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.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_4096.vcf.gz --id UKB-b:3499 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_4096.txt.gz --cohort_controls 147326 --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-3499/UKB-b-3499_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3499/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:43 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3499/UKB-b-3499_data.vcf.gz ...
Read summary statistics for 9307147 SNPs.
Dropped 10319 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, 1287962 SNPs remain.
After merging with regression SNP LD, 1287962 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0018 (0.0031)
Lambda GC: 1.0018
Mean Chi^2: 1.0034
Intercept: 0.9982 (0.0059)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:45:25 2019
Total time elapsed: 1.0m:41.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1,
    "mean_EFFECT": -5.8915e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 4,
    "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": 112092,
    "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": 1287962,
    "ldsc_nsnp_merge_regression_ld": 1287962,
    "ldsc_observed_scale_h2_beta": 0.0018,
    "ldsc_observed_scale_h2_se": 0.0031,
    "ldsc_intercept_beta": 0.9982,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0018,
    "ldsc_mean_chisq": 1.0034,
    "ldsc_ratio": -0.5294
}

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 9296880 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 9307147 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 8.635137e+00 5.754130e+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 7.881118e+07 5.630824e+07 828.0000000 3.250169e+07 6.939391e+07 1.145412e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.900000e-06 1.516400e-03 -0.0198907 -5.703000e-04 -1.910000e-05 5.235000e-04 2.318050e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.194800e-03 9.431000e-04 0.0004008 4.822000e-04 7.618000e-04 1.637900e-03 1.391030e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.003546e-01 2.884455e-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 5.003544e-01 2.884178e-01 0.0000000 2.510881e-01 5.001154e-01 7.500215e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.137724e-01 2.578154e-01 0.0023760 1.749500e-02 9.250800e-02 3.356450e-01 9.976240e-01 ▇▂▁▁▁
numeric AF_reference 112092 0.9879564 NA NA NA NA NA NA NA 2.147860e-01 2.496050e-01 0.0000000 1.477640e-02 1.110220e-01 3.354630e-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 0.0011979 0.0007392 0.1100001 0.1051366 0.623858 0.7821490 NA
1 54676 rs2462492 C T -0.0008371 0.0007340 0.2500000 0.2541090 0.399250 NA NA
1 86028 rs114608975 T C -0.0008170 0.0011700 0.4899999 0.4850045 0.103752 0.0277556 NA
1 91536 rs6702460 G T -0.0004380 0.0007232 0.5400003 0.5447621 0.456216 0.4207270 NA
1 234313 rs8179466 C T -0.0020416 0.0014289 0.1499999 0.1530447 0.074438 NA NA
1 534192 rs6680723 C T -0.0000587 0.0008262 0.9400001 0.9433107 0.241211 NA NA
1 546697 rs12025928 A G 0.0015223 0.0010253 0.1400000 0.1376073 0.913033 NA NA
1 693731 rs12238997 A G 0.0012418 0.0006893 0.0719996 0.0716096 0.116868 0.1417730 NA
1 705882 rs72631875 G A -0.0017164 0.0010074 0.0879995 0.0884118 0.067673 0.0315495 NA
1 706368 rs55727773 A G -0.0009877 0.0005102 0.0530005 0.0528656 0.514917 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0002469 0.0006174 0.6899999 0.6892687 0.137270 0.2052720 NA
22 51219387 rs9616832 T C -0.0008051 0.0008024 0.3200000 0.3157336 0.072942 0.0654952 NA
22 51219704 rs147475742 G A -0.0010072 0.0010711 0.3500000 0.3470330 0.041769 0.0473243 NA
22 51221190 rs369304721 G A -0.0005054 0.0010739 0.6400000 0.6379135 0.049233 NA NA
22 51221731 rs115055839 T C -0.0007643 0.0008030 0.3400001 0.3412472 0.072418 0.0625000 NA
22 51222100 rs114553188 G T 0.0003008 0.0009418 0.7499995 0.7494320 0.054397 0.0880591 NA
22 51223637 rs375798137 G A 0.0003351 0.0009467 0.7199992 0.7233862 0.054005 0.0788738 NA
22 51229805 rs9616985 T C -0.0007707 0.0008060 0.3400001 0.3389511 0.072283 0.0730831 NA
22 51232488 rs376461333 A G -0.0020333 0.0018870 0.2800000 0.2812415 0.020191 NA NA
22 51237063 rs3896457 T C 0.0004060 0.0004906 0.4100001 0.4079176 0.297681 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623858 ES:SE:LP:AF:ID  0.00119789:0.000739235:0.958607:0.623858:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39925  ES:SE:LP:AF:ID  -0.000837093:0.000734018:0.60206:0.39925:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103752 ES:SE:LP:AF:ID  -0.000817011:0.00117004:0.309804:0.103752:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456216 ES:SE:LP:AF:ID  -0.000437985:0.000723192:0.267606:0.456216:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074438 ES:SE:LP:AF:ID  -0.00204164:0.00142886:0.823909:0.074438:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241211 ES:SE:LP:AF:ID  -5.87477e-05:0.00082616:0.0268721:0.241211:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913033 