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_5089.vcf.gz --id UKB-b:5090 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5089.txt.gz --cohort_controls 99071 --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-5090/UKB-b-5090_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5090/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:00 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5090/UKB-b-5090_data.vcf.gz ...
Read summary statistics for 9019439 SNPs.
Dropped 8786 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, 1287265 SNPs remain.
After merging with regression SNP LD, 1287265 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0235 (0.0053)
Lambda GC: 1.0558
Mean Chi^2: 1.0618
Intercept: 1.016 (0.0062)
Ratio: 0.2586 (0.1006)
Analysis finished at Thu Oct 17 14:46:30 2019
Total time elapsed: 1.0m:29.34s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 15,
    "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": 93942,
    "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": 1287265,
    "ldsc_nsnp_merge_regression_ld": 1287265,
    "ldsc_observed_scale_h2_beta": 0.0235,
    "ldsc_observed_scale_h2_se": 0.0053,
    "ldsc_intercept_beta": 1.016,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0558,
    "ldsc_mean_chisq": 1.0618,
    "ldsc_ratio": 0.2589
}

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 9010693 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 9019439 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 8.642992e+00 5.758157e+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 7.878496e+07 5.633944e+07 828.0000000 3.242930e+07 6.934579e+07 1.145385e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -8.070000e-05 1.483050e-02 -0.1732350 -5.829200e-03 -3.850000e-05 5.708700e-03 1.611290e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.181150e-02 8.676400e-03 0.0042802 5.104600e-03 7.825600e-03 1.620530e-02 9.937080e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.934887e-01 2.902872e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.934895e-01 2.902615e-01 0.0000000 2.408051e-01 4.912452e-01 7.448650e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.199583e-01 2.585105e-01 0.0035330 2.038700e-02 1.011670e-01 3.468000e-01 9.964670e-01 ▇▂▁▁▁
numeric AF_reference 93942 0.9895845 NA NA NA NA NA NA NA 2.202909e-01 2.504123e-01 0.0000000 1.777160e-02 1.186100e-01 3.452480e-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 0.0001930 0.0079093 0.9800000 0.9805356 0.623764 0.7821490 NA
1 54676 rs2462492 C T -0.0088453 0.0078575 0.2599998 0.2602863 0.398686 NA NA
1 86028 rs114608975 T C 0.0019377 0.0124699 0.8800001 0.8765144 0.103973 0.0277556 NA
1 91536 rs6702460 G T -0.0047081 0.0077233 0.5400003 0.5421285 0.455613 0.4207270 NA
1 234313 rs8179466 C T -0.0133456 0.0151428 0.3800004 0.3781465 0.074778 NA NA
1 534192 rs6680723 C T -0.0112852 0.0088338 0.2000000 0.2014270 0.240464 NA NA
1 546697 rs12025928 A G 0.0083468 0.0109489 0.4500005 0.4458557 0.912871 NA NA
1 693731 rs12238997 A G 0.0039516 0.0073454 0.5900000 0.5906002 0.117768 0.1417730 NA
1 705882 rs72631875 G A -0.0128671 0.0107501 0.2300001 0.2313345 0.067645 0.0315495 NA
1 706368 rs55727773 A G -0.0112816 0.0054467 0.0379997 0.0383340 0.514180 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0108458 0.0065887 0.1000000 0.0997388 0.137223 0.2052720 NA
22 51219387 rs9616832 T C -0.0162888 0.0085875 0.0580003 0.0578539 0.072606 0.0654952 NA
22 51219704 rs147475742 G A -0.0229870 0.0114150 0.0439997 0.0440354 0.041858 0.0473243 NA
22 51221190 rs369304721 G A -0.0189981 0.0114882 0.0980009 0.0981874 0.049110 NA NA
22 51221731 rs115055839 T C -0.0154941 0.0085901 0.0710003 0.0712749 0.072139 0.0625000 NA
22 51222100 rs114553188 G T -0.0088709 0.0100400 0.3800004 0.3769350 0.054533 0.0880591 NA
22 51223637 rs375798137 G A -0.0084097 0.0100924 0.4000000 0.4046933 0.054145 0.0788738 NA
22 51229805 rs9616985 T C -0.0158858 0.0086212 0.0649995 0.0653814 0.072001 0.0730831 NA
22 51232488 rs376461333 A G -0.0320778 0.0203234 0.1100001 0.1144811 0.020054 NA NA
22 51237063 rs3896457 T C -0.0045901 0.0052412 0.3800004 0.3811509 0.298305 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.000192967:0.00790932:0.00877392:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398686 ES:SE:LP:AF:ID  -0.00884527:0.00785747:0.585027:0.398686:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103973 ES:SE:LP:AF:ID  0.00193769:0.0124699:0.0555173:0.103973:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455613 ES:SE:LP:AF:ID  -0.00470811:0.00772331:0.267606:0.455613:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074778 ES:SE:LP:AF:ID  -0.0133456:0.0151428:0.420216:0.074778:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240464 ES:SE:LP:AF:ID  -0.0112852:0.00883384:0.69897:0.240464:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912871 ES:SE:LP:AF:ID  