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_5162.vcf.gz --id UKB-b:5309 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5162.txt.gz --cohort_controls 51767 --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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}

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-5309/UKB-b-5309_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5309/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5309/UKB-b-5309_data.vcf.gz ...
Read summary statistics for 8295075 SNPs.
Dropped 6709 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, 1284538 SNPs remain.
After merging with regression SNP LD, 1284538 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0394 (0.0087)
Lambda GC: 1.0422
Mean Chi^2: 1.0487
Intercept: 1.0089 (0.0064)
Ratio: 0.1832 (0.1308)
Analysis finished at Thu Oct 17 14:46:40 2019
Total time elapsed: 1.0m:26.74s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9448,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.2174e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 78019,
    "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": 1284538,
    "ldsc_nsnp_merge_regression_ld": 1284538,
    "ldsc_observed_scale_h2_beta": 0.0394,
    "ldsc_observed_scale_h2_se": 0.0087,
    "ldsc_intercept_beta": 1.0089,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0422,
    "ldsc_mean_chisq": 1.0487,
    "ldsc_ratio": 0.1828
}

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 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 8288396 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 8295075 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 8.655592e+00 5.762561e+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 7.873251e+07 5.638983e+07 828.0000000 3.232072e+07 6.921501e+07 1.145521e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.200000e-06 1.664970e-02 -0.1791000 -7.391000e-03 2.060000e-05 7.392200e-03 1.759880e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.397740e-02 8.948700e-03 0.0059666 6.968700e-03 9.961400e-03 1.863040e-02 9.254000e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.949667e-01 2.901047e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.949666e-01 2.900774e-01 0.0000000 2.424700e-01 4.935855e-01 7.460214e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.375731e-01 2.602435e-01 0.0067620 3.028000e-02 1.256650e-01 3.762420e-01 9.932380e-01 ▇▂▂▁▁
numeric AF_reference 78019 0.9905945 NA NA NA NA NA NA NA 2.370847e-01 2.521535e-01 0.0000000 3.015180e-02 1.413740e-01 3.724040e-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 0.0146917 0.0110107 0.1800002 0.1821019 0.622552 0.7821490 NA
1 54676 rs2462492 C T 0.0014633 0.0109254 0.8900000 0.8934528 0.400239 NA NA
1 86028 rs114608975 T C -0.0024637 0.0174238 0.8900000 0.8875537 0.103841 0.0277556 NA
1 91536 rs6702460 G T 0.0232249 0.0107623 0.0309999 0.0309289 0.456533 0.4207270 NA
1 234313 rs8179466 C T -0.0137399 0.0210936 0.5099998 0.5148027 0.074618 NA NA
1 534192 rs6680723 C T 0.0022610 0.0123350 0.8499999 0.8545649 0.240322 NA NA
1 546697 rs12025928 A G 0.0147539 0.0152237 0.3300000 0.3324752 0.912530 NA NA
1 693731 rs12238997 A G -0.0054988 0.0102301 0.5900000 0.5909141 0.118128 0.1417730 NA
1 705882 rs72631875 G A 0.0042071 0.0150376 0.7800007 0.7796529 0.067259 0.0315495 NA
1 706368 rs55727773 A G 0.0059740 0.0075983 0.4299995 0.4317305 0.514809 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0012763 0.0091737 0.8900000 0.8893524 0.136924 0.2052720 NA
22 51219387 rs9616832 T C 0.0053583 0.0119088 0.6499995 0.6527510 0.072794 0.0654952 NA
22 51219704 rs147475742 G A 0.0059683 0.0158035 0.7099994 0.7056860 0.042234 0.0473243 NA
22 51221190 rs369304721 G A 0.0036578 0.0158724 0.8200001 0.8177433 0.049443 NA NA
22 51221731 rs115055839 T C 0.0052711 0.0119110 0.6600001 0.6580963 0.072382 0.0625000 NA
22 51222100 rs114553188 G T 0.0044694 0.0140401 0.7499995 0.7502360 0.054139 0.0880591 NA
22 51223637 rs375798137 G A 0.0048563 0.0141101 0.7300002 0.7307186 0.053770 0.0788738 NA
22 51229805 rs9616985 T C 0.0062588 0.0119600 0.5999997 0.6007578 0.072210 0.0730831 NA
22 51232488 rs376461333 A G -0.0119084 0.0282784 0.6700003 0.6736726 0.020072 NA NA
22 51237063 rs3896457 T C 0.0096812 0.0073226 0.1900002 0.1861327 0.298970 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.622552 ES:SE:LP:AF:ID  0.0146917:0.0110107:0.744727:0.622552:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400239 ES:SE:LP:AF:ID  0.00146331:0.0109254:0.05061:0.400239:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103841 ES:SE:LP:AF:ID  -0.00246373:0.0174238:0.05061:0.103841:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456533 ES:SE:LP:AF:ID  0.0232249:0.0107623:1.50864:0.456533:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074618 ES:SE:LP:AF:ID  -0.0137399:0.0210936:0.29243:0.074618:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240322 ES:SE:LP:AF:ID  0.00226097:0.012335:0.0705811:0.240322:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91253  