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_1568.vcf.gz --id UKB-b:5239 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_1568.txt.gz --cohort_controls 327026 --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-5239/UKB-b-5239_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5239/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5239/UKB-b-5239_data.vcf.gz ...
Read summary statistics for 9792692 SNPs.
Dropped 14233 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, 1289027 SNPs remain.
After merging with regression SNP LD, 1289027 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0539 (0.0029)
Lambda GC: 1.3081
Mean Chi^2: 1.3712
Intercept: 1.0281 (0.008)
Ratio: 0.0757 (0.0216)
Analysis finished at Thu Oct 17 14:46:47 2019
Total time elapsed: 1.0m:42.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9496,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 19,
    "n_p_sig": 964,
    "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": 180795,
    "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": 1289027,
    "ldsc_nsnp_merge_regression_ld": 1289027,
    "ldsc_observed_scale_h2_beta": 0.0539,
    "ldsc_observed_scale_h2_se": 0.0029,
    "ldsc_intercept_beta": 1.0281,
    "ldsc_intercept_se": 0.008,
    "ldsc_lambda_gc": 1.3081,
    "ldsc_mean_chisq": 1.3712,
    "ldsc_ratio": 0.0757
}

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 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 9778525 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 9792692 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 8.622988e+00 5.748740e+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 7.885758e+07 5.628828e+07 828.0000000 3.258148e+07 6.948096e+07 1.145917e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.240000e-05 9.845000e-03 -0.1316110 -3.272000e-03 -2.240000e-05 3.208000e-03 2.519410e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.972400e-03 6.493800e-03 0.0019894 2.430300e-03 4.049100e-03 9.278400e-03 1.038500e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.688545e-01 2.972883e-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 4.688557e-01 2.972655e-01 0.0000000 2.034603e-01 4.583553e-01 7.265894e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.043996e-01 2.568237e-01 0.0010710 1.355400e-02 7.928000e-02 3.182472e-01 9.989290e-01 ▇▂▁▁▁
numeric AF_reference 180795 0.9815378 NA NA NA NA NA NA NA 2.074678e-01 2.483860e-01 0.0000000 1.198080e-02 1.008390e-01 3.218850e-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 0.0059391 0.0036556 0.1000000 0.1042392 0.623716 0.7821490 NA
1 54676 rs2462492 C T 0.0057038 0.0036235 0.1199999 0.1154550 0.400592 NA NA
1 86028 rs114608975 T C -0.0106621 0.0057874 0.0649995 0.0654338 0.103641 0.0277556 NA
1 91536 rs6702460 G T 0.0039528 0.0035704 0.2700001 0.2682582 0.456784 0.4207270 NA
1 234313 rs8179466 C T -0.0051514 0.0070354 0.4600002 0.4640385 0.074491 NA NA
1 534192 rs6680723 C T -0.0010048 0.0040790 0.8100000 0.8054254 0.241149 NA NA
1 546697 rs12025928 A G 0.0023431 0.0050914 0.6499995 0.6453692 0.913637 NA NA
1 693731 rs12238997 A G 0.0005887 0.0034186 0.8600001 0.8632881 0.116256 0.1417730 NA
1 705882 rs72631875 G A 0.0000367 0.0049992 0.9900000 0.9941492 0.067395 0.0315495 NA
1 706368 rs55727773 A G 0.0000592 0.0025321 0.9800000 0.9813353 0.516204 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0053948 0.0053198 0.3100002 0.3105413 0.041890 0.0473243 NA
22 51219766 rs182321900 C T 0.0097945 0.0253875 0.6999999 0.6996456 0.001854 NA NA
22 51220146 rs868950473 C T 0.0086256 0.0250999 0.7300002 0.7311077 0.001908 NA NA
22 51221190 rs369304721 G A -0.0004647 0.0053083 0.9299999 0.9302349 0.049595 NA NA
22 51221731 rs115055839 T C -0.0008226 0.0039706 0.8400000 0.8358823 0.073082 0.0625000 NA
22 51222100 rs114553188 G T -0.0013856 0.0046758 0.7700005 0.7669844 0.054322 0.0880591 NA
22 51223637 rs375798137 G A -0.0014803 0.0046979 0.7499995 0.7526838 0.053963 0.0788738 NA
22 51229805 rs9616985 T C -0.0007684 0.0039848 0.8499999 0.8470868 0.072915 0.0730831 NA
22 51232488 rs376461333 A G -0.0044790 0.0093974 0.6300007 0.6336303 0.019946 NA NA
22 51237063 rs3896457 T C 0.0054719 0.0024352 0.0250000 0.0246415 0.298277 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623716 ES:SE:LP:AF:ID  0.0059391:0.00365564:1:0.623716:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400592 ES:SE:LP:AF:ID  0.00570385:0.00362347:0.920819:0.400592:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103641 ES:SE:LP:AF:ID  -0.0106621:0.00578744:1.18709:0.103641:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456784 ES:SE:LP:AF:ID  0.00395275:0.00357042:0.568636:0.456784:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074491 ES:SE:LP:AF:ID  -0.00515142:0.00703541:0.337242:0.074491:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241149 ES:SE:LP:AF:ID  -0.00100478:0.00407897:0.091515:0.241149:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913637 ES:SE:LP:AF:ID  