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-1045/ieu-a-1045.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-1045/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 19:13:42 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1045/ieu-a-1045.vcf.gz ...
Read summary statistics for 6499595 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, 1170989 SNPs remain.
After merging with regression SNP LD, 1170989 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1492 (0.0375)
Lambda GC: 1.0102
Mean Chi^2: 1.0244
Intercept: 0.9851 (0.0066)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 19:14:54 2020
Total time elapsed: 1.0m:12.02s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9426,
    "inflation_factor": 1.0084,
    "mean_EFFECT": -0.0204,
    "n": 13163,
    "n_snps": 6499595,
    "n_clumped_hits": 2,
    "n_p_sig": 28,
    "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": 88978,
    "n_est": 12855.1257,
    "ratio_se_n": 0.9882,
    "mean_diff": 0.0204,
    "ratio_diff": 1654.019,
    "sd_y_est1": 385.8922,
    "sd_y_est2": 381.3526,
    "r2_sum1": 869.0636,
    "r2_sum2": 0.0058,
    "r2_sum3": 0.006,
    "r2_sum4": 0.0062,
    "ldsc_nsnp_merge_refpanel_ld": 1170989,
    "ldsc_nsnp_merge_regression_ld": 1170989,
    "ldsc_observed_scale_h2_beta": 0.1492,
    "ldsc_observed_scale_h2_se": 0.0375,
    "ldsc_intercept_beta": 0.9851,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.0102,
    "ldsc_mean_chisq": 1.0244,
    "ldsc_ratio": -0.6107
}

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 FALSE
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 6499595 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 8.614661e+00 5.742591e+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 7.937251e+07 5.625676e+07 828.000000 3.317573e+07 7.028342e+07 1.150825e+08 2.492178e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.044990e-02 1.286400e+01 -175.856000 -5.239200e+00 3.700000e-03 5.203300e+00 1.767210e+02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.026882e+01 7.767676e+00 4.488300 5.169800e+00 6.912600e+00 1.204400e+01 6.419520e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.982669e-01 2.894058e-01 0.000000 2.468999e-01 4.982003e-01 7.485003e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.982669e-01 2.894058e-01 0.000000 2.468732e-01 4.982207e-01 7.485393e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.606407e-01 2.612727e-01 0.002639 4.617000e-02 1.609000e-01 4.129000e-01 9.986810e-01 ▇▂▂▁▁
numeric AF_reference 88978 0.9863102 NA NA NA NA NA 2.626810e-01 2.529910e-01 0.000000 5.551120e-02 1.751200e-01 4.107430e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.229524e+04 1.693061e+03 5589.000000 1.256500e+04 1.316300e+04 1.316300e+04 1.316300e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A 4.1808 6.4005 0.5136000 0.5136280 0.8364 0.718251 11688
1 752721 rs3131972 A G 3.9190 6.5805 0.5515006 0.5514776 0.8325 0.653355 11688
1 752894 rs3131971 T C 5.5996 6.9134 0.4179997 0.4179613 0.7955 0.753195 11688
1 753541 rs2073813 G A -7.4193 7.6637 0.3329998 0.3329897 0.1332 0.301917 11688
1 754182 rs3131969 A G 7.0245 7.6730 0.3599001 0.3599382 0.8668 0.678514 11688
1 754192 rs3131968 A G 7.1161 7.7185 0.3565997 0.3565527 0.8654 0.678514 11688
1 754334 rs3131967 T C 10.1024 9.0335 0.2634001 0.2634277 0.8377 0.684305 7251
1 754503 rs3115859 G A 4.9636 6.9758 0.4766998 0.4767462 0.8311 0.663938 11688
1 754964 rs3131966 C T 4.1235 7.5158 0.5832007 0.5832497 0.8074 0.663339 11138
