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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_816.vcf.gz --id UKB-b:2002 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_816.txt.gz --cohort_controls 263615 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-2002/ukb-b-2002.vcf.gz; Date=Sun May 10 06:24:11 2020"
}

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/public/UKB-b-2002/UKB-b-2002_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2002/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:00 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2002/UKB-b-2002_data.vcf.gz ...
Read summary statistics for 9681826 SNPs.
Dropped 13112 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1288744 SNPs remain.
After merging with regression SNP LD, 1288744 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0785 (0.0035)
Lambda GC: 1.3822
Mean Chi^2: 1.4567
Intercept: 1.0496 (0.0083)
Ratio: 0.1086 (0.0181)
Analysis finished at Thu Oct 17 14:43:42 2019
Total time elapsed: 1.0m:41.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9496,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 25,
    "n_p_sig": 1633,
    "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": 158041,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1288744,
    "ldsc_nsnp_merge_regression_ld": 1288744,
    "ldsc_observed_scale_h2_beta": 0.0785,
    "ldsc_observed_scale_h2_se": 0.0035,
    "ldsc_intercept_beta": 1.0496,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.3822,
    "ldsc_mean_chisq": 1.4567,
    "ldsc_ratio": 0.1086
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 9668778 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9681826 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.626133e+00 5.750239e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.884225e+07 5.629539e+07 828.0000000 3.256139e+07 6.944636e+07 1.145730e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.690000e-04 1.087810e-02 -0.1519380 -3.703100e-03 5.780000e-05 3.877900e-03 2.207890e-01 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.747600e-03 6.889100e-03 0.0023078 2.808900e-03 4.621200e-03 1.043730e-02 1.210250e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.619864e-01 2.985652e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.619879e-01 2.985418e-01 0.0000000 1.941967e-01 4.479334e-01 7.205565e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.064529e-01 2.570238e-01 0.0013280 1.438500e-02 8.215400e-02 3.222460e-01 9.986720e-01 ▇▂▁▁▁
numeric AF_reference 158041 0.9836765 NA NA NA NA NA NA NA 2.089379e-01 2.486131e-01 0.0000000 1.257990e-02 1.030350e-01 3.246810e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C 0.0059234 0.0042490 0.1600000 0.1632997 0.623924 0.7821490 NA
1 54676 rs2462492 C T -0.0100607 0.0042047 0.0170000 0.0167234 0.400577 NA NA
1 86028 rs114608975 T C 0.0125865 0.0067172 0.0610000 0.0609607 0.103551 0.0277556 NA
1 91536 rs6702460 G T -0.0022076 0.0041422 0.5900000 0.5940624 0.456762 0.4207270 NA
1 234313 rs8179466 C T 0.0005679 0.0081347 0.9400001 0.9443418 0.074781 NA NA
1 534192 rs6680723 C T 0.0000466 0.0047326 0.9900000 0.9921501 0.241042 NA NA
1 546697 rs12025928 A G -0.0094859 0.0059057 0.1100001 0.1082243 0.913624 NA NA
1 693731 rs12238997 A G -0.0030201 0.0039582 0.4500005 0.4454704 0.116250 0.1417730 NA
1 705882 rs72631875 G A 0.0000481 0.0058201 0.9900000 0.9934031 0.066999 0.0315495 NA
1 706368 rs55727773 A G -0.0002730 0.0029342 0.9299999 0.9258836 0.515530 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0129023 0.0061557 0.0359998 0.0360829 0.042130 0.0473243 NA
22 51219766 rs182321900 C T 0.0079286 0.0283296 0.7800007 0.7795771 0.002000 NA NA
22 51220146 rs868950473 C T 0.0062180 0.0280690 0.8200001 0.8246830 0.002049 NA NA
22 51221190 rs369304721 G A -0.0192155 0.0061458 0.0018000 0.0017684 0.049908 NA NA
22 51221731 rs115055839 T C -0.0142333 0.0046004 0.0020000 0.0019754 0.073432 0.0625000 NA
22 51222100 rs114553188 G T 0.0103092 0.0054267 0.0569994 0.0574683 0.054504 0.0880591 NA
22 51223637 rs375798137 G A 0.0102550 0.0054527 0.0599998 0.0600087 0.054144 0.0788738 NA
22 51229805 rs9616985 T C -0.0139819 0.0046174 0.0025000 0.0024608 0.073262 0.0730831 NA
22 51232488 rs376461333 A G 0.0183385 0.0108853 0.0920005 0.0920458 0.020034 NA NA
22 51237063 rs3896457 T C 0.0016657 0.0028292 0.5600000 0.5560266 0.297358 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623924 ES:SE:LP:AF:ID  0.0059234:0.00424903:0.79588:0.623924:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400577 ES:SE:LP:AF:ID  -0.0100607:0.00420469:1.76955:0.400577:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103551 ES:SE:LP:AF:ID  0.0125865:0.00671717:1.21467:0.103551:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456762 ES:SE:LP:AF:ID  -0.00220762:0.0041422:0.229148:0.456762:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074781 ES:SE:LP:AF:ID  0.000567916:0.00813472:0.0268721:0.074781:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241042 ES:SE:LP:AF:ID  4.65619e-05:0.0047326:0.00436481:0.241042:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913624 