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.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_20131.vcf.gz --id UKB-b:15780 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20131.txt.gz --cohort_controls 113150 --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-15780/UKB-b-15780_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15780/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15780/UKB-b-15780_data.vcf.gz ...
Read summary statistics for 9113026 SNPs.
Dropped 9232 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, 1287453 SNPs remain.
After merging with regression SNP LD, 1287453 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0158 (0.0042)
Lambda GC: 1.0166
Mean Chi^2: 1.0269
Intercept: 0.9922 (0.0061)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:46:07 2019
Total time elapsed: 1.0m:41.47s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.948,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "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": 98874,
    "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": 1287453,
    "ldsc_nsnp_merge_regression_ld": 1287453,
    "ldsc_observed_scale_h2_beta": 0.0158,
    "ldsc_observed_scale_h2_se": 0.0042,
    "ldsc_intercept_beta": 0.9922,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0166,
    "ldsc_mean_chisq": 1.0269,
    "ldsc_ratio": -0.29
}

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 9103837 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 9113026 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 8.640360e+00 5.756773e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.879289e+07 5.632616e+07 828.000000 3.245563e+07 6.936316e+07 1.145258e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -7.180000e-05 1.233840e-02 -0.146328 -4.722800e-03 -1.740000e-05 4.679600e-03 1.390510e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.806400e-03 7.367800e-03 0.003471 4.146100e-03 6.419600e-03 1.346030e-02 7.924050e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.958937e-01 2.903553e-01 0.000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.958924e-01 2.903301e-01 0.000000 2.427413e-01 4.948704e-01 7.476171e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.178307e-01 2.582759e-01 0.003094 1.935500e-02 9.818700e-02 3.431710e-01 9.969060e-01 ▇▂▁▁▁
numeric AF_reference 98874 0.9891503 NA NA NA NA NA NA NA 2.183329e-01 2.501420e-01 0.000000 1.657350e-02 1.160140e-01 3.418530e-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 0.0092386 0.0063761 0.1499999 0.1473572 0.623894 0.7821490 NA
1 54676 rs2462492 C T -0.0007785 0.0063197 0.9000000 0.9019588 0.399432 NA NA
1 86028 rs114608975 T C -0.0127509 0.0101278 0.2099999 0.2080303 0.103378 0.0277556 NA
1 91536 rs6702460 G T -0.0066947 0.0062223 0.2800000 0.2819628 0.456529 0.4207270 NA
1 234313 rs8179466 C T 0.0081443 0.0123683 0.5099998 0.5102286 0.074020 NA NA
1 534192 rs6680723 C T -0.0044642 0.0070960 0.5300002 0.5292668 0.241075 NA NA
1 546697 rs12025928 A G 0.0066489 0.0088439 0.4500005 0.4521674 0.913027 NA NA
1 693731 rs12238997 A G -0.0006730 0.0059543 0.9100000 0.9100058 0.116860 0.1417730 NA
1 705882 rs72631875 G A -0.0224652 0.0086792 0.0096000 0.0096426 0.067714 0.0315495 NA
1 706368 rs55727773 A G -0.0036075 0.0044132 0.4100001 0.4136749 0.515748 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0032899 0.0053469 0.5400003 0.5383613 0.136637 0.2052720 NA
22 51219387 rs9616832 T C 0.0014797 0.0069481 0.8300000 0.8313495 0.072783 0.0654952 NA
22 51219704 rs147475742 G A 0.0036972 0.0093406 0.6899999 0.6922342 0.041213 0.0473243 NA
22 51221190 rs369304721 G A 0.0058277 0.0092925 0.5300002 0.5305679 0.049193 NA NA
22 51221731 rs115055839 T C 0.0013395 0.0069534 0.8499999 0.8472394 0.072236 0.0625000 NA
22 51222100 rs114553188 G T -0.0127929 0.0081688 0.1199999 0.1173339 0.054245 0.0880591 NA
22 51223637 rs375798137 G A -0.0127442 0.0082101 0.1199999 0.1206012 0.053879 0.0788738 NA
22 51229805 rs9616985 T C 0.0011617 0.0069786 0.8700001 0.8677896 0.072062 0.0730831 NA
22 51232488 rs376461333 A G -0.0036576 0.0165101 0.8200001 0.8246757 0.019767 NA NA
22 51237063 rs3896457 T C -0.0057935 0.0042290 0.1700000 0.1707058 0.298310 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623894 ES:SE:LP:AF:ID  0.00923858:0.00637614:0.823909:0.623894:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399432 ES:SE:LP:AF:ID  -0.000778504:0.00631968:0.0457575:0.399432:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103378 ES:SE:LP:AF:ID  -0.0127509:0.0101278:0.677781:0.103378:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456529 ES:SE:LP:AF:ID  -0.00669469:0.00622229:0.552842:0.456529:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07402  ES:SE:LP:AF:ID  0.0081443:0.0123683:0.29243:0.07402:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241075 ES:SE:LP:AF:ID  -0.00446425:0.00709596:0.275724:0.241075:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913027 