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-1047/ieu-a-1047.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-1047/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 18:00:06 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1047/ieu-a-1047.vcf.gz ...
Read summary statistics for 6506509 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, 1170974 SNPs remain.
After merging with regression SNP LD, 1170974 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2863 (0.0441)
Lambda GC: 1.0144
Mean Chi^2: 1.0272
Intercept: 0.9533 (0.007)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 18:01:12 2020
Total time elapsed: 1.0m:6.74s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9427,
    "inflation_factor": 1.0042,
    "mean_EFFECT": 0.1016,
    "n": 13145,
    "n_snps": 6506509,
    "n_clumped_hits": 4,
    "n_p_sig": 245,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 89188,
    "n_est": 12825.2679,
    "ratio_se_n": 0.9878,
    "mean_diff": -0.1014,
    "ratio_diff": 1886.9457,
    "sd_y_est1": 491.7951,
    "sd_y_est2": 485.7772,
    "r2_sum1": 3723.5146,
    "r2_sum2": 0.0154,
    "r2_sum3": 0.0158,
    "r2_sum4": 0.016,
    "ldsc_nsnp_merge_refpanel_ld": 1170974,
    "ldsc_nsnp_merge_regression_ld": 1170974,
    "ldsc_observed_scale_h2_beta": 0.2863,
    "ldsc_observed_scale_h2_se": 0.0441,
    "ldsc_intercept_beta": 0.9533,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0144,
    "ldsc_mean_chisq": 1.0272,
    "ldsc_ratio": -1.7169
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 TRUE
mean_chisq FALSE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 TRUE
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 58 0 6506509 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.614552e+00 5.742105e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.936943e+07 5.625274e+07 828.000000 3.317657e+07 7.027666e+07 1.150738e+08 2.492178e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.015838e-01 1.611038e+01 -227.374000 -6.579400e+00 5.600000e-02 6.699600e+00 2.500420e+02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.303213e+01 9.753801e+00 5.717700 6.594700e+00 8.815700e+00 1.536610e+01 7.998080e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.988408e-01 2.892071e-01 0.000000 2.483002e-01 4.991005e-01 7.489003e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.988408e-01 2.892071e-01 0.000000 2.482879e-01 4.990860e-01 7.489486e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.603711e-01 2.612680e-01 0.002639 4.485000e-02 1.609000e-01 4.129000e-01 9.986810e-01 ▇▂▂▁▁
numeric AF_reference 89188 0.9862925 NA NA NA NA NA 2.624074e-01 2.530036e-01 0.000000 5.511180e-02 1.747200e-01 4.103430e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.227056e+04 1.705992e+03 5589.000000 1.255000e+04 1.314500e+04 1.314500e+04 1.314500e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A -8.0514 8.1278 0.3219000 0.3218809 0.8364 0.718251 11671
1 752721 rs3131972 A G -8.8651 8.3050 0.2857999 0.2857726 0.8325 0.653355 11671
1 752894 rs3131971 T C -9.9038 8.7075 0.2554001 0.2553764 0.7955 0.753195 11671
1 753541 rs2073813 G A 5.9375 9.6601 0.5388005 0.5387914 0.1332 0.301917 11671
1 754182 rs3131969 A G -5.0930 9.7210 0.6002995 0.6003361 0.8668 0.678514 11671
1 754192 rs3131968 A G -5.3132 9.7827 0.5869999 0.5870458 0.8654 0.678514 11671
1 754334 rs3131967 T C -6.0723 11.3613 0.5930004 0.5930148 0.8377 0.684305 7229
1 754503 rs3115859 G A -8.7664 8.8401 0.3214001 0.3213620 0.8311 0.663938 11671
