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.3": "<ID=AF,Number=A,Type=Float,Description=\"Alternate allele frequency in the association study\">",
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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_104160.vcf.gz --id UKB-b:2975 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_104160.txt.gz --cohort_controls 64949 --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-2975/UKB-b-2975_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2975/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2975/UKB-b-2975_data.vcf.gz ...
Read summary statistics for 8625255 SNPs.
Dropped 7372 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, 1285751 SNPs remain.
After merging with regression SNP LD, 1285751 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.014 (0.0062)
Lambda GC: 1.0155
Mean Chi^2: 1.0165
Intercept: 0.9988 (0.0052)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:44:40 2019
Total time elapsed: 1.0m:30.41s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 83101,
    "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": 1285751,
    "ldsc_nsnp_merge_regression_ld": 1285751,
    "ldsc_observed_scale_h2_beta": 0.014,
    "ldsc_observed_scale_h2_se": 0.0062,
    "ldsc_intercept_beta": 0.9988,
    "ldsc_intercept_se": 0.0052,
    "ldsc_lambda_gc": 1.0155,
    "ldsc_mean_chisq": 1.0165,
    "ldsc_ratio": -0.0727
}

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 8617917 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 8625255 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 8.650335e+00 5.760993e+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 7.877026e+07 5.637169e+07 828.0000000 3.238547e+07 6.929218e+07 1.145689e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.700000e-05 1.279480e-02 -0.1282820 -5.348600e-03 -2.410000e-05 5.296800e-03 1.486830e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.054220e-02 7.196500e-03 0.0041866 4.930400e-03 7.269700e-03 1.425110e-02 7.217570e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.977272e-01 2.894163e-01 0.0000003 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.977273e-01 2.893913e-01 0.0000003 2.464312e-01 4.975897e-01 7.482103e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291107e-01 2.594876e-01 0.0053890 2.518600e-02 1.138890e-01 3.626125e-01 9.946110e-01 ▇▂▁▁▁
numeric AF_reference 83101 0.9903654 NA NA NA NA NA NA NA 2.288600e-01 2.514584e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 0.0004779 0.0077160 0.9500000 0.9506167 0.623812 0.7821490 NA
1 54676 rs2462492 C T -0.0086655 0.0076935 0.2599998 0.2600234 0.399144 NA NA
1 86028 rs114608975 T C 0.0070506 0.0122469 0.5600000 0.5648158 0.103536 0.0277556 NA
1 91536 rs6702460 G T -0.0127155 0.0075671 0.0929994 0.0928874 0.455916 0.4207270 NA
1 234313 rs8179466 C T 0.0013174 0.0149650 0.9299999 0.9298491 0.074455 NA NA
1 534192 rs6680723 C T 0.0029830 0.0086186 0.7300002 0.7292603 0.242057 NA NA
1 546697 rs12025928 A G 0.0016330 0.0106938 0.8800001 0.8786299 0.912862 NA NA
1 693731 rs12238997 A G -0.0131584 0.0071864 0.0669993 0.0670992 0.117313 0.1417730 NA
1 705882 rs72631875 G A -0.0022455 0.0104750 0.8300000 0.8302605 0.067698 0.0315495 NA
1 706368 rs55727773 A G 0.0066678 0.0053343 0.2099999 0.2112999 0.513304 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0037273 0.0064881 0.5700002 0.5656383 0.136315 0.2052720 NA
22 51219387 rs9616832 T C 0.0085586 0.0084564 0.3100002 0.3114932 0.071797 0.0654952 NA
22 51219704 rs147475742 G A 0.0017118 0.0112492 0.8800001 0.8790543 0.041190 0.0473243 NA
22 51221190 rs369304721 G A 0.0112185 0.0113290 0.3200000 0.3220538 0.048372 NA NA
22 51221731 rs115055839 T C 0.0087935 0.0084582 0.2999998 0.2985102 0.071348 0.0625000 NA
22 51222100 rs114553188 G T -0.0006032 0.0098012 0.9500000 0.9509279 0.054850 0.0880591 NA
22 51223637 rs375798137 G A 0.0000742 0.0098524 0.9900000 0.9939904 0.054470 0.0788738 NA
22 51229805 rs9616985 T C 0.0091767 0.0084843 0.2800000 0.2794278 0.071253 0.0730831 NA
22 51232488 rs376461333 A G -0.0092408 0.0195410 0.6400000 0.6362900 0.020460 NA NA
