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_1807.vcf.gz --id UKB-b:11303 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_1807.txt.gz --cohort_controls 341118 --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-11303/UKB-b-11303_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11303/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11303/UKB-b-11303_data.vcf.gz ...
Read summary statistics for 9826872 SNPs.
Dropped 14515 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, 1289103 SNPs remain.
After merging with regression SNP LD, 1289103 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0316 (0.0022)
Lambda GC: 1.2709
Mean Chi^2: 1.2977
Intercept: 1.0875 (0.0073)
Ratio: 0.2939 (0.0245)
Analysis finished at Thu Oct 17 14:42:06 2019
Total time elapsed: 1.0m:47.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9498,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 12,
    "n_p_sig": 269,
    "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": 183994,
    "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": 1289103,
    "ldsc_nsnp_merge_regression_ld": 1289103,
    "ldsc_observed_scale_h2_beta": 0.0316,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0875,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.2709,
    "ldsc_mean_chisq": 1.2977,
    "ldsc_ratio": 0.2939
}

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 9812424 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 9826872 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 8.622872e+00 5.748244e+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 7.885813e+07 5.628268e+07 828.0000000 3.258809e+07 6.948891e+07 1.145881e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.120000e-04 1.187180e-02 -0.2292900 -3.818200e-03 -6.160000e-05 3.681800e-03 2.443840e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 8.205600e-03 7.716300e-03 0.0023155 2.831400e-03 4.735000e-03 1.089320e-02 1.226080e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.692633e-01 2.964281e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.692667e-01 2.964037e-01 0.0000000 2.054685e-01 4.580985e-01 7.254859e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.038477e-01 2.568067e-01 0.0010270 1.332500e-02 7.849800e-02 3.171490e-01 9.989730e-01 ▇▂▁▁▁
numeric AF_reference 183994 0.9812764 NA NA NA NA NA NA NA 2.070658e-01 2.483180e-01 0.0000000 1.198080e-02 1.002400e-01 3.208870e-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 0.0044397 0.0042502 0.2999998 0.2962177 0.623527 0.7821490 NA
1 54676 rs2462492 C T -0.0112227 0.0042101 0.0077000 0.0076843 0.400830 NA NA
1 86028 rs114608975 T C 0.0016934 0.0067310 0.8000000 0.8013620 0.103718 0.0277556 NA
1 91536 rs6702460 G T -0.0005136 0.0041513 0.9000000 0.9015284 0.457174 0.4207270 NA
1 234313 rs8179466 C T -0.0025726 0.0081907 0.7499995 0.7534517 0.074432 NA NA
1 534192 rs6680723 C T 0.0020682 0.0047411 0.6600001 0.6626690 0.240982 NA NA
1 546697 rs12025928 A G -0.0033085 0.0059164 0.5800000 0.5760156 0.913438 NA NA
1 693731 rs12238997 A G -0.0012599 0.0039786 0.7499995 0.7514915 0.116120 0.1417730 NA
1 705882 rs72631875 G A 0.0098091 0.0058207 0.0920005 0.0919478 0.067363 0.0315495 NA
1 706368 rs55727773 A G 0.0067590 0.0029455 0.0219999 0.0217521 0.515789 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0116230 0.0061904 0.0599998 0.0604376 0.041905 0.0473243 NA
22 51219766 rs182321900 C T 0.0158102 0.0292735 0.5900000 0.5891379 0.001885 NA NA
22 51220146 rs868950473 C T 0.0157534 0.0290247 0.5900000 0.5872962 0.001931 NA NA
22 51221190 rs369304721 G A -0.0040318 0.0061684 0.5099998 0.5133514 0.049803 NA NA
22 51221731 rs115055839 T C -0.0032958 0.0046132 0.4700002 0.4749632 0.073320 0.0625000 NA
22 51222100 rs114553188 G T -0.0030190 0.0054366 0.5800000 0.5786848 0.054460 0.0880591 NA
22 51223637 rs375798137 G A -0.0030797 0.0054636 0.5700002 0.5729706 0.054078 0.0788738 NA
22 51229805 rs9616985 T C -0.0032873 0.0046303 0.4799997 0.4777300 0.073143 0.0730831 NA
22 51232488 rs376461333 A G 0.0008255 0.0109412 0.9400001 0.9398590 0.019983 NA NA
22 51237063 rs3896457 T C 0.0053721 0.0028320 0.0580003 0.0578401 0.298217 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623527 ES:SE:LP:AF:ID  0.0044397:0.00425023:0.522879:0.623527:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40083  ES:SE:LP:AF:ID  -0.0112227:0.00421014:2.11351:0.40083:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103718 ES:SE:LP:AF:ID  0.00169343:0.00673105:0.09691:0.103718:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457174 ES:SE:LP:AF:ID  -0.000513645:0.00415131:0.0457575:0.457174:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074432 ES:SE:LP:AF:ID  -0.00257264:0.00819074:0.124939:0.074432:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240982 ES:SE:LP:AF:ID  0.00206822:0.00474111:0.180456:0.240982:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913438 ES:SE:LP:AF:ID  -0.00330854:0.00591641:0.236572:0.913438:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11612  