ES:SE:LP:AF:ID  0.00664888:0.00884387:0.346787:0.913027:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11686  ES:SE:LP:AF:ID  -0.000673021:0.00595429:0.0409586:0.11686:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067714 ES:SE:LP:AF:ID  -0.0224652:0.00867922:2.01773:0.067714:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515748 ES:SE:LP:AF:ID  -0.00360751:0.00441316:0.387216:0.515748:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032972 ES:SE:LP:AF:ID  -0.0213239:0.0111412:1.25181:0.032972:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036592 ES:SE:LP:AF:ID  -0.0163494:0.0101148:0.958607:0.036592:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03671  ES:SE:LP:AF:ID  -0.0180385:0.0100751:1.13668:0.03671:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036406 ES:SE:LP:AF:ID  -0.0174123:0.0101494:1.0655:0.036406:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016622 ES:SE:LP:AF:ID  -0.0111827:0.0155129:0.327902:0.016622:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036947 ES:SE:LP:AF:ID  -0.016689:0.0100351:1.01773:0.036947:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  -0.0166225:0.0099991:1.01773:0.037066:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101815 ES:SE:LP:AF:ID  0.00578043:0.00726106:0.366532:0.101815:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959293 ES:SE:LP:AF:ID  0.0153577:0.00966487:0.958607:0.959293:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031208 ES:SE:LP:AF:ID  0.0273031:0.0177357:0.920819:0.031208:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053366 ES:SE:LP:AF:ID  -0.00915252:0.0138916:0.29243:0.053366:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03656  ES:SE:LP:AF:ID  -0.0151886:0.0100631:0.886057:0.03656:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036868 ES:SE:LP:AF:ID  -0.0168956:0.00997317:1.04576:0.036868:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843058 ES:SE:LP:AF:ID  0.00417877:0.00516863:0.376751:0.843058:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055808 ES:SE:LP:AF:ID  0.00274172:0.00837815:0.130768:0.055808:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12281  ES:SE:LP:AF:ID  -0.00148865:0.00565277:0.102373:0.12281:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.024822 ES:SE:LP:AF:ID  -0.00221255:0.0141456:0.0555173:0.024822:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122046 ES:SE:LP:AF:ID  -0.00202439:0.00565591:0.142668:0.122046:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132537 ES:SE:LP:AF:ID  -0.00335165:0.00557339:0.259637:0.132537:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011112 ES:SE:LP:AF:ID  -0.0134137:0.0203364:0.29243:0.011112:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005663 ES:SE:LP:AF:ID  -0.0116748:0.0263458:0.180456:0.005663:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036784 ES:SE:LP:AF:ID  -0.016021:0.00987234:1:0.036784:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838672 ES:SE:LP:AF:ID  0.00638776:0.00500486:0.69897:0.838672:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838334 ES:SE:LP:AF:ID  0.00644363:0.00499987:0.69897:0.838334:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86926  ES:SE:LP:AF:ID  0.00424946:0.00536036:0.366532:0.86926:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130389 ES:SE:LP:AF:ID  -0.00412699:0.00537231:0.356547:0.130389:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037276 ES:SE:LP:AF:ID  -0.019003:0.00970697:1.30103:0.037276:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  -0.0194026:0.00964292:1.35655:0.037526:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868617 ES:SE:LP:AF:ID  0.0043895:0.00535057:0.387216:0.868617:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868727 ES:SE:LP:AF:ID  0.00446361:0.00535327:0.39794:0.868727:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037482 ES:SE:LP:AF:ID  -0.0193263:0.00968715:1.33724:0.037482:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868625 ES:SE:LP:AF:ID  0.00441723:0.00535047:0.387216:0.868625:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005194 ES:SE:LP:AF:ID  -0.0282512:0.0272562:0.522879:0.005194:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005166 ES:SE:LP:AF:ID  -0.0280237:0.027302:0.522879:0.005166:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837766 ES:SE:LP:AF:ID  0.00688459:0.00498598:0.769551:0.837766:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037521 ES:SE:LP:AF:ID  -0.0186861:0.00969813:1.26761:0.037521:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838368 ES:SE:LP:AF:ID  0.00683166:0.00499954:0.769551:0.838368:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013588 ES:SE:LP:AF:ID  -0.0209451:0.0175416:0.638272:0.013588:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005481 ES:SE:LP:AF:ID  0.0124819:0.0269854:0.19382:0.005481:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839512 ES:SE:LP:AF:ID  0.00564413:0.00506636:0.568636:0.839512:rs3131965