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_5112.vcf.gz --id UKB-b:18509 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5112.txt.gz --cohort_controls 95986 --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-18509/UKB-b-18509_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18509/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-18509/UKB-b-18509_data.vcf.gz ...
Read summary statistics for 8993593 SNPs.
Dropped 8679 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, 1287187 SNPs remain.
After merging with regression SNP LD, 1287187 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.057 (0.0056)
Lambda GC: 1.0853
Mean Chi^2: 1.0976
Intercept: 0.9904 (0.0063)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:41:59 2019
Total time elapsed: 1.0m:39.94s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9478,
    "inflation_factor": 1.0475,
    "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": 92898,
    "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": 1287187,
    "ldsc_nsnp_merge_regression_ld": 1287187,
    "ldsc_observed_scale_h2_beta": 0.057,
    "ldsc_observed_scale_h2_se": 0.0056,
    "ldsc_intercept_beta": 0.9904,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0853,
    "ldsc_mean_chisq": 1.0976,
    "ldsc_ratio": -0.0984
}

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 8984953 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 8993593 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 8.643296e+00 5.758300e+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 7.878782e+07 5.634161e+07 828.0000000 3.242854e+07 6.934860e+07 1.145457e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.570000e-05 1.526350e-02 -0.1741660 -6.041900e-03 1.500000e-05 6.075600e-03 1.725360e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.216650e-02 8.888500e-03 0.0044351 5.287400e-03 8.084200e-03 1.668370e-02 1.038180e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.900876e-01 2.917765e-01 0.0000001 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.900879e-01 2.917500e-01 0.0000001 2.341125e-01 4.872252e-01 7.430302e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.205264e-01 2.585711e-01 0.0036470 2.067200e-02 1.019420e-01 3.478150e-01 9.963530e-01 ▇▂▁▁▁
numeric AF_reference 92898 0.9896706 NA NA NA NA NA NA NA 2.208110e-01 2.504799e-01 0.0000000 1.797120e-02 1.194090e-01 3.460460e-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 -0.0013970 0.0082004 0.8600001 0.8647328 0.623785 0.7821490 NA
1 54676 rs2462492 C T 0.0043311 0.0081402 0.5900000 0.5946784 0.398815 NA NA
1 86028 rs114608975 T C 0.0031078 0.0129322 0.8100000 0.8100856 0.103896 0.0277556 NA
1 91536 rs6702460 G T 0.0106904 0.0080017 0.1800002 0.1815418 0.455852 0.4207270 NA
1 234313 rs8179466 C T 0.0193357 0.0156806 0.2200002 0.2175396 0.074801 NA NA
1 534192 rs6680723 C T 0.0098933 0.0091538 0.2800000 0.2797913 0.240460 NA NA
1 546697 rs12025928 A G -0.0050747 0.0113458 0.6499995 0.6546786 0.912825 NA NA
1 693731 rs12238997 A G 0.0022838 0.0076121 0.7600007 0.7641638 0.117771 0.1417730 NA
1 705882 rs72631875 G A 0.0146922 0.0111445 0.1900002 0.1873911 0.067660 0.0315495 NA
1 706368 rs55727773 A G -0.0005081 0.0056476 0.9299999 0.9283178 0.514393 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0040973 0.0068309 0.5500004 0.5486296 0.137218 0.2052720 NA
22 51219387 rs9616832 T C 0.0020510 0.0088994 0.8200001 0.8177350 0.072641 0.0654952 NA
22 51219704 rs147475742 G A 0.0148380 0.0118359 0.2099999 0.2099716 0.041803 0.0473243 NA
22 51221190 rs369304721 G A 0.0063726 0.0119049 0.5900000 0.5924496 0.049141 NA NA
22 51221731 rs115055839 T C 0.0030635 0.0089016 0.7300002 0.7307320 0.072181 0.0625000 NA
22 51222100 rs114553188 G T -0.0071637 0.0104139 0.4899999 0.4915153 0.054499 0.0880591 NA
22 51223637 rs375798137 G A -0.0074464 0.0104674 0.4799997 0.4768416 0.054121 0.0788738 NA
22 51229805 rs9616985 T C 0.0027517 0.0089338 0.7600007 0.7580764 0.072044 0.0730831 NA
22 51232488 rs376461333 A G -0.0163127 0.0210854 0.4400003 0.4391383 0.020019 NA NA
22 51237063 rs3896457 T C 0.0021087 0.0054342 0.6999999 0.6979833 0.298259 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623785 ES:SE:LP:AF:ID  -0.00139696:0.0082004:0.0655015:0.623785:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398815 ES:SE:LP:AF:ID  0.00433113:0.00814017:0.229148:0.398815:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103896 ES:SE:LP:AF:ID  0.00310781:0.0129322:0.091515:0.103896:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455852 ES:SE:LP:AF:ID  0.0106904:0.00800166:0.744727:0.455852:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074801 ES:SE:LP:AF:ID  0.0193357:0.0156806:0.657577:0.074801:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24046  ES:SE:LP:AF:ID  0.00989333:0.00915381:0.552842:0.24046:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912825 ES:SE:LP:AF:ID  -0.00507466:0.0113458:0.187087:0.912825:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117771 ES:SE:LP:AF:ID  0.00228376:0.00761209:0.119186:0.117771:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06766  ES:SE:LP:AF:ID  0.0146922:0.0111445:0.721246:0.06766:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514393 ES:SE:LP:AF:ID  -0.000508062:0.00564755:0.0315171:0.514393:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033502 ES:SE:LP:AF:ID  -0.0214074:0.0141205:0.886057:0.033502:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037142 ES:SE:LP:AF:ID  -0.0245277:0.0128425:1.25181:0.037142:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037225 ES:SE:LP:AF:ID  -0.0242105:0.0128007:1.22915:0.037225:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036911 ES:SE:LP:AF:ID  -0.0238033:0.012891:1.18709:0.036911:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016729 ES:SE:LP:AF:ID  -0.0281311:0.0198253:0.79588:0.016729:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037479 ES:SE:LP:AF:ID  -0.0247938:0.0127468:1.284:0.037479:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037568 ES:SE:LP:AF:ID  -0.0245202:0.0127069:1.26761:0.037568:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101139 ES:SE:LP:AF:ID  0.00209231:0.00934284:0.0861861:0.101139:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958239 ES:SE:LP:AF:ID  0.0298134:0.0122234:1.82391:0.958239:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031891 ES:SE:LP:AF:ID  -0.0218818:0.0222373:0.481486:0.031891:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052581 ES:SE:LP:AF:ID  9.42359e-05:0.0180074:-0:0.052581:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037044 ES:SE:LP:AF:ID  -0.0255429:0.0127937:1.33724:0.037044:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037353 ES:SE:LP:AF:ID  -0.0254651:0.0126859:1.34679:0.037353:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841095 ES:SE:LP:AF:ID  0.00486018:0.00659497:0.337242:0.841095:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056118 ES:SE:LP:AF:ID  0.00224649:0.0107308:0.0809219:0.056118:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123697 ES:SE:LP:AF:ID  0.00488619:0.00722645:0.30103:0.123697:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025928 ES:SE:LP:AF:ID  0.0253824:0.0177221:0.823909:0.025928:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122886 ES:SE:LP:AF:ID  0.00489584:0.00723002:0.30103:0.122886:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133509 ES:SE:LP:AF:ID  -0.0033077:0.00712982:0.19382:0.133509:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011235 ES:SE:LP:AF:ID  -0.0185162:0.025856:0.327902:0.011235:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006076 ES:SE:LP:AF:ID  0.0249824:0.0323194:0.356547:0.006076:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037322 ES:SE:LP:AF:ID  -0.0281548:0.012545:1.60206:0.037322:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836845 ES:SE:LP:AF:ID  0.00598591:0.00638179:0.455932:0.836845:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836419 ES:SE:LP:AF:ID  0.0062632:0.00637479:0.481486:0.836419:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.867992 ES:SE:LP:AF:ID  -0.00175278:0.0068361:0.09691:0.867992:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.13168  ES:SE:LP:AF:ID  8.75804e-05:0.00685075:0.00436481:0.13168:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037765 ES:SE:LP:AF:ID  -0.0279252:0.0123463:1.61979:0.037765:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038011 ES:SE:LP:AF:ID  -0.0282655:0.0122703:1.67778:0.038011:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867294 ES:SE:LP:AF:ID  -0.000975662:0.00682235:0.05061:0.867294:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867393 ES:SE:LP:AF:ID  -0.00101769:0.00682555:0.0555173:0.867393:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037958 ES:SE:LP:AF:ID  -0.0291088:0.0123195:1.74473:0.037958:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867293 ES:SE:LP:AF:ID  -0.000899384:0.00682192:0.0457575:0.867293:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005105 ES:SE:LP:AF:ID  -0.0494922:0.0352918:0.79588:0.005105:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005072 ES:SE:LP:AF:ID  -0.0487314:0.0353917:0.769551:0.005072:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835954 ES:SE:LP:AF:ID  0.0071858:0.00636073:0.585027:0.835954:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037977 ES:SE:LP:AF:ID  -0.0291325:0.0123358:1.74473:0.037977:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83656  ES:SE:LP:AF:ID  0.00722657:0.00637781:0.585027:0.83656:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013189 ES:SE:LP:AF:ID  0.00142129:0.0228825:0.0222764:0.013189:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005503 ES:SE:LP:AF:ID  -0.0556412:0.0345739:0.958607:0.005503:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837844 ES:SE:LP:AF:ID  0.00570112:0.00646472:0.420216:0.837844:rs3131965