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-983/ieu-a-983.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-983/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 18:54:54 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-983/ieu-a-983.vcf.gz ...
Read summary statistics for 6270126 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, 1067369 SNPs remain.
After merging with regression SNP LD, 1067369 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 1.081 (0.6209)
Lambda GC: 1.0305
Mean Chi^2: 1.0364
Intercept: 1.0184 (0.0077)
Ratio: 0.5044 (0.2118)
Analysis finished at Tue Feb  4 18:55:59 2020
Total time elapsed: 1.0m:5.54s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8845,
    "inflation_factor": 1.0281,
    "mean_EFFECT": -0.0035,
    "n": 788,
    "n_snps": 6270126,
    "n_clumped_hits": 3,
    "n_p_sig": 317,
    "n_mono": 0,
    "n_ns": 427892,
    "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": 264128,
    "n_est": 762.7324,
    "ratio_se_n": 0.9838,
    "mean_diff": 0.002,
    "ratio_diff": 19.0924,
    "sd_y_est1": 2.5909,
    "sd_y_est2": 2.549,
    "r2_sum1": 1.7245,
    "r2_sum2": 0.2569,
    "r2_sum3": 0.2654,
    "r2_sum4": 0.2646,
    "ldsc_nsnp_merge_refpanel_ld": 1067369,
    "ldsc_nsnp_merge_regression_ld": 1067369,
    "ldsc_observed_scale_h2_beta": 1.081,
    "ldsc_observed_scale_h2_se": 0.6209,
    "ldsc_intercept_beta": 1.0184,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.0305,
    "ldsc_mean_chisq": 1.0364,
    "ldsc_ratio": 0.5055
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 TRUE
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 57 0 6270124 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 44 0 16538 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 40 0 8699 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.560568e+00 5.700104e+00 1.000000 4.000000e+00 8.000000e+00 1.200000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.940239e+07 5.629099e+07 302.000000 3.308474e+07 7.017803e+07 1.151307e+08 2.492186e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.501900e-03 2.248924e-01 -2.380730 -1.286230e-01 -4.360900e-03 1.187070e-01 2.485640e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.035529e-01 9.125380e-02 0.115291 1.374580e-01 1.655740e-01 2.366000e-01 6.201360e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.959075e-01 2.902029e-01 0.000000 2.426779e-01 4.940410e-01 7.482246e-01 9.999996e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.959075e-01 2.902029e-01 0.000000 2.426780e-01 4.940410e-01 7.482239e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 3.248753e-01 2.660484e-01 0.019999 9.579900e-02 2.465280e-01 5.068470e-01 9.799990e-01 ▇▃▂▂▂
numeric AF_reference 264128 0.9578752 NA NA NA NA NA 3.050781e-01 2.404278e-01 0.000000 1.066290e-01 2.422120e-01 4.646570e-01 1.000000e+00 ▇▅▃▂▁
numeric N 0 1.0000000 NA NA NA NA NA 7.880000e+02 0.000000e+00 788.000000 7.880000e+02 7.880000e+02 7.880000e+02 7.880000e+02 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 734349 rs141242758 T C 0.1555830 0.305172 0.6101772 0.6101771 0.071905 0.152556 788
1 752566 rs3094315 G A -0.1571200 0.219059 0.4732199 0.4732200 0.906091 0.718251 788
1 752894 rs3131971 T C -0.0861993 0.240886 0.7204602 0.7204610 0.911485 0.753195 788
1 755775 rs3131965 A G -0.4163050 0.223693 0.0627365 0.0627364 0.882468 NA 788
1 755890 rs3115858 A T -0.1455510 0.225435 0.5185086 0.5185092 0.907663 0.751398 788
1 756604 rs3131962 A G -0.1761620 0.221710 0.4268694 0.4268692 0.895946 0.748003 788
1 757734 rs4951929 C T -0.1396160 0.223268 0.5317555 0.5317550 0.906426 0.748203 788
1 757936 rs4951862 C A -0.1388030 0.223257 0.5341276 0.5341270 0.906379 0.748802 788
