LP:AF:SS:ID   0.1768:0.2421:0.332454:0.02132:42895:rs183605470
1   86028   rs114608975 T   C   .   PASS    AF=0.04742  ES:SE:LP:AF:SS:ID   0.08134:0.1423:0.245958:0.04742:42895:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.06995  ES:SE:LP:AF:SS:ID   0.06572:0.1248:0.223008:0.06995:42895:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.1018   ES:SE:LP:AF:SS:ID   0.1608:0.09581:1.03044:0.1018:42895:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.00763  ES:SE:LP:AF:SS:ID   -0.1285:0.4058:0.124071:0.00763:42895:rs188486692
1   87360   rs180907504 C   T   .   PASS    AF=0.01853  ES:SE:LP:AF:SS:ID   0.129:0.2072:0.272866:0.01853:42895:rs180907504
1   87409   rs139490478 C   T   .   PASS    AF=0.07088  ES:SE:LP:AF:SS:ID   0.0661:0.1237:0.226872:0.07088:42895:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.2022   ES:SE:LP:AF:SS:ID   0.08971:0.07152:0.678402:0.2022:42895:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.06423  ES:SE:LP:AF:SS:ID   0.07876:0.1191:0.293709:0.06423:42895:rs940551
1   88177   rs143215837 G   C   .   PASS    AF=0.06377  ES:SE:LP:AF:SS:ID   0.09901:0.1195:0.390086:0.06377:42895:rs143215837
1   88188   rs148331237 C   A   .   PASS    AF=0.007142 ES:SE:LP:AF:SS:ID   -0.02859:0.3467:0.0295137:0.007142:42895:rs148331237
1   88236   rs186918018 C   T   .   PASS    AF=0.01279  ES:SE:LP:AF:SS:ID   -0.4268:0.6272:0.304343:0.01279:42895:rs186918018
1   88316   rs113759966 G   A   .   PASS    AF=0.06376  ES:SE:LP:AF:SS:ID   0.09844:0.1196:0.386898:0.06376:42895:rs113759966
1   88338   rs55700207  G   A   .   PASS    AF=0.08209  ES:SE:LP:AF:SS:ID   0.1289:0.1172:0.56591:0.08209:42895:rs55700207
1   88710   rs186575039 C   G   .   PASS    AF=0.07086  ES:SE:LP:AF:SS:ID   0.06699:0.1237:0.230623:0.07086:42895:rs186575039
1   89599   rs375955515 A   T   .   PASS    AF=0.07086  ES:SE:LP:AF:SS:ID   0.06699:0.1237:0.230623:0.07086:42895:rs375955515
1   89946   rs138808727 A   T   .   PASS    AF=0.2272   ES:SE:LP:AF:SS:ID   -0.06819:0.06992:0.482276:0.2272:42895:rs138808727