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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_5263.vcf.gz --id UKB-b:12440 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5263.txt.gz --cohort_controls 97465 --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-12440/UKB-b-12440_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12440/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:03 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12440/UKB-b-12440_data.vcf.gz ...
Read summary statistics for 9006125 SNPs.
Dropped 8731 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, 1287218 SNPs remain.
After merging with regression SNP LD, 1287218 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2114 (0.0105)
Lambda GC: 1.3016
Mean Chi^2: 1.4539
Intercept: 1.0517 (0.0103)
Ratio: 0.1139 (0.0228)
Analysis finished at Thu Oct 17 14:43:42 2019
Total time elapsed: 1.0m:38.35s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 95,
    "n_p_sig": 7239,
    "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": 93411,
    "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": 1287218,
    "ldsc_nsnp_merge_regression_ld": 1287218,
    "ldsc_observed_scale_h2_beta": 0.2114,
    "ldsc_observed_scale_h2_se": 0.0105,
    "ldsc_intercept_beta": 1.0517,
    "ldsc_intercept_se": 0.0103,
    "ldsc_lambda_gc": 1.3016,
    "ldsc_mean_chisq": 1.4539,
    "ldsc_ratio": 0.1139
}

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 TRUE
n_p_sig TRUE
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 8997433 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 9006125 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 8.643115e+00 5.758251e+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 7.878828e+07 5.634116e+07 828.0000000 3.242940e+07 6.934977e+07 1.145449e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.095000e-04 1.543790e-02 -0.2119180 -6.472700e-03 -8.680000e-05 6.295400e-03 1.755340e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.182100e-02 8.658800e-03 0.0042927 5.123400e-03 7.843300e-03 1.621470e-02 1.000930e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.674271e-01 2.981973e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.674292e-01 2.981728e-01 0.0000000 2.011114e-01 4.560017e-01 7.263705e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.202507e-01 2.585404e-01 0.0035920 2.053500e-02 1.015670e-01 3.473310e-01 9.964080e-01 ▇▂▁▁▁
numeric AF_reference 93411 0.9896281 NA NA NA NA NA NA NA 2.205580e-01 2.504474e-01 0.0000000 1.797120e-02 1.190100e-01 3.456470e-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 -0.0027577 0.0079346 0.7300002 0.7281756 0.623865 0.7821490 NA
1 54676 rs2462492 C T 0.0030379 0.0078800 0.6999999 0.6998505 0.398679 NA NA
1 86028 rs114608975 T C 0.0052875 0.0125018 0.6700003 0.6723397 0.103994 0.0277556 NA
1 91536 rs6702460 G T 0.0015398 0.0077441 0.8400000 0.8423880 0.455564 0.4207270 NA
1 234313 rs8179466 C T -0.0056886 0.0151613 0.7099994 0.7075093 0.074844 NA NA
1 534192 rs6680723 C T 0.0045520 0.0088655 0.6100002 0.6076358 0.240283 NA NA
1 546697 rs12025928 A G 0.0113236 0.0109801 0.2999998 0.3024077 0.912849 NA NA
1 693731 rs12238997 A G 0.0024508 0.0073653 0.7400005 0.7393196 0.117836 0.1417730 NA
1 705882 rs72631875 G A -0.0017801 0.0107767 0.8700001 0.8688005 0.067682 0.0315495 NA
1 706368 rs55727773 A G -0.0008350 0.0054632 0.8800001 0.8785251 0.514115 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0142109 0.0066274 0.0320000 0.0320125 0.137113 0.2052720 NA
22 51219387 rs9616832 T C 0.0052436 0.0086413 0.5400003 0.5439762 0.072486 0.0654952 NA
22 51219704 rs147475742 G A -0.0015404 0.0115014 0.8900000 0.8934595 0.041684 0.0473243 NA
22 51221190 rs369304721 G A 0.0102903 0.0115614 0.3700002 0.3734355 0.049030 NA NA
22 51221731 rs115055839 T C 0.0055402 0.0086439 0.5199996 0.5215611 0.072021 0.0625000 NA
22 51222100 rs114553188 G T 0.0194440 0.0101070 0.0539995 0.0543778 0.054470 0.0880591 NA
22 51223637 rs375798137 G A 0.0206470 0.0101613 0.0420001 0.0421612 0.054067 0.0788738 NA
22 51229805 rs9616985 T C 0.0058710 0.0086746 0.5000000 0.4985319 0.071886 0.0730831 NA
22 51232488 rs376461333 A G 0.0196998 0.0204279 0.3300000 0.3348667 0.020049 NA NA
22 51237063 rs3896457 T C -0.0022823 0.0052716 0.6700003 0.6650618 0.298167 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623865 ES:SE:LP:AF:ID  -0.00275769:0.00793458:0.136677:0.623865:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398679 ES:SE:LP:AF:ID  0.0030379:0.00787996:0.154902:0.398679:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103994 ES:SE:LP:AF:ID  0.0052875:0.0125018:0.173925:0.103994:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455564 ES:SE:LP:AF:ID  0.00153983:0.00774407:0.0757207:0.455564:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074844 ES:SE:LP:AF:ID  -0.00568857:0.0151613:0.148742:0.074844:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240283 ES:SE:LP:AF:ID  0.00455199:0.00886548:0.21467:0.240283:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912849 