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.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_3147.vcf.gz --id UKB-b:19234 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_3147.txt.gz --cohort_controls 265753 --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",
    "file_date": "2019-09-13T03:44:09.309813",
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    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-19234/ukb-b-19234.vcf.gz; Date=Sun May 10 14:21:34 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-19234/UKB-b-19234_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19234/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19234/UKB-b-19234_data.vcf.gz ...
Read summary statistics for 9674801 SNPs.
Dropped 13097 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, 1288733 SNPs remain.
After merging with regression SNP LD, 1288733 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2844 (0.0244)
Lambda GC: 1.674
Mean Chi^2: 2.7498
Intercept: 1.2011 (0.0176)
Ratio: 0.1149 (0.0101)
Analysis finished at Thu Oct 17 14:43:01 2019
Total time elapsed: 1.0m:51.69s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9495,
    "inflation_factor": 1.4295,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 362,
    "n_p_sig": 59686,
    "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": 159217,
    "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": 1288733,
    "ldsc_nsnp_merge_regression_ld": 1288733,
    "ldsc_observed_scale_h2_beta": 0.2844,
    "ldsc_observed_scale_h2_se": 0.0244,
    "ldsc_intercept_beta": 1.2011,
    "ldsc_intercept_se": 0.0176,
    "ldsc_lambda_gc": 1.674,
    "ldsc_mean_chisq": 2.7498,
    "ldsc_ratio": 0.1149
}
 

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 9661769 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 9674801 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 8.625678e+00 5.749911e+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 7.884118e+07 5.629187e+07 828.0000000 3.256549e+07 6.944570e+07 1.145707e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.200000e-05 1.244450e-02 -0.2068640 -4.450000e-03 1.030000e-05 4.454600e-03 3.866430e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 8.266200e-03 7.353200e-03 0.0024625 2.999500e-03 4.931000e-03 1.112860e-02 1.266760e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.374942e-01 3.063325e-01 0.0000000 1.600000e-01 4.199997e-01 6.999999e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.374951e-01 3.063107e-01 0.0000000 1.559183e-01 4.157226e-01 7.024975e-01 9.999998e-01 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.065163e-01 2.569900e-01 0.0013180 1.442100e-02 8.227800e-02 3.224240e-01 9.986820e-01 ▇▂▁▁▁
numeric AF_reference 159217 0.9835431 NA NA NA NA NA NA NA 2.089750e-01 2.486176e-01 0.0000000 1.257990e-02 1.030350e-01 3.248800e-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 -0.0053496 0.0045175 0.2399999 0.2363364 0.623768 0.7821490 NA
1 54676 rs2462492 C T 0.0089475 0.0044674 0.0449997 0.0451932 0.400852 NA NA
1 86028 rs114608975 T C -0.0053185 0.0071682 0.4600002 0.4581160 0.103356 0.0277556 NA
1 91536 rs6702460 G T -0.0002411 0.0044027 0.9599999 0.9563230 0.456893 0.4207270 NA
1 234313 rs8179466 C T -0.0098644 0.0086604 0.2500000 0.2546925 0.074614 NA NA
1 534192 rs6680723 C T -0.0016147 0.0050273 0.7499995 0.7480641 0.240666 NA NA
1 546697 rs12025928 A G 0.0199062 0.0062720 0.0015000 0.0015044 0.913402 NA NA
1 693731 rs12238997 A G -0.0069206 0.0042110 0.1000000 0.1002872 0.116479 0.1417730 NA
1 705882 rs72631875 G A -0.0085296 0.0061742 0.1700000 0.1671300 0.067530 0.0315495 NA
1 706368 rs55727773 A G -0.0022530 0.0031259 0.4700002 0.4710641 0.516350 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0017074 0.0066042 0.8000000 0.7959928 0.042041 0.0473243 NA
22 51219766 rs182321900 C T -0.0096319 0.0305193 0.7499995 0.7523059 0.001975 NA NA
22 51220146 rs868950473 C T -0.0102903 0.0303148 0.7300002 0.7342722 0.002014 NA NA
22 51221190 rs369304721 G A 0.0043219 0.0065844 0.5099998 0.5115756 0.049828 NA NA
22 51221731 rs115055839 T C -0.0019402 0.0049292 0.6899999 0.6938697 0.073394 0.0625000 NA
22 51222100 rs114553188 G T -0.0012487 0.0058012 0.8300000 0.8295789 0.054628 0.0880591 NA
22 51223637 rs375798137 G A -0.0015483 0.0058284 0.7899998 0.7905108 0.054268 0.0788738 NA
22 51229805 rs9616985 T C -0.0016476 0.0049469 0.7400005 0.7390851 0.073231 0.0730831 NA
22 51232488 rs376461333 A G -0.0088095 0.0116653 0.4500005 0.4501339 0.020022 NA NA