ES:SE:LP:AF:ID  -0.00948592:0.00590572:0.958607:0.913624:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11625  ES:SE:LP:AF:ID  -0.00302006:0.0039582:0.346787:0.11625:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066999 ES:SE:LP:AF:ID  4.81216e-05:0.00582013:0.00436481:0.066999:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51553  ES:SE:LP:AF:ID  -0.000272957:0.00293423:0.0315171:0.51553:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033273 ES:SE:LP:AF:ID  0.00342765:0.00737121:0.19382:0.033273:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.0369   ES:SE:LP:AF:ID  0.00530365:0.0066986:0.366532:0.0369:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037004 ES:SE:LP:AF:ID  0.00546097:0.00667546:0.387216:0.037004:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036717 ES:SE:LP:AF:ID  0.00529828:0.00672116:0.366532:0.036717:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016451 ES:SE:LP:AF:ID  0.00278127:0.0103665:0.102373:0.016451:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037266 ES:SE:LP:AF:ID  0.00511428:0.00664659:0.356547:0.037266:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037364 ES:SE:LP:AF:ID  0.00457127:0.00662424:0.309804:0.037364:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101071 ES:SE:LP:AF:ID  -0.00209729:0.00485005:0.173925:0.101071:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958715 ES:SE:LP:AF:ID  -0.00600232:0.00638108:0.455932:0.958715:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031509 ES:SE:LP:AF:ID  0.0078438:0.011606:0.30103:0.031509:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053225 ES:SE:LP:AF:ID  -0.0062126:0.00924923:0.30103:0.053225:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036868 ES:SE:LP:AF:ID  0.00562487:0.00666819:0.39794:0.036868:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03718  ES:SE:LP:AF:ID  0.00556989:0.00660741:0.39794:0.03718:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842911 ES:SE:LP:AF:ID  -1.11102e-05:0.00342655:-0:0.842911:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055786 ES:SE:LP:AF:ID  -0.0106871:0.00556494:1.25964:0.055786:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122257 ES:SE:LP:AF:ID  -0.00285714:0.00375387:0.346787:0.122257:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025719 ES:SE:LP:AF:ID  0.00237729:0.00924198:0.09691:0.025719:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121473 ES:SE:LP:AF:ID  -0.00266423:0.00375551:0.318759:0.121473:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132466 ES:SE:LP:AF:ID  -0.00179346:0.00370083:0.200659:0.132466:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011209 ES:SE:LP:AF:ID  0.00228513:0.0134599:0.0604807:0.011209:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005727 ES:SE:LP:AF:ID  0.00510977:0.017354:0.113509:0.005727:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002328 ES:SE:LP:AF:ID  0.0405134:0.0288023:0.79588:0.002328:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.037115 ES:SE:LP:AF:ID  0.00561178:0.00653869:0.408935:0.037115:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838728 ES:SE:LP:AF:ID  3.01193e-05:0.00332016:0.00436481:0.838728:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838309 ES:SE:LP:AF:ID  2.30367e-05:0.00331609:0.00436481:0.838309:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869767 ES:SE:LP:AF:ID  0.00157602:0.0035597:0.180456:0.869767:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129913 ES:SE:LP:AF:ID  -0.00187305:0.00356652:0.221849:0.129913:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037621 ES:SE:LP:AF:ID  0.00677148:0.00642798:0.537602:0.037621:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037873 ES:SE:LP:AF:ID  0.00661144:0.00638693:0.522879:0.037873:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869068 ES:SE:LP:AF:ID  0.00166529:0.00355216:0.19382:0.869068:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86917  ES:SE:LP:AF:ID  0.00175912:0.00355367:0.207608:0.86917:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037828 ES:SE:LP:AF:ID  0.00628226:0.00641496:0.481486:0.037828:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869073 ES:SE:LP:AF:ID  0.00165914:0.00355219:0.19382:0.869073:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005123 ES:SE:LP:AF:ID  0.0107062:0.0182496:0.251812:0.005123:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005089 ES:SE:LP:AF:ID  0.00979806:0.018298:0.229148:0.005089:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837747 ES:SE:LP:AF:ID  0.000178829:0.00330695:0.0177288:0.837747:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037842 ES:SE:LP:AF:ID  0.00610115:0.006424:0.468521:0.037842:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838401 ES:SE:LP:AF:ID  0.000449652:0.00331637:0.05061:0.838401:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013724 ES:SE:LP:AF:ID  -0.0010373:0.0116224:0.0315171:0.013724:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.00553  ES:SE:LP:AF:ID  0.0170722:0.0179404:0.468521:0.00553:rs184270342