0.00834681:0.0109489:0.346787:0.912871:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117768 ES:SE:LP:AF:ID  0.00395159:0.00734542:0.229148:0.117768:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067645 ES:SE:LP:AF:ID  -0.0128671:0.0107501:0.638272:0.067645:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51418  ES:SE:LP:AF:ID  -0.0112816:0.00544672:1.42022:0.51418:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033663 ES:SE:LP:AF:ID  -0.00899157:0.0135898:0.29243:0.033663:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037324 ES:SE:LP:AF:ID  -0.00812181:0.0123603:0.29243:0.037324:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037404 ES:SE:LP:AF:ID  -0.00823198:0.0123209:0.30103:0.037404:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037098 ES:SE:LP:AF:ID  -0.00845029:0.0124056:0.30103:0.037098:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016724 ES:SE:LP:AF:ID  0.0110572:0.0191346:0.251812:0.016724:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037665 ES:SE:LP:AF:ID  -0.00769825:0.0122674:0.275724:0.037665:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037752 ES:SE:LP:AF:ID  -0.00706716:0.0122297:0.251812:0.037752:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101285 ES:SE:LP:AF:ID  0.0224594:0.00900484:1.88606:0.101285:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958033 ES:SE:LP:AF:ID  0.00916884:0.0117634:0.356547:0.958033:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031831 ES:SE:LP:AF:ID  0.0224454:0.021518:0.522879:0.031831:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052516 ES:SE:LP:AF:ID  0.00112249:0.0174068:0.0222764:0.052516:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037209 ES:SE:LP:AF:ID  -0.00791028:0.0123163:0.283997:0.037209:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037525 ES:SE:LP:AF:ID  -0.0079102:0.0122119:0.283997:0.037525:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840936 ES:SE:LP:AF:ID  -0.00253423:0.00636113:0.161151:0.840936:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056184 ES:SE:LP:AF:ID  0.00673959:0.0103488:0.29243:0.056184:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123696 ES:SE:LP:AF:ID  0.00289453:0.00697228:0.167491:0.123696:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025917 ES:SE:LP:AF:ID  -0.0272952:0.0171097:0.958607:0.025917:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12289  ES:SE:LP:AF:ID  0.0028783:0.00697583:0.167491:0.12289:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133662 ES:SE:LP:AF:ID  0.00147765:0.00687579:0.0809219:0.133662:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011245 ES:SE:LP:AF:ID  -0.0208742:0.0248885:0.39794:0.011245:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006012 ES:SE:LP:AF:ID  -0.0206943:0.0313443:0.29243:0.006012:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037495 ES:SE:LP:AF:ID  -0.00961982:0.0120762:0.366532:0.037495:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836696 ES:SE:LP:AF:ID  -0.00123371:0.00615554:0.0757207:0.836696:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836264 ES:SE:LP:AF:ID  -0.00164511:0.00614855:0.102373:0.836264:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.867973 ES:SE:LP:AF:ID  -0.00238635:0.00659526:0.142668:0.867973:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131689 ES:SE:LP:AF:ID  0.00298305:0.00660943:0.187087:0.131689:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037937 ES:SE:LP:AF:ID  -0.00835448:0.0118861:0.318759:0.037937:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038185 ES:SE:LP:AF:ID  -0.00771282:0.0118125:0.29243:0.038185:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867277 ES:SE:LP:AF:ID  -0.002725:0.00658194:0.167491:0.867277:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867378 ES:SE:LP:AF:ID  -0.00243741:0.00658502:0.148742:0.867378:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038137 ES:SE:LP:AF:ID  -0.00762062:0.0118596:0.283997:0.038137:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867276 ES:SE:LP:AF:ID  -0.00272129:0.00658153:0.167491:0.867276:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  0.0651074:0.0340923:1.25181:0.005088:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005055 ES:SE:LP:AF:ID  0.0648925:0.0341872:1.23657:0.005055:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835809 ES:SE:LP:AF:ID  -0.00192434:0.00613542:0.124939:0.835809:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038155 ES:SE:LP:AF:ID  -0.00746886:0.0118752:0.275724:0.038155:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836413 ES:SE:LP:AF:ID  -0.00216461:0.00615185:0.142668:0.836413:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013199 ES:SE:LP:AF:ID  -0.0272173:0.0220559:0.657577:0.013199:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005513 ES:SE:LP:AF:ID  0.0337956:0.0333328:0.508638:0.005513:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837704 ES:SE:LP:AF:ID  -0.00148875:0.00623606:0.091515:0.837704:rs3131965