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_23107.vcf.gz --id UKB-b:7376 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_23107.txt.gz --cohort_controls 454863 --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": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-7376/ukb-b-7376.vcf.gz; Date=Sat May  9 14:38:47 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-7376/UKB-b-7376_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7376/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7376/UKB-b-7376_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2345 (0.0078)
Lambda GC: 2.4138
Mean Chi^2: 3.471
Intercept: 1.2434 (0.0226)
Ratio: 0.0985 (0.0092)
Analysis finished at Thu Oct 17 14:41:54 2019
Total time elapsed: 1.0m:36.52s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.92,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 489,
    "n_p_sig": 84217,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.2345,
    "ldsc_observed_scale_h2_se": 0.0078,
    "ldsc_intercept_beta": 1.2434,
    "ldsc_intercept_se": 0.0226,
    "ldsc_lambda_gc": 2.4138,
    "ldsc_mean_chisq": 3.471,
    "ldsc_ratio": 0.0985
}
 

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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.910000e-05 9.839100e-03 -0.1675340 -3.734200e-03 2.090000e-05 3.789900e-03 2.419970e-01 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.205000e-03 5.872900e-03 0.0017343 2.125800e-03 3.564600e-03 8.224200e-03 9.126410e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.984315e-01 3.113863e-01 0.0000000 1.000000e-01 3.500000e-01 6.700003e-01 1.000000e+00 ▇▅▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.984342e-01 3.113654e-01 0.0000000 1.038465e-01 3.549578e-01 6.655251e-01 9.999996e-01 ▇▅▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568614e-01 0.0009850 1.316900e-02 7.791300e-02 3.164560e-01 9.990060e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 -0.0024098 0.0031842 0.4500005 0.4491787 0.623734 0.7821490 NA
1 54676 rs2462492 C T -0.0022234 0.0031552 0.4799997 0.4810156 0.400351 NA NA
1 86028 rs114608975 T C -0.0018808 0.0050438 0.7099994 0.7092314 0.103558 0.0277556 NA
1 91536 rs6702460 G T -0.0038771 0.0031060 0.2099999 0.2119415 0.456839 0.4207270 NA
1 234313 rs8179466 C T 0.0120748 0.0061270 0.0490004 0.0487529 0.074495 NA NA
1 534192 rs6680723 C T -0.0022777 0.0035484 0.5199996 0.5209445 0.240939 NA NA
1 546697 rs12025928 A G -0.0084676 0.0044267 0.0560003 0.0557680 0.913464 NA NA
1 693731 rs12238997 A G -0.0020724 0.0029752 0.4899999 0.4860707 0.116214 0.1417730 NA
1 705882 rs72631875 G A 0.0044612 0.0043565 0.3100002 0.3058165 0.067319 0.0315495 NA
1 706368 rs55727773 A G 0.0043325 0.0022030 0.0490004 0.0492277 0.515784 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0023619 0.0046549 0.6100002 0.6118698 0.041966 0.0473243 NA
22 51219766 rs182321900 C T 0.0042554 0.0216656 0.8400000 0.8442871 0.001942 NA NA
22 51220146 rs868950473 C T 0.0060989 0.0214593 0.7800007 0.7762504 0.001991 NA NA
22 51221190 rs369304721 G A -0.0001679 0.0046464 0.9699999 0.9711695 0.049761 NA NA
22 51221731 rs115055839 T C -0.0018901 0.0034756 0.5900000 0.5865664 0.073280 0.0625000 NA
22 51222100 rs114553188 G T -0.0006005 0.0040920 0.8800001 0.8833324 0.054487 0.0880591 NA
22 51223637 rs375798137 G A -0.0005819 0.0041118 0.8900000 0.8874612 0.054117 0.0788738 NA
22 51229805 rs9616985 T C -0.0016023 0.0034882 0.6499995 0.6459849 0.073113 0.0730831 NA
22 51232488 rs376461333 A G 0.0006986 0.0082160 0.9299999 0.9322356 0.020056 NA NA
22 51237063 rs3896457 T C -0.0052875 0.0021345 0.0129999 0.0132442 0.297891 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623734 ES:SE:LP:AF:ID  -0.00240977:0.00318422:0.346787:0.623734:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400351 ES:SE:LP:AF:ID  -0.00222341:0.00315525:0.318759:0.400351:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103558 ES:SE:LP:AF:ID  -0.00188079:0.00504384:0.148742:0.103558:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456839 ES:SE:LP:AF:ID  -0.00387706:0.00310601:0.677781:0.456839:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074495 ES:SE:LP:AF:ID  0.0120748:0.00612702:1.3098:0.074495:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240939 ES:SE:LP:AF:ID  -0.00227767:0.00354838:0.283997:0.240939:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913464 ES:SE:LP:AF:ID  -0.00846757:0.00442669:1.25181:0.913464:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116214 ES:SE:LP:AF:ID  -0.00207242:0.00297517:0.309804:0.116214:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067319 