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_4631.vcf.gz --id UKB-b:18674 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_4631.txt.gz --cohort_cases 54234 --cohort_controls 92308 --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-18674/UKB-b-18674_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18674/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18674/UKB-b-18674_data.vcf.gz ...
Read summary statistics for 8360767 SNPs.
Dropped 6850 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, 1284761 SNPs remain.
After merging with regression SNP LD, 1284761 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0531 (0.005)
Lambda GC: 1.1332
Mean Chi^2: 1.1644
Intercept: 1.0118 (0.0079)
Ratio: 0.0716 (0.0481)
Analysis finished at Thu Oct 17 14:41:56 2019
Total time elapsed: 1.0m:36.58s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.945,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 1.6704e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 39,
    "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": 78888,
    "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": 1284761,
    "ldsc_nsnp_merge_regression_ld": 1284761,
    "ldsc_observed_scale_h2_beta": 0.0531,
    "ldsc_observed_scale_h2_se": 0.005,
    "ldsc_intercept_beta": 1.0118,
    "ldsc_intercept_se": 0.0079,
    "ldsc_lambda_gc": 1.1332,
    "ldsc_mean_chisq": 1.1644,
    "ldsc_ratio": 0.0718
}

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 8353948 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 8360767 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 8.654288e+00 5.761971e+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 7.874220e+07 5.638459e+07 828.0000000 3.233733e+07 6.924243e+07 1.145520e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.700000e-06 4.992600e-03 -0.0487768 -2.243900e-03 -1.320000e-05 2.227800e-03 5.239170e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.064100e-03 2.637700e-03 0.0017100 2.000400e-03 2.876500e-03 5.435200e-03 2.599390e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.825833e-01 2.940718e-01 0.0000000 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▆▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.825827e-01 2.940466e-01 0.0000000 2.231278e-01 4.772187e-01 7.377034e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.358266e-01 2.601196e-01 0.0064540 2.920300e-02 1.231560e-01 3.734460e-01 9.935460e-01 ▇▂▂▁▁
numeric AF_reference 78888 0.9905645 NA NA NA NA NA NA NA 2.353770e-01 2.520303e-01 0.0000000 2.855430e-02 1.391770e-01 3.698080e-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 -0.0072472 0.0031496 0.0210000 0.0213902 0.623774 0.7821490 NA
1 54676 rs2462492 C T 0.0020822 0.0031309 0.5099998 0.5060202 0.399472 NA NA
1 86028 rs114608975 T C 0.0108768 0.0049917 0.0290001 0.0293334 0.103775 0.0277556 NA
1 91536 rs6702460 G T -0.0026127 0.0030835 0.4000000 0.3968178 0.456288 0.4207270 NA
1 234313 rs8179466 C T -0.0074894 0.0060850 0.2200002 0.2183944 0.074577 NA NA
1 534192 rs6680723 C T 0.0084105 0.0035258 0.0170000 0.0170594 0.241247 NA NA
1 546697 rs12025928 A G 0.0005876 0.0043724 0.8900000 0.8930986 0.912986 NA NA
1 693731 rs12238997 A G 0.0029246 0.0029381 0.3200000 0.3195359 0.117007 0.1417730 NA
1 705882 rs72631875 G A 0.0028224 0.0042999 0.5099998 0.5115715 0.067605 0.0315495 NA
1 706368 rs55727773 A G -0.0019990 0.0021769 0.3599996 0.3584806 0.515072 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0014091 0.0026364 0.5900000 0.5930168 0.136990 0.2052720 NA
22 51219387 rs9616832 T C -0.0009005 0.0034270 0.7899998 0.7927317 0.072831 0.0654952 NA
22 51219704 rs147475742 G A -0.0042470 0.0045719 0.3500000 0.3529216 0.041770 0.0473243 NA
22 51221190 rs369304721 G A -0.0030666 0.0045852 0.5000000 0.5036312 0.049179 NA NA
22 51221731 rs115055839 T C -0.0009287 0.0034290 0.7899998 0.7865262 0.072323 0.0625000 NA
22 51222100 rs114553188 G T 0.0052356 0.0040246 0.1900002 0.1932842 0.054281 0.0880591 NA
22 51223637 rs375798137 G A 0.0046021 0.0040450 0.2599998 0.2552333 0.053901 0.0788738 NA
22 51229805 rs9616985 T C -0.0007658 0.0034417 0.8200001 0.8239262 0.072175 0.0730831 NA
22 51232488 rs376461333 A G 0.0059595 0.0080841 0.4600002 0.4610128 0.020095 NA NA
22 51237063 rs3896457 T C -0.0002681 0.0020931 0.9000000 0.8980696 0.297834 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623774 ES:SE:LP:AF:ID  -0.00724724:0.00314957:1.67778:0.623774:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399472 ES:SE:LP:AF:ID  0.00208217:0.00313086:0.29243:0.399472:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103775 ES:SE:LP:AF:ID  0.0108768:0.0049917:1.5376:0.103775:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456288 ES:SE:LP:AF:ID  -0.00261268:0.00308347:0.39794:0.456288:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074577 ES:SE:LP:AF:ID  -0.00748941:0.00608495:0.657577:0.074577:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241247 ES:SE:LP:AF:ID  0.00841048:0.00352578:1.76955:0.241247:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912986 