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_2159.vcf.gz --id UKB-b:12026 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2159.txt.gz --cohort_cases 14480 --cohort_controls 403640 --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-12026/UKB-b-12026_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12026/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12026/UKB-b-12026_data.vcf.gz ...
Read summary statistics for 6477984 SNPs.
Dropped 3486 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, 1242553 SNPs remain.
After merging with regression SNP LD, 1242553 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0122 (0.0013)
Lambda GC: 1.139
Mean Chi^2: 1.1379
Intercept: 1.0371 (0.0077)
Ratio: 0.2687 (0.0557)
Analysis finished at Thu Oct 17 14:42:44 2019
Total time elapsed: 1.0m:27.77s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9305,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 7.4589e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 29,
    "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": 59407,
    "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": 1242553,
    "ldsc_nsnp_merge_regression_ld": 1242553,
    "ldsc_observed_scale_h2_beta": 0.0122,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0371,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.139,
    "ldsc_mean_chisq": 1.1379,
    "ldsc_ratio": 0.269
}

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 6474519 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 6477984 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 8.667585e+00 5.763866e+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 7.857068e+07 5.647907e+07 828.0000000 3.203986e+07 6.900029e+07 1.144745e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.500000e-06 7.197000e-04 -0.0065522 -4.092000e-04 3.200000e-06 4.166000e-04 6.412900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.347000e-04 2.515000e-04 0.0003855 4.302000e-04 5.329000e-04 7.777000e-04 3.345700e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.798378e-01 2.938332e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.798394e-01 2.938077e-01 0.0000000 2.206207e-01 4.713305e-01 7.347083e-01 1.000000e+00 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.939167e-01 2.572639e-01 0.0241720 7.742500e-02 2.048545e-01 4.557490e-01 9.758280e-01 ▇▃▂▂▁
numeric AF_reference 59407 0.9908294 NA NA NA NA NA NA NA 2.914054e-01 2.496791e-01 0.0000000 8.666130e-02 2.144570e-01 4.476840e-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 -0.0004934 0.0007094 0.4899999 0.4867338 0.623721 0.7821490 NA
1 54676 rs2462492 C T 0.0002327 0.0007028 0.7400005 0.7405572 0.400474 NA NA
1 86028 rs114608975 T C 0.0006762 0.0011232 0.5500004 0.5471460 0.103561 0.0277556 NA
1 91536 rs6702460 G T -0.0002517 0.0006920 0.7199992 0.7161026 0.456961 0.4207270 NA
1 234313 rs8179466 C T -0.0006475 0.0013650 0.6400000 0.6352541 0.074516 NA NA
1 534192 rs6680723 C T 0.0007380 0.0007904 0.3500000 0.3504628 0.241037 NA NA
1 546697 rs12025928 A G 0.0018050 0.0009851 0.0669993 0.0668992 0.913291 NA NA
1 693731 rs12238997 A G -0.0000344 0.0006619 0.9599999 0.9585279 0.116426 0.1417730 NA
1 705882 rs72631875 G A -0.0003755 0.0009706 0.6999999 0.6988573 0.067304 0.0315495 NA
1 706368 rs55727773 A G 0.0002816 0.0004906 0.5700002 0.5659828 0.515772 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0000365 0.0007670 0.9599999 0.9620426 0.073554 0.0826677 NA
22 51219006 rs28729663 G A 0.0008583 0.0005921 0.1499999 0.1471641 0.137854 0.2052720 NA
22 51219387 rs9616832 T C -0.0000024 0.0007685 1.0000000 0.9974597 0.073688 0.0654952 NA
22 51219704 rs147475742 G A -0.0008745 0.0010300 0.4000000 0.3958205 0.041919 0.0473243 NA
22 51221190 rs369304721 G A -0.0005395 0.0010286 0.5999997 0.5999367 0.049641 NA NA
22 51221731 rs115055839 T C -0.0000581 0.0007690 0.9400001 0.9397355 0.073171 0.0625000 NA
22 51222100 rs114553188 G T 0.0016598 0.0009050 0.0669993 0.0666432 0.054455 0.0880591 NA
22 51223637 rs375798137 G A 0.0017288 0.0009094 0.0569994 0.0572855 0.054084 0.0788738 NA
22 51229805 rs9616985 T C -0.0000740 0.0007717 0.9199999 0.9236219 0.073028 0.0730831 NA
22 51237063 rs3896457 T C -0.0001568 0.0004718 0.7400005 0.7396501 0.298121 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623721 ES:SE:LP:AF:ID  -0.00049342:0.000709433:0.309804:0.623721:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400474 ES:SE:LP:AF:ID  0.000232713:0.000702815:0.130768:0.400474:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103561 ES:SE:LP:AF:ID  0.000676244:0.00112325:0.259637:0.103561:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456961 ES:SE:LP:AF:ID  -0.000251657:0.000691988:0.142668:0.456961:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074516 ES:SE:LP:AF:ID  -0.00064749:0.00136502:0.19382:0.074516:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241037 ES:SE:LP:AF:ID  0.000738034:0.000790447:0.455932:0.241037:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913291 ES:SE:LP:AF:ID  