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_24014.vcf.gz --id UKB-b:1100 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_24014.txt.gz --cohort_cases 31833 --cohort_controls 424547 --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-1100/UKB-b-1100_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1100/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-1100/UKB-b-1100_data.vcf.gz ...
Read summary statistics for 7595574 SNPs.
Dropped 5341 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, 1277591 SNPs remain.
After merging with regression SNP LD, 1277591 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0004 (0.001)
Lambda GC: 1.0367
Mean Chi^2: 1.0366
Intercept: 1.0334 (0.0058)
Ratio: 0.9118 (0.159)
Analysis finished at Thu Oct 17 14:41:47 2019
Total time elapsed: 1.0m:28.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9404,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 7.3662e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 70554,
    "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": 1277591,
    "ldsc_nsnp_merge_regression_ld": 1277591,
    "ldsc_observed_scale_h2_beta": 0.0004,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0334,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 1.0367,
    "ldsc_mean_chisq": 1.0366,
    "ldsc_ratio": 0.9126
}

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 7590256 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 7595574 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 8.663172e+00 5.764444e+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 7.866593e+07 5.643884e+07 828.0000000 3.219481e+07 6.910630e+07 1.145586e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.400000e-06 1.207000e-03 -0.0117779 -5.873000e-04 1.800000e-06 5.933000e-04 1.093180e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.041500e-03 5.704000e-04 0.0005146 5.897000e-04 7.947000e-04 1.346400e-03 6.175800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.938405e-01 2.901117e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.938400e-01 2.900854e-01 0.0000000 2.404563e-01 4.924915e-01 7.447235e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.571743e-01 2.608438e-01 0.0109950 4.394100e-02 1.530970e-01 4.061970e-01 9.890050e-01 ▇▂▂▁▁
numeric AF_reference 70554 0.9907112 NA NA NA NA NA NA NA 2.561020e-01 2.526931e-01 0.0000000 4.852240e-02 1.673320e-01 4.003590e-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 -0.0002076 0.0009470 0.8300000 0.8264982 0.623756 0.7821490 NA
1 54676 rs2462492 C T 0.0001980 0.0009384 0.8300000 0.8328483 0.400407 NA NA
1 86028 rs114608975 T C -0.0001361 0.0015004 0.9299999 0.9277285 0.103555 0.0277556 NA
1 91536 rs6702460 G T 0.0009102 0.0009238 0.3200000 0.3244631 0.456805 0.4207270 NA
1 234313 rs8179466 C T -0.0015067 0.0018209 0.4100001 0.4079822 0.074538 NA NA
1 534192 rs6680723 C T -0.0020532 0.0010551 0.0519996 0.0516664 0.240997 NA NA
1 546697 rs12025928 A G 0.0018210 0.0013170 0.1700000 0.1667699 0.913520 NA NA
1 693731 rs12238997 A G 0.0002076 0.0008841 0.8100000 0.8143769 0.116381 0.1417730 NA
1 705882 rs72631875 G A -0.0017928 0.0012966 0.1700000 0.1667773 0.067232 0.0315495 NA
1 706368 rs55727773 A G -0.0006041 0.0006552 0.3599996 0.3565190 0.515569 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0002766 0.0007903 0.7300002 0.7263333 0.137926 0.2052720 NA
22 51219387 rs9616832 T C -0.0004910 0.0010260 0.6300007 0.6322585 0.073706 0.0654952 NA
22 51219704 rs147475742 G A -0.0004891 0.0013752 0.7199992 0.7220747 0.041920 0.0473243 NA
22 51221190 rs369304721 G A -0.0003884 0.0013731 0.7800007 0.7773092 0.049688 NA NA
22 51221731 rs115055839 T C -0.0005206 0.0010266 0.6100002 0.6120805 0.073200 0.0625000 NA
22 51222100 rs114553188 G T 0.0013116 0.0012084 0.2800000 0.2777347 0.054461 0.0880591 NA
22 51223637 rs375798137 G A 0.0013801 0.0012142 0.2599998 0.2556873 0.054091 0.0788738 NA
22 51229805 rs9616985 T C -0.0005831 0.0010303 0.5700002 0.5714055 0.073035 0.0730831 NA
22 51232488 rs376461333 A G 0.0044606 0.0024266 0.0659994 0.0660340 0.020045 NA NA
22 51237063 rs3896457 T C -0.0009694 0.0006300 0.1199999 0.1238693 0.297983 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623756 ES:SE:LP:AF:ID  -0.00020758:0.000947011:0.0809219:0.623756:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  0.000198049:0.000938399:0.0809219:0.400407:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103555 ES:SE:LP:AF:ID  -0.000136091:0.0015004:0.0315171:0.103555:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456805 ES:SE:LP:AF:ID  0.000910235:0.000923789:0.49485:0.456805:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074538 ES:SE:LP:AF:ID  -0.00150667:0.00182086:0.387216:0.074538:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240997 ES:SE:LP:AF:ID  -0.0020532:0.00105514:1.284:0.240997:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91352  ES:SE:LP:AF:ID  