1 758144 rs3131956 A G -0.1925800 0.222684 0.3871417 0.3871415 0.904454 0.740216 788
1 758626 rs3131954 C T -0.1409660 0.223539 0.5282956 0.5282954 0.906544 0.751398 788
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51161019 rs5770994 C T -0.0800569 0.128862 0.5344277 0.5344281 0.398612 0.425719 788
22 51162059 rs10451 G A -0.0017837 0.151366 0.9905980 0.9905980 0.443842 0.386581 788
22 51162850 rs5770822 C T 0.0556429 0.135479 0.6812837 0.6812835 0.540916 NA 788
22 51163039 rs715584 G T 0.1879970 0.158027 0.2341833 0.2341835 0.495176 0.473642 788
22 51164109 rs5770995 G C 0.0646153 0.138875 0.6417339 0.6417333 0.636569 0.510982 788
22 51164115 rs5770996 C T 0.0652468 0.138803 0.6383061 0.6383067 0.637306 0.514776 788
22 51164287 rs6009957 T C 0.0158997 0.153757 0.9176393 0.9176392 0.448949 0.415535 788
22 51165664 rs8137951 G A 0.0000315 0.155005 0.9998379 0.9998379 0.444516 0.406350 788
23 57596530 rs36177845 A AT 0.0396765 0.145361 0.7848904 0.7848905 0.241648 NA 788
23 100784211 rs188350543 C A 0.3198740 0.172740 0.0640590 0.0640595 0.806591 0.649801 788

bcf preview

1   734349  rs141242758 T   C   .   PASS    AF=0.071905 ES:SE:LP:AF:SS:ID   0.155583:0.305172:0.214544:0.071905:788:rs141242758
1   752566  rs3094315   G   A   .   PASS    AF=0.906091 ES:SE:LP:AF:SS:ID   -0.15712:0.219059:0.324937:0.906091:788:rs3094315
1   752894  rs3131971   T   C   .   PASS    AF=0.911485 ES:SE:LP:AF:SS:ID   -0.0861993:0.240886:0.14239:0.911485:788:rs3131971
1   755775  rs3131965   A   G   .   PASS    AF=0.882468 ES:SE:LP:AF:SS:ID   -0.416305:0.223693:1.20248:0.882468:788:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.907663 ES:SE:LP:AF:SS:ID   -0.145551:0.225435:0.285244:0.907663:788:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.895946 ES:SE:LP:AF:SS:ID   -0.176162:0.22171:0.369705:0.895946:788:rs3131962
1   757734  rs4951929   C   T   .   PASS    AF=0.906426 ES:SE:LP:AF:SS:ID   -0.139616:0.223268:0.274288:0.906426:788:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.906379 ES:SE:LP:AF:SS:ID   -0.138803:0.223257:0.272355:0.906379:788:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.904454 ES:SE:LP:AF:SS:ID   -0.19258:0.222684:0.41213:0.904454:788:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.906544 ES:SE:LP:AF:SS:ID   -0.140966:0.223539:0.277123:0.906544:788:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.874218 ES:SE:LP:AF:SS:ID   -0.143739:0.216569:0.295098:0.874218:788:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.875167 ES:SE:LP:AF:SS:ID   -0.108578:0.217224:0.209584:0.875167:788:rs3115850
1   761752  rs1057213   C   T   .   PASS    AF=0.903181 ES:SE:LP:AF:SS:ID   -0.157997:0.222476:0.32094:0.903181:788:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.896869 ES:SE:LP:AF:SS:ID   -0.0866257:0.22083:0.158105:0.896869:788:rs3115849
1   764191  rs7515915   T   G   .   PASS    AF=0.09047  ES:SE:LP:AF:SS:ID   0.141569:0.228292:0.271502:0.09047:788:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.064148 ES:SE:LP:AF:SS:ID   -0.157632:0.305939:0.217251:0.064148:788:rs61768174
1   769138  rs59306077  CAT C   .   PASS    AF=0.090205 ES:SE:LP:AF:SS:ID   0.0940011:0.226291:0.168867:0.090205:788:rs59306077
1   769223  rs60320384  C   G   .   PASS    AF=0.080496 ES:SE:LP:AF:SS:ID   -0.013015:0.251324:0.0183175:0.080496:788:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.914489 ES:SE:LP:AF:SS:ID   -0.0592356:0.233768:0.09693:0.914489:788:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.080258 ES:SE:LP:AF:SS:ID   0.0397709:0.24249:0.0606191:0.080258:788:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.914752 ES:SE:LP:AF:SS:ID   -0.059411:0.234455:0.0969324:0.914752:788:rs2905039