ES:SE:LP:AF:ID  0.000587576:0.00437235:0.05061:0.912986:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117007 ES:SE:LP:AF:ID  0.00292465:0.00293813:0.49485:0.117007:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067605 ES:SE:LP:AF:ID  0.00282241:0.00429988:0.29243:0.067605:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515072 ES:SE:LP:AF:ID  -0.00199896:0.00217689:0.443698:0.515072:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033515 ES:SE:LP:AF:ID  0.00242237:0.00544228:0.180456:0.033515:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037209 ES:SE:LP:AF:ID  0.000547999:0.00494289:0.0409586:0.037209:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  0.000963761:0.00492372:0.0757207:0.037336:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03699  ES:SE:LP:AF:ID  8.05207e-05:0.00496084:0.00436481:0.03699:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016295 ES:SE:LP:AF:ID  0.000340006:0.00775544:0.0132283:0.016295:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037571 ES:SE:LP:AF:ID  0.000933438:0.00490426:0.0705811:0.037571:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037661 ES:SE:LP:AF:ID  0.00074764:0.00488904:0.0555173:0.037661:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101412 ES:SE:LP:AF:ID  -0.00474532:0.00358513:0.721246:0.101412:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958407 ES:SE:LP:AF:ID  -0.00289822:0.00471736:0.267606:0.958407:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031655 ES:SE:LP:AF:ID  4.95742e-05:0.00862612:-0:0.031655:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052641 ES:SE:LP:AF:ID  -0.000789294:0.00695889:0.0409586:0.052641:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037138 ES:SE:LP:AF:ID  0.00132203:0.00492256:0.102373:0.037138:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037462 ES:SE:LP:AF:ID  0.000959757:0.00487937:0.0757207:0.037462:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841987 ES:SE:LP:AF:ID  -0.00403791:0.00254437:0.958607:0.841987:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056199 ES:SE:LP:AF:ID  0.00766838:0.00412897:1.20066:0.056199:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122945 ES:SE:LP:AF:ID  0.00370074:0.00278888:0.744727:0.122945:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02576  ES:SE:LP:AF:ID  0.00637782:0.00685696:0.455932:0.02576:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122154 ES:SE:LP:AF:ID  0.00364501:0.00279033:0.721246:0.122154:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133474 ES:SE:LP:AF:ID  0.00260737:0.00274504:0.468521:0.133474:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011237 ES:SE:LP:AF:ID  -0.00391083:0.009962:0.161151:0.011237:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.037405 ES:SE:LP:AF:ID  -7.98131e-05:0.00482921:0.00436481:0.037405:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837695 ES:SE:LP:AF:ID  -0.00433299:0.00246366:1.10237:0.837695:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837305 ES:SE:LP:AF:ID  -0.00418745:0.00246089:1.05061:0.837305:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868953 ES:SE:LP:AF:ID  -0.00520426:0.00264135:1.3098:0.868953:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130753 ES:SE:LP:AF:ID  0.00525147:0.00264637:1.3279:0.130753:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03791  ES:SE:LP:AF:ID  0.000375072:0.00474876:0.0268721:0.03791:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038157 ES:SE:LP:AF:ID  0.00056098:0.00471917:0.0409586:0.038157:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868273 ES:SE:LP:AF:ID  -0.00520094:0.00263602:1.31876:0.868273:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868383 ES:SE:LP:AF:ID  -0.0051827:0.00263725:1.3098:0.868383:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038092 ES:SE:LP:AF:ID  0.000723328:0.00473948:0.0555173:0.038092:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868272 ES:SE:LP:AF:ID  -0.00512199:0.00263586:1.284:0.868272:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836795 ES:SE:LP:AF:ID  -0.00442568:0.00245466:1.14874:0.836795:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038106 ES:SE:LP:AF:ID  0.000586722:0.00474583:0.0457575:0.038106:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83743  ES:SE:LP:AF:ID  -0.00456195:0.00246148:1.19382:0.83743:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013285 ES:SE:LP:AF:ID  0.000177239:0.00879637:0.00877392:0.013285:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.838642 ES:SE:LP:AF:ID  -0.00560261:0.00249492:1.60206:0.838642:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.86859  ES:SE:LP:AF:ID  -0.00528292:0.00263322:1.34679:0.86859:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868143 ES:SE:LP:AF:ID  -0.00507557:0.00262667:1.27572:0.868143:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86696  ES:SE:LP:AF:ID  -0.00492294:0.00262052:1.22185:0.86696:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868285 ES:SE:LP:AF:ID  -0.00517225:0.00262874:1.3098:0.868285:rs4951929