0.00180497:0.000985057:1.17393:0.913291:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116426 ES:SE:LP:AF:ID  -3.44211e-05:0.000661931:0.0177288:0.116426:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067304 ES:SE:LP:AF:ID  -0.000375473:0.000970557:0.154902:0.067304:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515772 ES:SE:LP:AF:ID  0.000281609:0.000490627:0.244125:0.515772:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033009 ES:SE:LP:AF:ID  0.00119795:0.001237:0.481486:0.033009:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036645 ES:SE:LP:AF:ID  0.000775255:0.00112311:0.309804:0.036645:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036766 ES:SE:LP:AF:ID  0.000852186:0.00111885:0.346787:0.036766:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036459 ES:SE:LP:AF:ID  0.000821417:0.00112702:0.327902:0.036459:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.037004 ES:SE:LP:AF:ID  0.000703666:0.00111443:0.275724:0.037004:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037097 ES:SE:LP:AF:ID  0.00087622:0.00111068:0.366532:0.037097:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10117  ES:SE:LP:AF:ID  -0.00151781:0.000809422:1.21467:0.10117:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95912  ES:SE:LP:AF:ID  -0.00102659:0.00107199:0.468521:0.95912:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031463 ES:SE:LP:AF:ID  -0.00294362:0.00194534:0.886057:0.031463:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053314 ES:SE:LP:AF:ID  0.00225888:0.00154523:0.853872:0.053314:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036612 ES:SE:LP:AF:ID  0.000716522:0.00111789:0.283997:0.036612:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036926 ES:SE:LP:AF:ID  0.000772834:0.00110772:0.309804:0.036926:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843102 ES:SE:LP:AF:ID  -0.000298146:0.000573845:0.221849:0.843102:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055996 ES:SE:LP:AF:ID  0.000301516:0.000928525:0.124939:0.055996:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122435 ES:SE:LP:AF:ID  7.90605e-05:0.000627954:0.0457575:0.122435:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025689 ES:SE:LP:AF:ID  0.00124782:0.00154721:0.376751:0.025689:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12167  ES:SE:LP:AF:ID  7.90344e-05:0.000628216:0.0457575:0.12167:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132493 ES:SE:LP:AF:ID  0.000433297:0.000619079:0.318759:0.132493:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036833 ES:SE:LP:AF:ID  0.00087547:0.00109662:0.376751:0.036833:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838878 ES:SE:LP:AF:ID  -9.19927e-05:0.000555689:0.0604807:0.838878:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838503 ES:SE:LP:AF:ID  -0.000165393:0.000555091:0.113509:0.838503:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869727 ES:SE:LP:AF:ID  0.000139246:0.000595598:0.0861861:0.869727:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129957 ES:SE:LP:AF:ID  -4.19618e-05:0.000596767:0.0268721:0.129957:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037348 ES:SE:LP:AF:ID  0.000892504:0.00107807:0.387216:0.037348:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037591 ES:SE:LP:AF:ID  0.000787786:0.00107126:0.337242:0.037591:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  7.068e-05:0.00059444:0.0409586:0.869067:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869167 ES:SE:LP:AF:ID  4.91654e-05:0.000594682:0.0315171:0.869167:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037548 ES:SE:LP:AF:ID  0.000877248:0.00107595:0.387216:0.037548:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86907  ES:SE:LP:AF:ID  6.33317e-05:0.00059443:0.0362122:0.86907:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837954 ES:SE:LP:AF:ID  -0.000194821:0.000553573:0.142668:0.837954:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037559 ES:SE:LP:AF:ID  0.000881309:0.00107749:0.387216:0.037559:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838581 ES:SE:LP:AF:ID  -0.000143681:0.000555127:0.09691:0.838581:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839703 ES:SE:LP:AF:ID  -0.00012112:0.000562632:0.0809219:0.839703:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869347 ES:SE:LP:AF:ID  6.24558e-05:0.000593719:0.0362122:0.869347:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868889 ES:SE:LP:AF:ID  9.15917e-05:0.00059222:0.0555173:0.868889:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867848 ES:SE:LP:AF:ID  2.73581e-05:0.000591112:0.0177288:0.867848:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869041 ES:SE:LP:AF:ID  8.756e-05:0.000592709:0.0555173:0.869041:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869049 ES:SE:LP:AF:ID  8.86284e-05:0.000592754:0.0555173:0.869049:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869058 ES:SE:LP:AF:ID  8.95561e-05:0.000592769:0.0555173:0.869058:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869532 ES:SE:LP:AF:ID  8.79544e-05:0.000594391:0.0555173:0.869532:rs3131954