ES:SE:LP:AF:ID  -0.00125991:0.00397858:0.124939:0.11612:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067363 ES:SE:LP:AF:ID  0.00980906:0.00582067:1.03621:0.067363:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515789 ES:SE:LP:AF:ID  0.00675904:0.00294554:1.65758:0.515789:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032946 ES:SE:LP:AF:ID  0.000296949:0.00743015:0.0132283:0.032946:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036527 ES:SE:LP:AF:ID  0.000491993:0.00675197:0.0268721:0.036527:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036631 ES:SE:LP:AF:ID  0.000405291:0.00672742:0.0222764:0.036631:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03634  ES:SE:LP:AF:ID  -0.000213423:0.00677516:0.0132283:0.03634:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016428 ES:SE:LP:AF:ID  -0.0066504:0.01041:0.283997:0.016428:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036875 ES:SE:LP:AF:ID  -0.00027881:0.00669982:0.0132283:0.036875:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036977 ES:SE:LP:AF:ID  0.000616884:0.00667637:0.0315171:0.036977:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101391 ES:SE:LP:AF:ID  -0.000552405:0.00484963:0.0409586:0.101391:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959303 ES:SE:LP:AF:ID  0.00334355:0.00644823:0.221849:0.959303:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031403 ES:SE:LP:AF:ID  -0.00495806:0.0116723:0.173925:0.031403:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053176 ES:SE:LP:AF:ID  -0.0088737:0.00929171:0.468521:0.053176:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036495 ES:SE:LP:AF:ID  0.000499346:0.00672051:0.0268721:0.036495:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03681  ES:SE:LP:AF:ID  0.000830179:0.0066597:0.0457575:0.03681:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843552 ES:SE:LP:AF:ID  0.00197344:0.00344746:0.244125:0.843552:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055918 ES:SE:LP:AF:ID  -0.00438191:0.00557389:0.366532:0.055918:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122153 ES:SE:LP:AF:ID  -0.00128483:0.00377216:0.136677:0.122153:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025859 ES:SE:LP:AF:ID  0.001594:0.0092395:0.0655015:0.025859:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121409 ES:SE:LP:AF:ID  -0.00119709:0.00377357:0.124939:0.121409:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132166 ES:SE:LP:AF:ID  -0.000239579:0.00371845:0.0222764:0.132166:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011166 ES:SE:LP:AF:ID  0.016185:0.0134684:0.638272:0.011166:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005668 ES:SE:LP:AF:ID  0.0107913:0.0175216:0.267606:0.005668:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002191 ES:SE:LP:AF:ID  -0.0795873:0.029911:2.10791:0.002191:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036715 ES:SE:LP:AF:ID  0.000450625:0.00659383:0.0222764:0.036715:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83929  ES:SE:LP:AF:ID  0.00191393:0.00334059:0.244125:0.83929:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838926 ES:SE:LP:AF:ID  0.00167198:0.00333702:0.207608:0.838926:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.870002 ES:SE:LP:AF:ID  0.00228121:0.00357997:0.283997:0.870002:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129665 ES:SE:LP:AF:ID  -0.00141568:0.00358668:0.161151:0.129665:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037237 ES:SE:LP:AF:ID  0.00159835:0.00648078:0.091515:0.037237:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03748  ES:SE:LP:AF:ID  0.00157898:0.00643996:0.091515:0.03748:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869357 ES:SE:LP:AF:ID  0.00210616:0.00357307:0.251812:0.869357:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869461 ES:SE:LP:AF:ID  0.00213961:0.00357453:0.259637:0.869461:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03744  ES:SE:LP:AF:ID  0.00166687:0.00646773:0.09691:0.03744:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869358 ES:SE:LP:AF:ID  0.00215123:0.00357304:0.259637:0.869358:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005067 ES:SE:LP:AF:ID  -0.0137975:0.018447:0.346787:0.005067:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005033 ES:SE:LP:AF:ID  -0.0139118:0.0184965:0.346787:0.005033:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838383 ES:SE:LP:AF:ID  0.00195827:0.00332774:0.251812:0.838383:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037452 ES:SE:LP:AF:ID  0.00159627:0.00647712:0.091515:0.037452:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839013 ES:SE:LP:AF:ID  0.00183829:0.00333712:0.236572:0.839013:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013744 ES:SE:LP:AF:ID  -0.00463896:0.0116511:0.161151:0.013744:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005623 ES:SE:LP:AF:ID  -0.0540888:0.0178113:2.61979:0.005623:rs184270342