ES:SE:LP:AF:ID  0.00446125:0.00435652:0.508638:0.067319:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515784 ES:SE:LP:AF:ID  0.00433247:0.00220301:1.3098:0.515784:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032987 ES:SE:LP:AF:ID  -0.00377125:0.00555443:0.30103:0.032987:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036599 ES:SE:LP:AF:ID  -0.00463805:0.00504575:0.443698:0.036599:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036717 ES:SE:LP:AF:ID  -0.00509753:0.00502628:0.508638:0.036717:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036414 ES:SE:LP:AF:ID  -0.00444168:0.00506281:0.420216:0.036414:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016391 ES:SE:LP:AF:ID  -0.00256016:0.00779732:0.130768:0.016391:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036954 ES:SE:LP:AF:ID  -0.00449831:0.00500669:0.431798:0.036954:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  -0.00455767:0.0049894:0.443698:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101237 ES:SE:LP:AF:ID  -0.0013775:0.00363404:0.154902:0.101237:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959097 ES:SE:LP:AF:ID  0.00513647:0.004811:0.537602:0.959097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031462 ES:SE:LP:AF:ID  0.0129857:0.00872832:0.853872:0.031462:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053256 ES:SE:LP:AF:ID  0.001174:0.00694263:0.0604807:0.053256:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036573 ES:SE:LP:AF:ID  -0.00382935:0.00502145:0.346787:0.036573:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  -0.00284541:0.00497572:0.244125:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843323 ES:SE:LP:AF:ID  0.00316579:0.00257777:0.657577:0.843323:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055857 ES:SE:LP:AF:ID  0.00679793:0.00417461:1:0.055857:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12219  ES:SE:LP:AF:ID  -0.0025672:0.0028222:0.443698:0.12219:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  0.0090551:0.00693457:0.721246:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121431 ES:SE:LP:AF:ID  -0.00273716:0.00282339:0.481486:0.121431:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132217 ES:SE:LP:AF:ID  -0.00272515:0.00278233:0.481486:0.132217:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011122 ES:SE:LP:AF:ID  -0.0049654:0.0101229:0.207608:0.011122:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  -0.0233377:0.0130587:1.13077:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002287 ES:SE:LP:AF:ID  -0.0114573:0.0218625:0.221849:0.002287:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  -0.00152002:0.0357623:0.0132283:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036805 ES:SE:LP:AF:ID  -0.00286131:0.00492543:0.251812:0.036805:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839053 ES:SE:LP:AF:ID  0.00250751:0.00249622:0.49485:0.839053:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83868  ES:SE:LP:AF:ID  0.00260005:0.00249349:0.522879:0.83868:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869875 ES:SE:LP:AF:ID  0.00238754:0.00267596:0.431798:0.869875:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129765 ES:SE:LP:AF:ID  -0.00208337:0.00268155:0.356547:0.129765:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  -0.00151342:0.00484196:0.124939:0.037317:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037562 ES:SE:LP:AF:ID  -0.00135691:0.00481129:0.107905:0.037562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869219 ES:SE:LP:AF:ID  0.00239983:0.0026707:0.431798:0.869219:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869317 ES:SE:LP:AF:ID  0.0023573:0.00267176:0.420216:0.869317:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037515 ES:SE:LP:AF:ID  -0.00143837:0.00483238:0.113509:0.037515:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869222 ES:SE:LP:AF:ID  0.00240844:0.00267064:0.431798:0.869222:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005131 ES:SE:LP:AF:ID  0.00492341:0.0136913:0.142668:0.005131:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005097 ES:SE:LP:AF:ID  0.00531186:0.0137268:0.154902:0.005097:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838136 ES:SE:LP:AF:ID  0.00245648:0.00248662:0.49485:0.838136:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037528 ES:SE:LP:AF:ID  -0.00152876:0.00483922:0.124939:0.037528:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838769 ES:SE:LP:AF:ID  0.00241654:0.00249364:0.481486:0.838769:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  0.00249268:0.00870047:0.113509:0.013776:rs181660517