1 754964 rs3131966 C T -8.2782 9.5425 0.3857003 0.3856634 0.8074 0.663339 11121
1 755775 rs3131965 A G -13.9451 10.6154 0.1890001 0.1889583 0.7942 NA 8142
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51164115 rs5770996 C T 3.8508 6.4061 0.5478000 0.5477637 0.40770 0.5147760 11755
22 51164287 rs6009957 T C 4.4355 6.9464 0.5231003 0.5231273 0.28630 0.4155350 11755
22 51165390 rs76268556 C T -11.6972 31.9513 0.7143006 0.7142944 0.02507 0.0515176 6612
22 51165664 rs8137951 G A 4.3797 6.9201 0.5268003 0.5268019 0.28100 0.4063500 11755
22 51169045 rs8140772 C T -19.3404 28.3232 0.4947001 0.4947038 0.02770 0.0632987 7157
22 51171667 rs41281537 G A -20.7771 27.9539 0.4572998 0.4573225 0.02770 0.0577077 7432
22 51171693 rs756638 G A -1.4364 7.7131 0.8523000 0.8522655 0.25990 0.3049120 11009
22 51172460 rs5770824 T C -20.3543 28.0204 0.4675995 0.4675874 0.02770 0.0684904 7432
22 51175626 rs3810648 A G -2.0823 13.4698 0.8771000 0.8771443 0.05277 0.1084270 12014
22 51178090 rs2285395 G A -10.3399 14.0230 0.4609003 0.4609078 0.05145 0.0666933 12014

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   -8.0514:8.1278:0.492279:0.8364:11671:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8325   ES:SE:LP:AF:SS:ID   -8.8651:8.305:0.543938:0.8325:11671:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.7955   ES:SE:LP:AF:SS:ID   -9.9038:8.7075:0.592779:0.7955:11671:rs3131971
1   753541  rs2073813   G   A   .   PASS    AF=0.1332   ES:SE:LP:AF:SS:ID   5.9375:9.6601:0.268572:0.1332:11671:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -5.093:9.721:0.221632:0.8668:11671:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8654   ES:SE:LP:AF:SS:ID   -5.3132:9.7827:0.231362:0.8654:11671:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8377   ES:SE:LP:AF:SS:ID   -6.0723:11.3613:0.226945:0.8377:7229:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8311   ES:SE:LP:AF:SS:ID   -8.7664:8.8401:0.492954:0.8311:11671:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.8074   ES:SE:LP:AF:SS:ID   -8.2782:9.5425:0.41375:0.8074:11121:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.7942   ES:SE:LP:AF:SS:ID   -13.9451:10.6154:0.723538:0.7942:8142:rs3131965
1   756604  rs3131962   A   G   .   PASS    AF=0.8351   ES:SE:LP:AF:SS:ID   -6.3367:11.2481:0.241694:0.8351:7515:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -6.2965:11.2843:0.238899:0.8668:7710:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8681   ES:SE:LP:AF:SS:ID   -5.9662:11.3:0.223662:0.8681:7710:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -6.0416:11.3041:0.226945:0.8668:7710:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8391   ES:SE:LP:AF:SS:ID   -11.6345:10.4508:0.575772:0.8391:9049:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   -3.5047:11.5307:0.118501:0.8641:6843:rs3131954
1   768448  rs12562034  G   A   .   PASS    AF=0.09763  ES:SE:LP:AF:SS:ID   6.0527:11.6766:0.218819:0.09763:8801:rs12562034
1   769963  rs7518545   G   A   .   PASS    AF=0.09499  ES:SE:LP:AF:SS:ID   7.377:12.3044:0.260586:0.09499:8801:rs7518545
1   798400  rs10900604  A   G   .   PASS    AF=0.2203   ES:SE:LP:AF:SS:ID   -9.1002:9.751:0.455064:0.2203:7657:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.2269   ES:SE:LP:AF:SS:ID   -9.606:9.1617:0.531062:0.2269:7657:rs11240777
1   876499  rs4372192   A   G   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -2.9269:17.9365:0.0602811:0.94987:8470:rs4372192
1   879676  rs6605067   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -0.2632:17.6158:0.0051991:0.94987:8470:rs6605067