0.00182096:0.001317:0.769551:0.91352:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116381 ES:SE:LP:AF:ID  0.000207563:0.000884062:0.091515:0.116381:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067232 ES:SE:LP:AF:ID  -0.00179275:0.00129662:0.769551:0.067232:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515569 ES:SE:LP:AF:ID  -0.000604123:0.000655218:0.443698:0.515569:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033    ES:SE:LP:AF:ID  0.00271214:0.00165161:1:0.033:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036611 ES:SE:LP:AF:ID  0.00253467:0.00150029:1.04096:0.036611:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036726 ES:SE:LP:AF:ID  0.00250348:0.00149462:1.02687:0.036726:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036422 ES:SE:LP:AF:ID  0.00247305:0.00150547:1:0.036422:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01643  ES:SE:LP:AF:ID  0.0020433:0.00231558:0.420216:0.01643:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036964 ES:SE:LP:AF:ID  0.00263826:0.00148872:1.11919:0.036964:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037061 ES:SE:LP:AF:ID  0.00240118:0.00148362:0.958607:0.037061:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101221 ES:SE:LP:AF:ID  -0.000931662:0.00108079:0.408935:0.101221:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959116 ES:SE:LP:AF:ID  -0.00341248:0.00143106:1.76955:0.959116:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031451 ES:SE:LP:AF:ID  -0.00114732:0.00259649:0.180456:0.031451:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053252 ES:SE:LP:AF:ID  -0.0024056:0.00206649:0.619789:0.053252:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036579 ES:SE:LP:AF:ID  0.00248974:0.00149325:1.02228:0.036579:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.0369   ES:SE:LP:AF:ID  0.0024258:0.00147957:1:0.0369:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843173 ES:SE:LP:AF:ID  -0.00127817:0.000766241:1.02228:0.843173:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055948 ES:SE:LP:AF:ID  0.00112489:0.00124041:0.443698:0.055948:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12237  ES:SE:LP:AF:ID  0.000398432:0.000838603:0.200659:0.12237:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025756 ES:SE:LP:AF:ID  -0.000913941:0.00206168:0.180456:0.025756:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121613 ES:SE:LP:AF:ID  0.00044479:0.000838945:0.221849:0.121613:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132352 ES:SE:LP:AF:ID  0.000983906:0.000826978:0.638272:0.132352:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011107 ES:SE:LP:AF:ID  0.00370197:0.003012:0.657577:0.011107:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036814 ES:SE:LP:AF:ID  0.00245959:0.00146461:1.03152:0.036814:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838895 ES:SE:LP:AF:ID  -0.00137513:0.000742015:1.19382:0.838895:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838528 ES:SE:LP:AF:ID  -0.0013659:0.000741226:1.18709:0.838528:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869711 ES:SE:LP:AF:ID  -0.000747427:0.000795284:0.455932:0.869711:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129936 ES:SE:LP:AF:ID  0.000697854:0.000796924:0.420216:0.129936:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037328 ES:SE:LP:AF:ID  0.00226634:0.00143968:0.920819:0.037328:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037572 ES:SE:LP:AF:ID  0.00219976:0.00143056:0.920819:0.037572:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869056 ES:SE:LP:AF:ID  -0.000741347:0.000793742:0.455932:0.869056:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  -0.000675212:0.000794057:0.39794:0.869154:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037531 ES:SE:LP:AF:ID  0.00224518:0.00143675:0.920819:0.037531:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86906  ES:SE:LP:AF:ID  -0.000747357:0.00079373:0.455932:0.86906:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837976 ES:SE:LP:AF:ID  -0.0013505:0.000739146:1.16749:0.837976:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037544 ES:SE:LP:AF:ID  0.00217875:0.00143878:0.886057:0.037544:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838606 ES:SE:LP:AF:ID  -0.00135004:0.00074122:1.16115:0.838606:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  -0.00183586:0.00258741:0.318759:0.013775:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839716 ES:SE:LP:AF:ID  -0.00142705:0.000751248:1.24413:0.839716:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869338 ES:SE:LP:AF:ID  -0.000744517:0.000792802:0.455932:0.869338:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868886 ES:SE:LP:AF:ID  -0.000776084:0.000790813:0.481486:0.868886:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867838 ES:SE:LP:AF:ID  -0.000629532:0.000789298:0.366532:0.867838:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869028 ES:SE:LP:AF:ID  -0.000740837:0.000791453:0.455932:0.869028:rs4951929