1 755775 rs3131965 A G 4.5659 8.3594 0.5849005 0.5849288 0.7942 NA 8164
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51164115 rs5770996 C T -3.3201 5.0332 0.5094998 0.5094849 0.40770 0.5147760 11773
22 51164287 rs6009957 T C 4.9478 5.4369 0.3627998 0.3628011 0.28630 0.4155350 11773
22 51165390 rs76268556 C T 35.9464 26.4260 0.1737001 0.1737456 0.02507 0.0515176 6607
22 51165664 rs8137951 G A 4.9287 5.4151 0.3627004 0.3627291 0.28100 0.4063500 11773
22 51169045 rs8140772 C T 32.1770 23.5582 0.1719998 0.1719856 0.02770 0.0632987 7152
22 51171667 rs41281537 G A 31.9565 23.5572 0.1749001 0.1749245 0.02770 0.0577077 7152
22 51171693 rs756638 G A 3.4443 5.9928 0.5655005 0.5654674 0.25990 0.3049120 11027
22 51172460 rs5770824 T C 31.9955 23.6080 0.1753000 0.1753277 0.02770 0.0684904 7152
22 51175626 rs3810648 A G 1.9016 10.5741 0.8573000 0.8572816 0.05277 0.1084270 12033
22 51178090 rs2285395 G A 1.6839 11.0114 0.8785001 0.8784587 0.05145 0.0666933 12033

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   4.1808:6.4005:0.289375:0.8364:11688:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8325   ES:SE:LP:AF:SS:ID   3.919:6.5805:0.258454:0.8325:11688:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.7955   ES:SE:LP:AF:SS:ID   5.5996:6.9134:0.378824:0.7955:11688:rs3131971
1   753541  rs2073813   G   A   .   PASS    AF=0.1332   ES:SE:LP:AF:SS:ID   -7.4193:7.6637:0.477556:0.1332:11688:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   7.0245:7.673:0.443818:0.8668:11688:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8654   ES:SE:LP:AF:SS:ID   7.1161:7.7185:0.447819:0.8654:11688:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8377   ES:SE:LP:AF:SS:ID   10.1024:9.0335:0.579384:0.8377:7251:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8311   ES:SE:LP:AF:SS:ID   4.9636:6.9758:0.321755:0.8311:11688:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.8074   ES:SE:LP:AF:SS:ID   4.1235:7.5158:0.234182:0.8074:11138:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.7942   ES:SE:LP:AF:SS:ID   4.5659:8.3594:0.232918:0.7942:8164:rs3131965
1   756604  rs3131962   A   G   .   PASS    AF=0.8351   ES:SE:LP:AF:SS:ID   11.7759:8.8508:0.736601:0.8351:7537:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   9.5645:8.8819:0.550522:0.8668:7732:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8681   ES:SE:LP:AF:SS:ID   10.205:8.8903:0.600326:0.8681:7732:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   10.2807:8.8922:0.606249:0.8668:7732:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8391   ES:SE:LP:AF:SS:ID   9.2787:8.2394:0.58486:0.8391:9066:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   11.4391:9.1693:0.673255:0.8641:6865:rs3131954
1   768448  rs12562034  G   A   .   PASS    AF=0.09763  ES:SE:LP:AF:SS:ID   9.9432:9.4048:0.537003:0.09763:8790:rs12562034
1   769963  rs7518545   G   A   .   PASS    AF=0.09499  ES:SE:LP:AF:SS:ID   11.2994:9.9152:0.594312:0.09499:8790:rs7518545
1   798400  rs10900604  A   G   .   PASS    AF=0.2203   ES:SE:LP:AF:SS:ID   -22.7887:7.7112:2.50529:0.2203:7680:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.2269   ES:SE:LP:AF:SS:ID   -19.838:7.2082:2.2276:0.2269:7680:rs11240777
1   876499  rs4372192   A   G   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -29.251:14.2211:1.40121:0.94987:8492:rs4372192
1   879676  rs6605067   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -29.6893:13.9627:1.47521:0.94987:8492:rs6605067