0.00234311:0.00509145:0.187087:0.913637:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116256 ES:SE:LP:AF:ID  0.000588654:0.00341863:0.0655015:0.116256:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067395 ES:SE:LP:AF:ID  3.66587e-05:0.00499918:0.00436481:0.067395:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516204 ES:SE:LP:AF:ID  5.9238e-05:0.00253209:0.00877392:0.516204:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032817 ES:SE:LP:AF:ID  0.00152518:0.00639574:0.091515:0.032817:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036422 ES:SE:LP:AF:ID  0.00246948:0.00580912:0.173925:0.036422:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036532 ES:SE:LP:AF:ID  0.00271322:0.00578763:0.19382:0.036532:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036233 ES:SE:LP:AF:ID  0.00304799:0.00582924:0.221849:0.036233:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01627  ES:SE:LP:AF:ID  -0.00241738:0.00899431:0.102373:0.01627:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036764 ES:SE:LP:AF:ID  0.00273976:0.00576516:0.200659:0.036764:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036853 ES:SE:LP:AF:ID  0.00299092:0.00574631:0.221849:0.036853:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  -0.00413069:0.00417829:0.49485:0.101206:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959463 ES:SE:LP:AF:ID  -0.00211752:0.00555135:0.154902:0.959463:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03152  ES:SE:LP:AF:ID  -0.0184559:0.0100227:1.18046:0.03152:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053182 ES:SE:LP:AF:ID  0.0168285:0.00799231:1.45593:0.053182:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03639  ES:SE:LP:AF:ID  0.00284775:0.00578265:0.207608:0.03639:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036704 ES:SE:LP:AF:ID  0.00327276:0.00572955:0.244125:0.036704:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843587 ES:SE:LP:AF:ID  -0.000815936:0.00296358:0.107905:0.843587:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056182 ES:SE:LP:AF:ID  0.00601887:0.00478364:0.677781:0.056182:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122284 ES:SE:LP:AF:ID  0.000202804:0.00324197:0.0222764:0.122284:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02601  ES:SE:LP:AF:ID  0.00635406:0.00792018:0.376751:0.02601:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121536 ES:SE:LP:AF:ID  0.00014153:0.00324334:0.0132283:0.121536:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132347 ES:SE:LP:AF:ID  0.00113149:0.00319505:0.142668:0.132347:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011062 ES:SE:LP:AF:ID  0.00662986:0.0116731:0.244125:0.011062:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005701 ES:SE:LP:AF:ID  -0.0010235:0.01498:0.0222764:0.005701:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002151 ES:SE:LP:AF:ID  -0.0133313:0.0260751:0.21467:0.002151:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036619 ES:SE:LP:AF:ID  0.00242946:0.00567221:0.173925:0.036619:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839286 ES:SE:LP:AF:ID  -0.000329994:0.00287068:0.0409586:0.839286:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838954 ES:SE:LP:AF:ID  -7.97395e-05:0.00286808:0.00877392:0.838954:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869917 ES:SE:LP:AF:ID  0.000888682:0.00307681:0.113509:0.869917:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12973  ES:SE:LP:AF:ID  -0.000971383:0.0030833:0.124939:0.12973:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037129 ES:SE:LP:AF:ID  0.00288072:0.00557633:0.21467:0.037129:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037368 ES:SE:LP:AF:ID  0.00299122:0.00554108:0.229148:0.037368:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869304 ES:SE:LP:AF:ID  0.000947044:0.00307123:0.119186:0.869304:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869404 ES:SE:LP:AF:ID  0.0011034:0.00307245:0.142668:0.869404:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037316 ES:SE:LP:AF:ID  0.003044:0.00556645:0.236572:0.037316:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869307 ES:SE:LP:AF:ID  0.000946642:0.00307121:0.119186:0.869307:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005172 ES:SE:LP:AF:ID  -0.0156535:0.0156424:0.49485:0.005172:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005135 ES:SE:LP:AF:ID  -0.0164903:0.0156872:0.537602:0.005135:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83843  ES:SE:LP:AF:ID  -0.000290191:0.00286033:0.0362122:0.83843:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037329 ES:SE:LP:AF:ID  0.00273015:0.00557421:0.207608:0.037329:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839064 ES:SE:LP:AF:ID  -0.00047363:0.00286845:0.0604807:0.839064:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013886 ES:SE:LP:AF:ID  0.00899033:0.0099461:0.431798:0.013886:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005493 ES:SE:LP:AF:ID  -0.0085553:0.0154773:0.236572:0.005493:rs184270342