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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_102050.vcf.gz --id UKB-b:4007 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_102050.txt.gz --cohort_controls 64943 --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-4007/ukb-b-4007.vcf.gz; Date=Sat May  9 15:36:45 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-4007/UKB-b-4007_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4007/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4007/UKB-b-4007_data.vcf.gz ...
Read summary statistics for 8624969 SNPs.
Dropped 7372 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, 1285749 SNPs remain.
After merging with regression SNP LD, 1285749 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0081 (0.0066)
Lambda GC: 1.0251
Mean Chi^2: 1.0252
Intercept: 1.0356 (0.0061)
Ratio: 1.4103 (0.2399)
Analysis finished at Thu Oct 17 14:45:30 2019
Total time elapsed: 1.0m:36.75s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 5,
    "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": 83098,
    "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": 1285749,
    "ldsc_nsnp_merge_regression_ld": 1285749,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0356,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0251,
    "ldsc_mean_chisq": 1.0252,
    "ldsc_ratio": 1.4127
}
 

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 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 8617631 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 8624969 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 8.650349e+00 5.760986e+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 7.877013e+07 5.637166e+07 828.0000000 3.238541e+07 6.929181e+07 1.145690e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.440000e-05 5.010200e-03 -0.0445379 -2.076100e-03 -1.410000e-05 2.051100e-03 6.564270e-02 ▁▆▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.087100e-03 2.789900e-03 0.0016232 1.911600e-03 2.818500e-03 5.524900e-03 2.798190e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.968314e-01 2.894882e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.968307e-01 2.894629e-01 0.0000000 2.455647e-01 4.954570e-01 7.477724e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291178e-01 2.594884e-01 0.0053900 2.519000e-02 1.138990e-01 3.626270e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83098 0.9903654 NA NA NA NA NA NA NA 2.288670e-01 2.514592e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 -0.0021820 0.0029916 0.4700002 0.4657881 0.623817 0.7821490 NA
1 54676 rs2462492 C T -0.0036280 0.0029829 0.2200002 0.2238812 0.399145 NA NA
1 86028 rs114608975 T C 0.0019803 0.0047481 0.6800001 0.6766300 0.103541 0.0277556 NA
1 91536 rs6702460 G T -0.0010499 0.0029339 0.7199992 0.7204580 0.455906 0.4207270 NA
1 234313 rs8179466 C T 0.0075620 0.0058019 0.1900002 0.1924515 0.074459 NA NA
1 534192 rs6680723 C T 0.0020262 0.0033415 0.5400003 0.5442770 0.242052 NA NA
1 546697 rs12025928 A G 0.0044470 0.0041460 0.2800000 0.2834449 0.912857 NA NA
1 693731 rs12238997 A G -0.0009044 0.0027862 0.7499995 0.7454812 0.117317 0.1417730 NA
1 705882 rs72631875 G A 0.0007680 0.0040612 0.8499999 0.8500035 0.067703 0.0315495 NA
1 706368 rs55727773 A G -0.0036257 0.0020682 0.0800000 0.0795872 0.513305 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0001402 0.0025156 0.9599999 0.9555485 0.136304 0.2052720 NA
22 51219387 rs9616832 T C 0.0005880 0.0032789 0.8600001 0.8576797 0.071789 0.0654952 NA
22 51219704 rs147475742 G A -0.0035957 0.0043618 0.4100001 0.4097281 0.041186 0.0473243 NA
22 51221190 rs369304721 G A 0.0002066 0.0043931 0.9599999 0.9624951 0.048362 NA NA
22 51221731 rs115055839 T C 0.0006530 0.0032796 0.8400000 0.8421710 0.071339 0.0625000 NA
22 51222100 rs114553188 G T -0.0002077 0.0038002 0.9599999 0.9564045 0.054848 0.0880591 NA
22 51223637 rs375798137 G A -0.0002076 0.0038201 0.9599999 0.9566603 0.054468 0.0788738 NA
22 51229805 rs9616985 T C 0.0006326 0.0032897 0.8499999 0.8475023 0.071245 0.0730831 NA
22 51232488 rs376461333 A G -0.0026832 0.0075769 0.7199992 0.7232452 0.020457 NA NA
22 51237063 rs3896457 T C -0.0024744 0.0019859 0.2099999 0.2127771 0.298383 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623817 ES:SE:LP:AF:ID  -0.00218195:0.00299164:0.327902:0.623817:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399145 ES:SE:LP:AF:ID  -0.00362797:0.00298286:0.657577:0.399145:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103541 ES:SE:LP:AF:ID  0.00198028:0.00474812:0.167491:0.103541:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455906 ES:SE:LP:AF:ID  -0.00104989:0.00293391:0.142668:0.455906:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074459 ES:SE:LP:AF:ID  0.00756201:0.00580193:0.721246:0.074459:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242052 ES:SE:LP:AF:ID  0.00202617:0.00334154:0.267606:0.242052:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912857 