1   879687  rs2839  T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -26.1417:13.7976:1.23553:0.95119:9042:rs2839
1   880238  rs3748592   A   G   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -26.5561:13.7803:1.26785:0.95251:9042:rs3748592
1   882803  rs2340582   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -25.5004:13.4336:1.23913:0.95119:9042:rs2340582
1   884815  rs4246503   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -23.3019:12.9951:1.13697:0.95119:9042:rs4246503
1   885676  rs4970377   C   A   .   PASS    AF=0.94327  ES:SE:LP:AF:SS:ID   -17.3314:12.6973:0.763715:0.94327:9042:rs4970377
1   885689  rs4970452   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -24.4575:13.1696:1.19866:0.94987:9042:rs4970452
1   885699  rs4970376   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -23.0945:12.9478:1.12796:0.95119:9042:rs4970376
1   886006  rs4970375   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -23.0085:12.8659:1.13241:0.95119:9042:rs4970375
1   887801  rs3828047   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -22.5525:12.6547:1.12651:0.95119:9042:rs3828047
1   888639  rs3748596   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -22.5182:12.6313:1.12709:0.95119:9042:rs3748596
1   888659  rs3748597   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -22.4854:12.609:1.12761:0.95119:9042:rs3748597
1   889238  rs3828049   G   A   .   PASS    AF=0.04749  ES:SE:LP:AF:SS:ID   23.8625:12.8626:1.19675:0.04749:9042:rs3828049
1   889713  rs13303051  C   A   .   PASS    AF=0.94063  ES:SE:LP:AF:SS:ID   -16.88:12.1447:0.78357:0.94063:9042:rs13303051
1   891021  rs13302957  G   A   .   PASS    AF=0.94591  ES:SE:LP:AF:SS:ID   -22.4803:12.6629:1.12004:0.94591:9042:rs13302957
1   892745  rs13303227  G   A   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -23.1356:12.8504:1.14388:0.95119:9042:rs13303227
1   893280  rs4970371   G   A   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -24.5968:13.1006:1.2186:0.95251:9042:rs4970371
1   893631  rs6605069   A   G   .   PASS    AF=0.93931  ES:SE:LP:AF:SS:ID   -17.5269:12.4803:0.795337:0.93931:9042:rs6605069
1   893719  rs4970445   G   A   .   PASS    AF=0.92744  ES:SE:LP:AF:SS:ID   -19.2837:12.4763:0.912929:0.92744:8492:rs4970445
1   896476  rs28393498  A   G   .   PASS    AF=0.93536  ES:SE:LP:AF:SS:ID   -16.7767:13.098:0.698536:0.93536:8492:rs28393498
1   897564  rs13303229  T   C   .   PASS    AF=0.94459  ES:SE:LP:AF:SS:ID   -18.0339:13.2911:0.757459:0.94459:8492:rs13303229
1   897738  rs6696971   C   T   .   PASS    AF=0.05541  ES:SE:LP:AF:SS:ID   19.2194:13.3155:0.827105:0.05541:8492:rs6696971
1   898323  rs6605071   T   C   .   PASS    AF=0.94723  ES:SE:LP:AF:SS:ID   -25.4338:13.8028:1.18456:0.94723:9042:rs6605071
1   898467  rs41285808  C   T   .   PASS    AF=0.04617  ES:SE:LP:AF:SS:ID   25.7034:13.8566:1.19654:0.04617:9042:rs41285808
1   913889  rs2340596   G   A   .   PASS    AF=0.6003   ES:SE:LP:AF:SS:ID   4.9226:5.646:0.416461:0.6003:10044:rs2340596
1   914940  rs13303033  T   C   .   PASS    AF=0.5858   ES:SE:LP:AF:SS:ID   3.6883:5.4811:0.300162:0.5858:10044:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.5989   ES:SE:LP:AF:SS:ID   2.7366:5.4128:0.212398:0.5989:10044:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.5871   ES:SE:LP:AF:SS:ID   3.5632:5.3272:0.297914:0.5871:10044:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.5963   ES:SE:LP:AF:SS:ID   2.6293:5.338:0.206:0.5963:10044:rs2341354