22 51237063 rs3896457 T C -0.0028709 0.0030322 0.3400001 0.3437335 0.297736 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623768 ES:SE:LP:AF:ID  -0.00534956:0.00451747:0.619789:0.623768:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400852 ES:SE:LP:AF:ID  0.00894754:0.0044674:1.34679:0.400852:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103356 ES:SE:LP:AF:ID  -0.00531848:0.00716822:0.337242:0.103356:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456893 ES:SE:LP:AF:ID  -0.00024113:0.00440272:0.0177288:0.456893:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074614 ES:SE:LP:AF:ID  -0.00986444:0.00866042:0.60206:0.074614:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240666 ES:SE:LP:AF:ID  -0.00161474:0.00502732:0.124939:0.240666:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913402 ES:SE:LP:AF:ID  0.0199062:0.00627198:2.82391:0.913402:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116479 ES:SE:LP:AF:ID  -0.00692059:0.00421098:1:0.116479:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06753  ES:SE:LP:AF:ID  -0.00852959:0.00617422:0.769551:0.06753:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51635  ES:SE:LP:AF:ID  -0.00225301:0.00312593:0.327902:0.51635:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032869 ES:SE:LP:AF:ID  -0.00149645:0.0079026:0.0705811:0.032869:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036472 ES:SE:LP:AF:ID  -0.00214742:0.00717734:0.119186:0.036472:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036591 ES:SE:LP:AF:ID  -0.000545382:0.00714989:0.0268721:0.036591:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036304 ES:SE:LP:AF:ID  -0.000468462:0.00720055:0.0222764:0.036304:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016401 ES:SE:LP:AF:ID  0.00251081:0.0110435:0.0861861:0.016401:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036814 ES:SE:LP:AF:ID  -0.000146736:0.00712306:0.00877392:0.036814:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036918 ES:SE:LP:AF:ID  -0.000666843:0.0070974:0.0315171:0.036918:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101106 ES:SE:LP:AF:ID  0.0029197:0.00516229:0.244125:0.101106:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959291 ES:SE:LP:AF:ID  -0.000736973:0.00684329:0.0409586:0.959291:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031365 ES:SE:LP:AF:ID  -0.00199144:0.0124018:0.0604807:0.031365:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053453 ES:SE:LP:AF:ID  0.00639704:0.00980033:0.29243:0.053453:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036459 ES:SE:LP:AF:ID  -0.00160887:0.00714125:0.0861861:0.036459:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036767 ES:SE:LP:AF:ID  -0.00209528:0.00707615:0.113509:0.036767:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843248 ES:SE:LP:AF:ID  0.00548487:0.00365369:0.886057:0.843248:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056046 ES:SE:LP:AF:ID  -0.0106849:0.00590451:1.1549:0.056046:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122476 ES:SE:LP:AF:ID  -0.00787315:0.00399454:1.3098:0.122476:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025604 ES:SE:LP:AF:ID  -0.00122632:0.00986758:0.0457575:0.025604:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12173  ES:SE:LP:AF:ID  -0.00812756:0.00399574:1.37675:0.12173:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132455 ES:SE:LP:AF:ID  -0.00711239:0.00394113:1.14874:0.132455:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.010991 ES:SE:LP:AF:ID  -0.0147789:0.0144731:0.508638:0.010991:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.00576  ES:SE:LP:AF:ID  -0.0140166:0.018415:0.346787:0.00576:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002278 ES:SE:LP:AF:ID  0.0487528:0.030938:0.920819:0.002278:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036687 ES:SE:LP:AF:ID  -0.000536888:0.00700343:0.0268721:0.036687:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838959 ES:SE:LP:AF:ID  0.00401028:0.0035383:0.585027:0.838959:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838586 ES:SE:LP:AF:ID  0.00399029:0.00353454:0.585027:0.838586:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869675 ES:SE:LP:AF:ID  0.0051491:0.00379165:0.769551:0.869675:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129962 ES:SE:LP:AF:ID  -0.00534197:0.00379897:0.79588:0.129962:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037186 ES:SE:LP:AF:ID  2.02215e-06:0.00688482:-0:0.037186:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037424 ES:SE:LP:AF:ID  1.90913e-05:0.00684165:-0:0.037424:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869017 ES:SE:LP:AF:ID  0.00496565:0.00378423:0.721246:0.869017:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869099 ES:SE:LP:AF:ID  0.00491962:0.0037855:0.721246:0.869099:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037399 ES:SE:LP:AF:ID  -0.000217549:0.00687075:0.0132283:0.037399:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869022 ES:SE:LP:AF:ID  0.00494956:0.00378427:0.721246:0.869022:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00515  ES:SE:LP:AF:ID  0.0190445:0.0193614:0.481486:0.00515:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005114 ES:SE:LP:AF:ID  0.0200902:0.0194148:0.522879:0.005114:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838018 ES:SE:LP:AF:ID  0.00360961:0.00352425:0.508638:0.838018:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037416 ES:SE:LP:AF:ID  -0.000477262:0.00688032:0.0268721:0.037416:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838653 ES:SE:LP:AF:ID  0.00379966:0.00353421:0.552842:0.838653:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.014036 ES:SE:LP:AF:ID  0.0196265:0.0122:0.958607:0.014036:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005534 ES:SE:LP:AF:ID  -0.0266457:0.0190988:0.79588:0.005534:rs184270342