ES:SE:LP:AF:ID  0.00152231:0.00102529:0.853872:0.913033:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116868 ES:SE:LP:AF:ID  0.00124185:0.000689307:1.14267:0.116868:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067673 ES:SE:LP:AF:ID  -0.00171641:0.00100738:1.05552:0.067673:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514917 ES:SE:LP:AF:ID  -0.000987665:0.000510153:1.27572:0.514917:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033476 ES:SE:LP:AF:ID  0.00149755:0.00127665:0.619789:0.033476:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037183 ES:SE:LP:AF:ID  0.000978671:0.00115903:0.39794:0.037183:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03731  ES:SE:LP:AF:ID  0.00101016:0.00115448:0.420216:0.03731:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036961 ES:SE:LP:AF:ID  0.00101337:0.00116334:0.420216:0.036961:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016371 ES:SE:LP:AF:ID  -0.00113195:0.00181395:0.275724:0.016371:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  0.000892264:0.00115001:0.356547:0.03754:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037632 ES:SE:LP:AF:ID  0.0009124:0.00114639:0.366532:0.037632:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101682 ES:SE:LP:AF:ID  0.00106559:0.000839655:0.69897:0.101682:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95842  ES:SE:LP:AF:ID  -0.000650696:0.00110599:0.251812:0.95842:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031762 ES:SE:LP:AF:ID  0.000684831:0.00201604:0.136677:0.031762:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052659 ES:SE:LP:AF:ID  -0.0007068:0.0016311:0.180456:0.052659:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03711  ES:SE:LP:AF:ID  0.000778135:0.00115434:0.30103:0.03711:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037433 ES:SE:LP:AF:ID  0.000871027:0.0011441:0.346787:0.037433:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842124 ES:SE:LP:AF:ID  -0.000959174:0.000596592:0.958607:0.842124:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056069 ES:SE:LP:AF:ID  0.000681954:0.000968664:0.318759:0.056069:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122817 ES:SE:LP:AF:ID  0.00108889:0.000654092:1.01773:0.122817:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025733 ES:SE:LP:AF:ID  -0.000280292:0.00160928:0.0655015:0.025733:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122035 ES:SE:LP:AF:ID  0.00107213:0.000654421:1:0.122035:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133229 ES:SE:LP:AF:ID  0.00142284:0.000643895:1.56864:0.133229:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011245 ES:SE:LP:AF:ID  0.000392462:0.00233284:0.0604807:0.011245:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005812 ES:SE:LP:AF:ID  0.00199046:0.00299091:0.29243:0.005812:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037372 ES:SE:LP:AF:ID  0.000780029:0.00113248:0.309804:0.037372:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837796 ES:SE:LP:AF:ID  -0.000964183:0.00057755:1.02228:0.837796:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837407 ES:SE:LP:AF:ID  -0.00094027:0.000576854:1:0.837407:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869036 ES:SE:LP:AF:ID  -0.000973851:0.000619231:0.920819:0.869036:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130659 ES:SE:LP:AF:ID  0.00102276:0.000620437:1.00436:0.130659:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037867 ES:SE:LP:AF:ID  0.00120501:0.00111385:0.552842:0.037867:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038127 ES:SE:LP:AF:ID  0.00124505:0.00110668:0.585027:0.038127:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868367 ES:SE:LP:AF:ID  -0.000944997:0.000617974:0.886057:0.868367:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868472 ES:SE:LP:AF:ID  -0.000953096:0.000618216:0.920819:0.868472:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03805  ES:SE:LP:AF:ID  0.00118237:0.00111162:0.537602:0.03805:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86836  ES:SE:LP:AF:ID  -0.000944706:0.000617933:0.886057:0.86836:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005161 ES:SE:LP:AF:ID  0.00425046:0.00317192:0.744727:0.005161:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005132 ES:SE:LP:AF:ID  0.00429035:0.00317874:0.744727:0.005132:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.836906 ES:SE:LP:AF:ID  -0.000978651:0.000575413:1.05061:0.836906:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038059 ES:SE:LP:AF:ID  0.00118216:0.00111317:0.537602:0.038059:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837541 ES:SE:LP:AF:ID  -0.000984174:0.000577022:1.05552:0.837541:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013292 ES:SE:LP:AF:ID  -0.0014943:0.00206051:0.327902:0.013292:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005467 ES:SE:LP:AF:ID  0.00168986:0.00313181:0.229148:0.005467:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.83876  ES:SE:LP:AF:ID  -0.00102554:0.000584954:1.09691:0.83876:rs3131965