ES:SE:LP:AF:ID  0.00444702:0.00414597:0.552842:0.912857:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117317 ES:SE:LP:AF:ID  -0.000904423:0.00278624:0.124939:0.117317:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067703 ES:SE:LP:AF:ID  0.00076802:0.00406115:0.0705811:0.067703:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513305 ES:SE:LP:AF:ID  -0.00362568:0.00206817:1.09691:0.513305:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033673 ES:SE:LP:AF:ID  -0.00776136:0.00515536:0.886057:0.033673:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037453 ES:SE:LP:AF:ID  -0.00641758:0.0046756:0.769551:0.037453:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03764  ES:SE:LP:AF:ID  -0.0053199:0.00465113:0.60206:0.03764:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037216 ES:SE:LP:AF:ID  -0.00514405:0.00469364:0.568636:0.037216:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016283 ES:SE:LP:AF:ID  0.0077562:0.00736153:0.537602:0.016283:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037856 ES:SE:LP:AF:ID  -0.0050753:0.00463523:0.568636:0.037856:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037951 ES:SE:LP:AF:ID  -0.00508241:0.00462053:0.568636:0.037951:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102744 ES:SE:LP:AF:ID  0.00773063:0.00337488:1.65758:0.102744:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958093 ES:SE:LP:AF:ID  0.00446192:0.0044627:0.49485:0.958093:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031692 ES:SE:LP:AF:ID  0.00487698:0.00817119:0.259637:0.031692:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052725 ES:SE:LP:AF:ID  0.00678438:0.00658169:0.522879:0.052725:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037444 ES:SE:LP:AF:ID  -0.0053585:0.00465087:0.60206:0.037444:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037713 ES:SE:LP:AF:ID  -0.00443913:0.00461234:0.468521:0.037713:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841442 ES:SE:LP:AF:ID  0.0026349:0.00240961:0.568636:0.841442:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056332 ES:SE:LP:AF:ID  -0.00489791:0.00391438:0.677781:0.056332:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123081 ES:SE:LP:AF:ID  -0.00190667:0.00264661:0.327902:0.123081:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025132 ES:SE:LP:AF:ID  0.00104311:0.00659075:0.0604807:0.025132:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122334 ES:SE:LP:AF:ID  -0.00191303:0.00264746:0.327902:0.122334:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134136 ES:SE:LP:AF:ID  -0.00399843:0.00259896:0.920819:0.134136:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011551 ES:SE:LP:AF:ID  -0.0139078:0.00926649:0.886057:0.011551:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006101 ES:SE:LP:AF:ID  0.0129134:0.011762:0.568636:0.006101:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037595 ES:SE:LP:AF:ID  -0.00492567:0.00456959:0.552842:0.037595:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83703  ES:SE:LP:AF:ID  0.00160019:0.002331:0.309804:0.83703:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836734 ES:SE:LP:AF:ID  0.00175523:0.00232929:0.346787:0.836734:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868558 ES:SE:LP:AF:ID  0.000564566:0.00250292:0.0861861:0.868558:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131009 ES:SE:LP:AF:ID  -0.000713485:0.00250934:0.107905:0.131009:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038041 ES:SE:LP:AF:ID  -0.00507256:0.0044979:0.585027:0.038041:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038287 ES:SE:LP:AF:ID  -0.00528087:0.00447002:0.619789:0.038287:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867971 ES:SE:LP:AF:ID  0.000724533:0.00249889:0.113509:0.867971:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868045 ES:SE:LP:AF:ID  0.000694094:0.00249991:0.107905:0.868045:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038195 ES:SE:LP:AF:ID  -0.00528346:0.00449067:0.619789:0.038195:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867982 ES:SE:LP:AF:ID  0.000719432:0.00249883:0.113509:0.867982:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  0.0233135:0.0125236:1.20066:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  0.00156697:0.00232247:0.30103:0.836159:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038198 ES:SE:LP:AF:ID  -0.00507744:0.00449722:0.585027:0.038198:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  0.00149422:0.00232883:0.283997:0.836793:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013031 ES:SE:LP:AF:ID  -0.0141838:0.00842514:1.03621:0.013031:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005662 ES:SE:LP:AF:ID  0.0134358:0.0125072:0.552842:0.005662:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.83811  ES:SE:LP:AF:ID  0.00108266:0.00236161:0.187087:0.83811:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868223 ES:SE:LP:AF:ID  0.000473929:0.00249561:0.0705811:0.868223:rs3115858