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_104330.vcf.gz --id UKB-b:9686 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_104330.txt.gz --cohort_controls 64945 --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-9686/UKB-b-9686_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9686/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9686/UKB-b-9686_data.vcf.gz ...
Read summary statistics for 8624977 SNPs.
Dropped 7370 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, 1285747 SNPs remain.
After merging with regression SNP LD, 1285747 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0033 (0.0066)
Lambda GC: 1.0063
Mean Chi^2: 1.0121
Intercept: 1.0078 (0.0063)
Ratio: 0.6459 (0.5211)
Analysis finished at Thu Oct 17 14:44:25 2019
Total time elapsed: 1.0m:34.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 8,
    "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": 83096,
    "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": 1285747,
    "ldsc_nsnp_merge_regression_ld": 1285747,
    "ldsc_observed_scale_h2_beta": 0.0033,
    "ldsc_observed_scale_h2_se": 0.0066,
    "ldsc_intercept_beta": 1.0078,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0063,
    "ldsc_mean_chisq": 1.0121,
    "ldsc_ratio": 0.6446
}

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 TRUE
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 8617641 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 8624977 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 8.650332e+00 5.760990e+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 7.877017e+07 5.637170e+07 828.0000000 3.238545e+07 6.929195e+07 1.145690e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.150000e-05 5.292900e-03 -0.0487996 -2.205900e-03 -1.660000e-05 2.179500e-03 6.818470e-02 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.356400e-03 2.973700e-03 0.0017302 2.037500e-03 3.004200e-03 5.889000e-03 2.983070e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.986806e-01 2.889303e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.986791e-01 2.889041e-01 0.0000000 2.483351e-01 4.980980e-01 7.487842e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291174e-01 2.594882e-01 0.0053900 2.519000e-02 1.138970e-01 3.626150e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83096 0.9903657 NA NA NA NA NA NA NA 2.288666e-01 2.514589e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 -0.0012676 0.0031887 0.6899999 0.6909812 0.623813 0.7821490 NA
1 54676 rs2462492 C T 0.0066042 0.0031796 0.0379997 0.0377921 0.399131 NA NA
1 86028 rs114608975 T C -0.0016688 0.0050611 0.7400005 0.7415985 0.103540 0.0277556 NA
1 91536 rs6702460 G T 0.0041005 0.0031272 0.1900002 0.1897806 0.455921 0.4207270 NA
1 234313 rs8179466 C T 0.0001951 0.0061844 0.9699999 0.9748342 0.074456 NA NA
1 534192 rs6680723 C T 0.0020824 0.0035617 0.5600000 0.5587860 0.242067 NA NA
1 546697 rs12025928 A G -0.0067947 0.0044192 0.1199999 0.1241666 0.912858 NA NA
1 693731 rs12238997 A G -0.0008569 0.0029698 0.7700005 0.7729457 0.117314 0.1417730 NA
1 705882 rs72631875 G A 0.0044010 0.0043288 0.3100002 0.3093095 0.067702 0.0315495 NA
1 706368 rs55727773 A G 0.0024322 0.0022045 0.2700001 0.2698959 0.513300 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0029441 0.0026812 0.2700001 0.2721867 0.136315 0.2052720 NA
22 51219387 rs9616832 T C -0.0057823 0.0034946 0.0980009 0.0979936 0.071802 0.0654952 NA
22 51219704 rs147475742 G A -0.0002093 0.0046487 0.9599999 0.9640943 0.041193 0.0473243 NA
22 51221190 rs369304721 G A -0.0050620 0.0046817 0.2800000 0.2795971 0.048375 NA NA
22 51221731 rs115055839 T C -0.0060902 0.0034953 0.0810009 0.0814410 0.071352 0.0625000 NA
22 51222100 rs114553188 G T 0.0036352 0.0040506 0.3700002 0.3694779 0.054846 0.0880591 NA
22 51223637 rs375798137 G A 0.0035601 0.0040717 0.3800004 0.3819261 0.054466 0.0788738 NA
22 51229805 rs9616985 T C -0.0062426 0.0035061 0.0749998 0.0749976 0.071257 0.0730831 NA
22 51232488 rs376461333 A G 0.0082550 0.0080755 0.3100002 0.3066719 0.020459 NA NA
22 51237063 rs3896457 T C -0.0006238 0.0021167 0.7700005 0.7682045 0.298397 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623813 ES:SE:LP:AF:ID  -0.0012676:0.00318874:0.161151:0.623813:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399131 ES:SE:LP:AF:ID  0.00660425:0.00317955:1.42022:0.399131:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10354  ES:SE:LP:AF:ID  -0.00166883:0.00506109:0.130768:0.10354:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455921 ES:SE:LP:AF:ID  0.0041005:0.00312722:0.721246:0.455921:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074456 ES:SE:LP:AF:ID  0.000195092:0.00618438:0.0132283:0.074456:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242067 ES:SE:LP:AF:ID  0.00208235:0.00356173:0.251812:0.242067:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912858 ES:SE:LP:AF:ID  -0.00679466:0.00441924:0.920819:0.912858:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117314 ES:SE:LP:AF:ID  -0.000856873:0.00296985:0.113509:0.117314:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067702 ES:SE:LP:AF:ID  0.00440098:0.00432881:0.508638:0.067702:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.5133   ES:SE:LP:AF:ID  0.00243223:0.0022045:0.568636:0.5133:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033679 ES:SE:LP:AF:ID  -0.0105886:0.00549454:1.26761:0.033679:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03746  ES:SE:LP:AF:ID  -0.0107807:0.00498328:1.50864:0.03746:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037646 ES:SE:LP:AF:ID  -0.0107061:0.00495721:1.50864:0.037646:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037223 ES:SE:LP:AF:ID  -0.0107055:0.0050025:1.49485:0.037223:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016283 ES:SE:LP:AF:ID  0.00158797:0.00784674:0.0757207:0.016283:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037863 ES:SE:LP:AF:ID  -0.0106218:0.00494026:1.49485:0.037863:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037957 ES:SE:LP:AF:ID  -0.0107754:0.00492459:1.5376:0.037957:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102741 ES:SE:LP:AF:ID  -0.000374413:0.0035973:0.0362122:0.102741:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958087 ES:SE:LP:AF:ID  0.0108487:0.00475641:1.63827:0.958087:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031692 ES:SE:LP:AF:ID  0.0104039:0.00870977:0.638272:0.031692:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052723 ES:SE:LP:AF:ID  0.00153484:0.00701559:0.0809219:0.052723:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037451 ES:SE:LP:AF:ID  -0.0112832:0.00495692:1.63827:0.037451:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03772  ES:SE:LP:AF:ID  -0.010563:0.00491586:1.49485:0.03772:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841437 ES:SE:LP:AF:ID  0.00375345:0.00256836:0.853872:0.841437:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056337 ES:SE:LP:AF:ID  0.00242589:0.00417211:0.251812:0.056337:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  -0.00118814:0.00282101:0.173925:0.123078:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025132 ES:SE:LP:AF:ID  0.000136603:0.00702515:0.00877392:0.025132:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122332 ES:SE:LP:AF:ID  -0.00139191:0.00282192:0.207608:0.122332:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134141 ES:SE:LP:AF:ID  -0.00527039:0.00277017:1.24413:0.134141:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011558 ES:SE:LP:AF:ID  -0.0031352:0.00987285:0.124939:0.011558:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006101 ES:SE:LP:AF:ID  -0.013157:0.0125373:0.537602:0.006101:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037602 ES:SE:LP:AF:ID  -0.0109724:0.00487031:1.61979:0.037602:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837027 ES:SE:LP:AF:ID  0.00417313:0.00248459:1.03152:0.837027:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836731 ES:SE:LP:AF:ID  0.00432742:0.00248277:1.09151:0.836731:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  0.00164934:0.00266787:0.267606:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131005 ES:SE:LP:AF:ID  -0.00174893:0.00267473:0.29243:0.131005:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038048 ES:SE:LP:AF:ID  -0.0108856:0.00479391:1.63827:0.038048:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038294 ES:SE:LP:AF:ID  -0.0109574:0.0047642:1.67778:0.038294:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867975 ES:SE:LP:AF:ID  0.00173172:0.00266358:0.283997:0.867975:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868049 ES:SE:LP:AF:ID  0.00204169:0.00266467:0.356547:0.868049:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038202 ES:SE:LP:AF:ID  -0.0109747:0.0047862:1.65758:0.038202:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867986 ES:SE:LP:AF:ID  0.00171937:0.00266352:0.283997:0.867986:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005395 ES:SE:LP:AF:ID  -0.0213409:0.0133494:0.958607:0.005395:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836157 ES:SE:LP:AF:ID  0.00412001:0.00247551:1.01773:0.836157:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038205 ES:SE:LP:AF:ID  -0.0109682:0.00479319:1.65758:0.038205:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836791 ES:SE:LP:AF:ID  0.00397589:0.00248229:0.958607:0.836791:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01303  ES:SE:LP:AF:ID  0.00229955:0.00898045:0.09691:0.01303:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005662 ES:SE:LP:AF:ID  0.0127389:0.0133316:0.468521:0.005662:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838107 ES:SE:LP:AF:ID  0.00324474:0.00251723:0.69897:0.838107:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868227 ES:SE:LP:AF:ID  0.00142813:0.00266009:0.229148:0.868227:rs3115858