ES:SE:LP:AF:ID  0.0147539:0.0152237:0.481486:0.91253:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.118128 ES:SE:LP:AF:ID  -0.0054988:0.0102301:0.229148:0.118128:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067259 ES:SE:LP:AF:ID  0.00420709:0.0150376:0.107905:0.067259:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514809 ES:SE:LP:AF:ID  0.00597404:0.0075983:0.366532:0.514809:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033305 ES:SE:LP:AF:ID  -0.00389891:0.0190579:0.0757207:0.033305:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03699  ES:SE:LP:AF:ID  -0.00701458:0.0173141:0.161151:0.03699:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037057 ES:SE:LP:AF:ID  -0.0084408:0.0172625:0.207608:0.037057:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036735 ES:SE:LP:AF:ID  -0.00797895:0.0173882:0.187087:0.036735:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016623 ES:SE:LP:AF:ID  -0.0283458:0.0267853:0.537602:0.016623:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037326 ES:SE:LP:AF:ID  -0.00573553:0.0171871:0.130768:0.037326:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037387 ES:SE:LP:AF:ID  -0.00678513:0.0171389:0.161151:0.037387:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100314 ES:SE:LP:AF:ID  -0.00503371:0.0126288:0.161151:0.100314:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95832  ES:SE:LP:AF:ID  -0.00332899:0.0164721:0.0757207:0.95832:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031987 ES:SE:LP:AF:ID  0.023951:0.0300253:0.366532:0.031987:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052621 ES:SE:LP:AF:ID  -0.0173035:0.0242018:0.327902:0.052621:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036832 ES:SE:LP:AF:ID  -0.00685169:0.0172649:0.161151:0.036832:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037131 ES:SE:LP:AF:ID  -0.00426069:0.0171188:0.09691:0.037131:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841171 ES:SE:LP:AF:ID  0.00562322:0.00887804:0.275724:0.841171:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055884 ES:SE:LP:AF:ID  0.0117654:0.0144784:0.376751:0.055884:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123746 ES:SE:LP:AF:ID  -0.0057712:0.00972815:0.259637:0.123746:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02569  ES:SE:LP:AF:ID  0.023432:0.0240589:0.481486:0.02569:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122861 ES:SE:LP:AF:ID  -0.00554563:0.00973467:0.244125:0.122861:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133462 ES:SE:LP:AF:ID  -0.0027316:0.00960117:0.107905:0.133462:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011304 ES:SE:LP:AF:ID  0.0272834:0.0345105:0.366532:0.011304:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.037129 ES:SE:LP:AF:ID  -0.00270427:0.0169186:0.0604807:0.037129:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837082 ES:SE:LP:AF:ID  0.00517708:0.00860137:0.259637:0.837082:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836691 ES:SE:LP:AF:ID  0.00460354:0.00859168:0.229148:0.836691:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868061 ES:SE:LP:AF:ID  0.00312532:0.00921761:0.136677:0.868061:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131593 ES:SE:LP:AF:ID  -0.00152525:0.0092348:0.0604807:0.131593:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037522 ES:SE:LP:AF:ID  -0.00278392:0.0166543:0.0604807:0.037522:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037785 ES:SE:LP:AF:ID  -0.00260651:0.0165479:0.0604807:0.037785:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867426 ES:SE:LP:AF:ID  0.00250709:0.0092007:0.102373:0.867426:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867525 ES:SE:LP:AF:ID  0.00254788:0.00920459:0.107905:0.867525:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037696 ES:SE:LP:AF:ID  -0.00228544:0.0166199:0.05061:0.037696:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867405 ES:SE:LP:AF:ID  0.00259744:0.00919991:0.107905:0.867405:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836267 ES:SE:LP:AF:ID  0.00472702:0.00857309:0.236572:0.836267:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037718 ES:SE:LP:AF:ID  -0.00294073:0.0166415:0.0655015:0.037718:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836828 ES:SE:LP:AF:ID  0.00516022:0.00859548:0.259637:0.836828:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013071 ES:SE:LP:AF:ID  0.024446:0.0309205:0.366532:0.013071:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.838005 ES:SE:LP:AF:ID  0.00648308:0.00870741:0.337242:0.838005:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.867786 ES:SE:LP:AF:ID  0.00336677:0.00919151:0.148742:0.867786:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867396 ES:SE:LP:AF:ID  0.00345795:0.0091711:0.148742:0.867396:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866153 ES:SE:LP:AF:ID  0.00181699:0.00914612:0.0757207:0.866153:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867519 ES:SE:LP:AF:ID  0.00370252:0.00917868:0.161151:0.867519:rs4951929