1   879687  rs2839  T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   9.9081:17.3909:0.244964:0.95119:9020:rs2839
1   880238  rs3748592   A   G   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   9.949:17.3731:0.246494:0.95251:9020:rs3748592
1   882803  rs2340582   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   8.4936:16.9383:0.210349:0.95119:9020:rs2340582
1   884815  rs4246503   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   8.688:16.4444:0.223807:0.95119:9020:rs4246503
1   885676  rs4970377   C   A   .   PASS    AF=0.94327  ES:SE:LP:AF:SS:ID   15.9806:16.0062:0.497436:0.94327:9020:rs4970377
1   885689  rs4970452   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   9.3591:16.6797:0.240559:0.94987:9020:rs4970452
1   885699  rs4970376   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   8.6319:16.3899:0.223008:0.95119:9020:rs4970376
1   886006  rs4970375   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   8.7064:16.2984:0.226799:0.95119:9020:rs4970375
1   887801  rs3828047   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   8.821:16.0248:0.235077:0.95119:9020:rs3828047
1   888639  rs3748596   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   8.7627:15.9997:0.233662:0.95119:9020:rs3748596
1   888659  rs3748597   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   9.0897:15.9684:0.244735:0.95119:9020:rs3748597
1   889238  rs3828049   G   A   .   PASS    AF=0.04749  ES:SE:LP:AF:SS:ID   -8.815:16.2684:0.230697:0.04749:9020:rs3828049
1   889713  rs13303051  C   A   .   PASS    AF=0.94063  ES:SE:LP:AF:SS:ID   14.3982:15.3569:0.457797:0.94063:9020:rs13303051
1   891021  rs13302957  G   A   .   PASS    AF=0.94591  ES:SE:LP:AF:SS:ID   7.3599:16.0288:0.1897:0.94591:9020:rs13302957
1   892745  rs13303227  G   A   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   9.3135:16.281:0.246187:0.95119:9020:rs13303227
1   893280  rs4970371   G   A   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   9.525:16.6067:0.246953:0.95251:9020:rs4970371
1   893631  rs6605069   A   G   .   PASS    AF=0.93931  ES:SE:LP:AF:SS:ID   16.3156:15.7099:0.524329:0.93931:9020:rs6605069
1   893719  rs4970445   G   A   .   PASS    AF=0.92744  ES:SE:LP:AF:SS:ID   9.3495:15.7089:0.258297:0.92744:8470:rs4970445
1   896476  rs28393498  A   G   .   PASS    AF=0.93536  ES:SE:LP:AF:SS:ID   -6.0022:16.4981:0.145087:0.93536:8470:rs28393498
1   897564  rs13303229  T   C   .   PASS    AF=0.94459  ES:SE:LP:AF:SS:ID   4.6143:16.7239:0.10646:0.94459:8470:rs13303229
1   897738  rs6696971   C   T   .   PASS    AF=0.05541  ES:SE:LP:AF:SS:ID   -4.659:16.7384:0.107516:0.05541:8470:rs6696971
1   898323  rs6605071   T   C   .   PASS    AF=0.94723  ES:SE:LP:AF:SS:ID   11.9657:17.3996:0.308388:0.94723:9020:rs6605071
1   898467  rs41285808  C   T   .   PASS    AF=0.04617  ES:SE:LP:AF:SS:ID   -9.6153:17.4755:0.234928:0.04617:9020:rs41285808
1   913889  rs2340596   G   A   .   PASS    AF=0.6003   ES:SE:LP:AF:SS:ID   13.2626:7.191:1.18622:0.6003:10022:rs2340596
1   914940  rs13303033  T   C   .   PASS    AF=0.5858   ES:SE:LP:AF:SS:ID   13.4834:6.9599:1.27811:0.5858:10022:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.5989   ES:SE:LP:AF:SS:ID   10.4076:6.8832:0.884389:0.5989:10022:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.5871   ES:SE:LP:AF:SS:ID   12.8828:6.7696:1.24382:0.5871:10022:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.5963   ES:SE:LP:AF:SS:ID   10.7738:6.7881:0.948847:0.5963:10022:rs2341354