ES:SE:LP:AF:ID  0.0113236:0.0109801:0.522879:0.912849:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117836 ES:SE:LP:AF:ID  0.00245085:0.00736534:0.130768:0.117836:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067682 ES:SE:LP:AF:ID  -0.00178012:0.0107767:0.0604807:0.067682:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514115 ES:SE:LP:AF:ID  -0.000834991:0.0054632:0.0555173:0.514115:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033658 ES:SE:LP:AF:ID  0.024993:0.0136279:1.17393:0.033658:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037308 ES:SE:LP:AF:ID  0.0262989:0.0123972:1.46852:0.037308:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03739  ES:SE:LP:AF:ID  0.0262477:0.0123567:1.46852:0.03739:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037088 ES:SE:LP:AF:ID  0.0266942:0.0124418:1.49485:0.037088:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016799 ES:SE:LP:AF:ID  -0.0175391:0.0191299:0.443698:0.016799:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03765  ES:SE:LP:AF:ID  0.0257138:0.0123038:1.4318:0.03765:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037735 ES:SE:LP:AF:ID  0.0250816:0.0122661:1.38722:0.037735:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101347 ES:SE:LP:AF:ID  0.0145202:0.00903413:0.958607:0.101347:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958076 ES:SE:LP:AF:ID  -0.0210812:0.0118064:1.13077:0.958076:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031781 ES:SE:LP:AF:ID  -0.0231671:0.0216128:0.552842:0.031781:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052542 ES:SE:LP:AF:ID  0.00346436:0.0174544:0.0757207:0.052542:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037194 ES:SE:LP:AF:ID  0.0275988:0.012353:1.60206:0.037194:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037508 ES:SE:LP:AF:ID  0.0260036:0.0122478:1.46852:0.037508:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840954 ES:SE:LP:AF:ID  -0.00627983:0.00638142:0.481486:0.840954:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056072 ES:SE:LP:AF:ID  -0.00234345:0.0103909:0.0861861:0.056072:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123718 ES:SE:LP:AF:ID  0.00288547:0.00699261:0.167491:0.123718:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025846 ES:SE:LP:AF:ID  -0.0262835:0.0171788:0.886057:0.025846:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122917 ES:SE:LP:AF:ID  0.00290378:0.00699622:0.167491:0.122917:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133582 ES:SE:LP:AF:ID  0.0119354:0.00690039:1.07572:0.133582:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011213 ES:SE:LP:AF:ID  -0.00042345:0.0249979:0.00436481:0.011213:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006042 ES:SE:LP:AF:ID  0.0442156:0.0313489:0.79588:0.006042:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037471 ES:SE:LP:AF:ID  0.0246655:0.0121138:1.37675:0.037471:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836757 ES:SE:LP:AF:ID  -0.00851456:0.00617458:0.769551:0.836757:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836316 ES:SE:LP:AF:ID  -0.00844671:0.00616754:0.769551:0.836316:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.867994 ES:SE:LP:AF:ID  -0.00485681:0.00661469:0.337242:0.867994:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.13167  ES:SE:LP:AF:ID  0.00532073:0.00662921:0.376751:0.13167:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.0379   ES:SE:LP:AF:ID  0.0249101:0.0119246:1.4318:0.0379:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038147 ES:SE:LP:AF:ID  0.0256137:0.0118508:1.50864:0.038147:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867294 ES:SE:LP:AF:ID  -0.00473876:0.00660147:0.327902:0.867294:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867397 ES:SE:LP:AF:ID  -0.00477823:0.00660434:0.327902:0.867397:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038097 ES:SE:LP:AF:ID  0.0250105:0.0118988:1.4437:0.038097:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867292 ES:SE:LP:AF:ID  -0.00485299:0.00660106:0.337242:0.867292:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005052 ES:SE:LP:AF:ID  0.000510526:0.0343631:0.00436481:0.005052:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005019 ES:SE:LP:AF:ID  0.000168121:0.0344565:-0:0.005019:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835859 ES:SE:LP:AF:ID  -0.00819089:0.00615444:0.744727:0.835859:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038115 ES:SE:LP:AF:ID  0.024655:0.0119147:1.40894:0.038115:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83646  ES:SE:LP:AF:ID  -0.00761582:0.0061709:0.657577:0.83646:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013132 ES:SE:LP:AF:ID  0.00427159:0.0221741:0.0705811:0.013132:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005506 ES:SE:LP:AF:ID  0.0115522:0.0334104:0.136677:0.005506:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.83774  ES:SE:LP:AF:ID  -0.00716804:0.00625509:0.60206:0.83774:rs3131965