22 51237063 rs3896457 T C 0.0063289 0.0051220 0.2200002 0.2166006 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  0.000477869:0.00771598:0.0222764:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  -0.00866551:0.00769354:0.585027:0.399144:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  0.00705058:0.0122469:0.251812:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  -0.0127155:0.00756713:1.03152:0.455916:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074455 ES:SE:LP:AF:ID  0.00131744:0.014965:0.0315171:0.074455:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  0.00298297:0.00861857:0.136677:0.242057:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912862 ES:SE:LP:AF:ID  0.00163301:0.0106938:0.0555173:0.912862:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117313 ES:SE:LP:AF:ID  -0.0131584:0.00718642:1.17393:0.117313:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067698 ES:SE:LP:AF:ID  -0.0022455:0.010475:0.0809219:0.067698:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  0.00666782:0.00533426:0.677781:0.513304:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033677 ES:SE:LP:AF:ID  0.00460816:0.0132959:0.136677:0.033677:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037457 ES:SE:LP:AF:ID  0.00660563:0.0120587:0.236572:0.037457:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037644 ES:SE:LP:AF:ID  0.00612424:0.0119956:0.21467:0.037644:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03722  ES:SE:LP:AF:ID  0.00715601:0.0121052:0.259637:0.03722:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016282 ES:SE:LP:AF:ID  -0.0114095:0.0189878:0.259637:0.016282:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03786  ES:SE:LP:AF:ID  0.00582224:0.0119546:0.200659:0.03786:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037955 ES:SE:LP:AF:ID  0.00424319:0.0119167:0.142668:0.037955:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102736 ES:SE:LP:AF:ID  0.00689725:0.00870485:0.366532:0.102736:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95809  ES:SE:LP:AF:ID  -0.0045972:0.0115097:0.161151:0.95809:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03169  ES:SE:LP:AF:ID  -0.0207041:0.0210762:0.481486:0.03169:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052723 ES:SE:LP:AF:ID  0.0194495:0.0169763:0.60206:0.052723:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037449 ES:SE:LP:AF:ID  0.00544206:0.0119949:0.187087:0.037449:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037717 ES:SE:LP:AF:ID  0.0045695:0.0118956:0.154902:0.037717:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  0.00744732:0.00621492:0.638272:0.841441:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056334 ES:SE:LP:AF:ID  -0.0200085:0.0100958:1.3279:0.056334:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  -0.0106538:0.00682627:0.920819:0.123078:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02513  ES:SE:LP:AF:ID  0.0116525:0.0169997:0.309804:0.02513:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  -0.0111034:0.00682847:1:0.12233:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  -0.00594904:0.00670326:0.431798:0.134139:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011558 ES:SE:LP:AF:ID  -0.0236643:0.0238907:0.49485:0.011558:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.0061   ES:SE:LP:AF:ID  -0.0342014:0.0303383:0.585027:0.0061:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.0376   ES:SE:LP:AF:ID  0.0064464:0.0117853:0.236572:0.0376:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  0.0068304:0.00601219:0.585027:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  0.00677951:0.00600778:0.585027:0.836733:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  0.010475:0.00645566:1:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131004 ES:SE:LP:AF:ID  -0.0115926:0.00647224:1.13668:0.131004:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038045 ES:SE:LP:AF:ID  0.00664108:0.0116005:0.244125:0.038045:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038292 ES:SE:LP:AF:ID  0.00717928:0.0115286:0.275724:0.038292:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867976 ES:SE:LP:AF:ID  0.0104478:0.00644529:0.958607:0.867976:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86805  ES:SE:LP:AF:ID  0.0107574:0.00644792:1.02228:0.86805:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038199 ES:SE:LP:AF:ID  0.00671885:0.0115818:0.251812:0.038199:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867987 ES:SE:LP:AF:ID  0.0104169:0.00644513:0.958607:0.867987:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005396 ES:SE:LP:AF:ID  0.00815886:0.0323027:0.09691:0.005396:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  0.00680453:0.0059902:0.585027:0.836159:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038203 ES:SE:LP:AF:ID  0.00654044:0.0115987:0.244125:0.038203:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  0.00679966:0.00600661:0.585027:0.836793:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01303  ES:SE:LP:AF:ID  0.0229412:0.0217313:0.537602:0.01303:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005662 ES:SE:LP:AF:ID  -0.0264836:0.0322604:0.387216:0.005662:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  0.00769978:0.00609116:0.677781:0.838109:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  0.0104117:0.00643683:0.958607:0.868228:rs3115858