1   775181  rs61768182  A   G   .   PASS    AF=0.091643 ES:SE:LP:AF:SS:ID   0.0677725:0.224742:0.117481:0.091643:788:rs61768182
1   777122  rs2980319   A   T   .   PASS    AF=0.909207 ES:SE:LP:AF:SS:ID   -0.105138:0.224841:0.193777:0.909207:788:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.085534 ES:SE:LP:AF:SS:ID   0.0889635:0.232615:0.153584:0.085534:788:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.088989 ES:SE:LP:AF:SS:ID   0.0880999:0.224029:0.158557:0.088989:788:rs4040617
1   781845  rs61768199  A   G   .   PASS    AF=0.058101 ES:SE:LP:AF:SS:ID   -0.162426:0.325616:0.209081:0.058101:788:rs61768199
1   783318  rs6686696   A   G   .   PASS    AF=0.07911  ES:SE:LP:AF:SS:ID   0.0199181:0.254737:0.0279471:0.07911:788:rs6686696
1   786995  rs61768202  G   A   .   PASS    AF=0.089569 ES:SE:LP:AF:SS:ID   0.0737934:0.232547:0.124363:0.089569:788:rs61768202
1   787606  rs3863622   G   T   .   PASS    AF=0.090556 ES:SE:LP:AF:SS:ID   0.10086:0.227546:0.182049:0.090556:788:rs3863622
1   789513  rs200509509 GA  G   .   PASS    AF=0.091362 ES:SE:LP:AF:SS:ID   0.143173:0.226575:0.277817:0.091362:788:rs200509509
1   790465  rs61768207  G   A   .   PASS    AF=0.07839  ES:SE:LP:AF:SS:ID   0.0305182:0.274433:0.0402652:0.07839:788:rs61768207
1   791191  rs111818025 G   A   .   PASS    AF=0.093273 ES:SE:LP:AF:SS:ID   0.148984:0.226774:0.29141:0.093273:788:rs111818025
1   796375  rs12083781  T   C   .   PASS    AF=0.095663 ES:SE:LP:AF:SS:ID   -0.0700113:0.272401:0.0984508:0.095663:788:rs12083781
1   797440  rs58013264  T   C   .   PASS    AF=0.097278 ES:SE:LP:AF:SS:ID   -0.0865508:0.26411:0.128934:0.097278:788:rs58013264
1   801467  rs61768212  G   C   .   PASS    AF=0.096516 ES:SE:LP:AF:SS:ID   -0.015847:0.270251:0.0207976:0.096516:788:rs61768212
1   802496  rs10157494  C   T   .   PASS    AF=0.092121 ES:SE:LP:AF:SS:ID   -0.0906552:0.275235:0.12967:0.092121:788:rs10157494
1   804759  rs7526310   C   T   .   PASS    AF=0.097317 ES:SE:LP:AF:SS:ID   -0.0576653:0.270128:0.0804213:0.097317:788:rs7526310
1   807997  rs61768215  G   A   .   PASS    AF=0.07844  ES:SE:LP:AF:SS:ID   -0.180886:0.29936:0.26306:0.07844:788:rs61768215
1   810780  rs58686784  G   C   .   PASS    AF=0.083672 ES:SE:LP:AF:SS:ID   -0.0761144:0.296442:0.0983433:0.083672:788:rs58686784
1   997769  rs113991671 CG  C   .   PASS    AF=0.110379 ES:SE:LP:AF:SS:ID   -0.249001:0.220963:0.585379:0.110379:788:rs113991671
1   998395  rs7526076   A   G   .   PASS    AF=0.90751  ES:SE:LP:AF:SS:ID   0.331337:0.239149:0.780141:0.90751:788:rs7526076
1   1000156 rs11584349  C   T   .   PASS    AF=0.881879 ES:SE:LP:AF:SS:ID   0.255689:0.214059:0.633968:0.881879:788:rs11584349
1   1000643 rs9442365   C   G   .   PASS    AF=0.911086 ES:SE:LP:AF:SS:ID   0.30305:0.243773:0.669978:0.911086:788:rs9442365
1   1001177 rs4970401   G   C   .   PASS    AF=0.889769 ES:SE:LP:AF:SS:ID   0.284629:0.215609:0.728632:0.889769:788:rs4970401
1   1002932 rs4246502   C   G   .   PASS    AF=0.91097  ES:SE:LP:AF:SS:ID   0.290185:0.241835:0.637958:0.91097:788:rs4246502
1   1003629 rs4075116   C   T   .   PASS    AF=0.888877 ES:SE:LP:AF:SS:ID   0.266845:0.206894:0.705244:0.888877:788:rs4075116
1   1004427 rs11588092  G   A   .   PASS    AF=0.91089  ES:SE:LP:AF:SS:ID   0.280139:0.243641:0.601669:0.91089:788:rs11588092
1   1006990 rs4326571   G   A   .   PASS    AF=0.909989 ES:SE:LP:AF:SS:ID   0.227533:0.248956:0.442801:0.909989:788:rs4326571
1   1007203 rs4633229   A   G   .   PASS    AF=0.916386 ES:SE:LP:AF:SS:ID   0.259535:0.261473:0.493616:0.916386:788:rs4633229
1   1009478 rs9442367   G   C   .   PASS    AF=0.908541 ES:SE:LP:AF:SS:ID   0.239723:0.247325:0.478321:0.908541:788:rs9442367