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_826.vcf.gz --id UKB-b:1712 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_826.txt.gz --cohort_controls 263315 --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-1712/UKB-b-1712_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1712/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:34 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1712/UKB-b-1712_data.vcf.gz ...
Read summary statistics for 9680626 SNPs.
Dropped 13107 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, 1288743 SNPs remain.
After merging with regression SNP LD, 1288743 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0263 (0.0024)
Lambda GC: 1.1654
Mean Chi^2: 1.1754
Intercept: 1.0412 (0.0066)
Ratio: 0.235 (0.0376)
Analysis finished at Thu Oct 17 14:47:03 2019
Total time elapsed: 1.0m:29.26s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9496,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 55,
    "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": 157894,
    "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": 1288743,
    "ldsc_nsnp_merge_regression_ld": 1288743,
    "ldsc_observed_scale_h2_beta": 0.0263,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0412,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.1654,
    "ldsc_mean_chisq": 1.1754,
    "ldsc_ratio": 0.2349
}

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 9667583 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 9680626 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 8.626193e+00 5.750246e+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 7.884193e+07 5.629522e+07 828.0000000 3.256133e+07 6.944612e+07 1.145726e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.286000e-04 1.031560e-02 -0.1532460 -3.288400e-03 4.910000e-05 3.438900e-03 1.767880e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.422200e-03 6.597400e-03 0.0022124 2.691800e-03 4.428100e-03 9.999300e-03 1.159690e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.817645e-01 2.935980e-01 0.0000000 2.200002e-01 4.700002e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.817640e-01 2.935725e-01 0.0000000 2.228032e-01 4.749650e-01 7.364002e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.064731e-01 2.570242e-01 0.0013300 1.439400e-02 8.218900e-02 3.222850e-01 9.986700e-01 ▇▂▁▁▁
numeric AF_reference 157894 0.9836897 NA NA NA NA NA NA NA 2.089526e-01 2.486152e-01 0.0000000 1.257990e-02 1.030350e-01 3.246810e-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 -0.0013173 0.0040740 0.7499995 0.7464385 0.623911 0.7821490 NA
1 54676 rs2462492 C T 0.0008584 0.0040314 0.8300000 0.8313904 0.400552 NA NA
1 86028 rs114608975 T C 0.0042394 0.0064405 0.5099998 0.5103858 0.103552 0.0277556 NA
1 91536 rs6702460 G T -0.0032104 0.0039716 0.4199997 0.4188986 0.456762 0.4207270 NA
1 234313 rs8179466 C T -0.0068851 0.0077984 0.3800004 0.3772987 0.074795 NA NA
1 534192 rs6680723 C T 0.0062496 0.0045379 0.1700000 0.1684557 0.241037 NA NA
1 546697 rs12025928 A G 0.0023586 0.0056637 0.6800001 0.6770926 0.913643 NA NA
1 693731 rs12238997 A G -0.0006219 0.0037951 0.8700001 0.8698394 0.116242 0.1417730 NA
1 705882 rs72631875 G A -0.0020820 0.0055809 0.7099994 0.7090994 0.067004 0.0315495 NA
1 706368 rs55727773 A G -0.0017127 0.0028136 0.5400003 0.5427159 0.515532 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0049752 0.0058944 0.4000000 0.3986381 0.042156 0.0473243 NA
22 51219766 rs182321900 C T 0.0286927 0.0271382 0.2900000 0.2903834 0.001999 NA NA
22 51220146 rs868950473 C T 0.0207778 0.0268885 0.4400003 0.4396767 0.002048 NA NA
22 51221190 rs369304721 G A -0.0068904 0.0058853 0.2399999 0.2416905 0.049932 NA NA
22 51221731 rs115055839 T C -0.0053825 0.0044052 0.2200002 0.2217646 0.073476 0.0625000 NA
22 51222100 rs114553188 G T 0.0136713 0.0051999 0.0086000 0.0085597 0.054481 0.0880591 NA
22 51223637 rs375798137 G A 0.0136696 0.0052248 0.0089000 0.0088895 0.054120 0.0788738 NA
22 51229805 rs9616985 T C -0.0056693 0.0044214 0.2000000 0.1997594 0.073307 0.0730831 NA
22 51232488 rs376461333 A G 0.0206911 0.0104268 0.0470002 0.0472096 0.020030 NA NA
22 51237063 rs3896457 T C -0.0063061 0.0027099 0.0200000 0.0199636 0.297367 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623911 ES:SE:LP:AF:ID  -0.00131727:0.00407396:0.124939:0.623911:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400552 ES:SE:LP:AF:ID  0.000858354:0.00403137:0.0809219:0.400552:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103552 ES:SE:LP:AF:ID  0.00423935:0.00644046:0.29243:0.103552:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456762 ES:SE:LP:AF:ID  -0.00321041:0.00397164:0.376751:0.456762:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074795 ES:SE:LP:AF:ID  -0.00688513:0.00779845:0.420216:0.074795:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241037 ES:SE:LP:AF:ID  0.00624956:0.00453793:0.769551:0.241037:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913643 ES:SE:LP:AF:ID  0.00235856:0.00566371:0.167491:0.913643:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116242 ES:SE:LP:AF:ID  -0.000621881:0.00379514:0.0604807:0.116242:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067004 ES:SE:LP:AF:ID  -0.00208204:0.00558089:0.148742:0.067004:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515532 ES:SE:LP:AF:ID  -0.0017127:0.00281365:0.267606:0.515532:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033262 ES:SE:LP:AF:ID  -0.0201138:0.0070691:2.35655:0.033262:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036885 ES:SE:LP:AF:ID  -0.0156475:0.00642434:1.82391:0.036885:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036991 ES:SE:LP:AF:ID  -0.0155196:0.00640193:1.82391:0.036991:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036704 ES:SE:LP:AF:ID  -0.016673:0.00644583:2.01323:0.036704:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016449 ES:SE:LP:AF:ID  -0.0230681:0.00993996:1.69897:0.016449:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037252 ES:SE:LP:AF:ID  -0.0161278:0.0063744:1.95861:0.037252:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037351 ES:SE:LP:AF:ID  -0.0159663:0.00635282:1.92082:0.037351:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101111 ES:SE:LP:AF:ID  -0.0074526:0.00464974:0.958607:0.101111:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958732 ES:SE:LP:AF:ID  0.0136854:0.00611986:1.60206:0.958732:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031504 ES:SE:LP:AF:ID  -0.00263124:0.0111306:0.091515:0.031504:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05322  ES:SE:LP:AF:ID  0.00609723:0.00886863:0.309804:0.05322:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036855 ES:SE:LP:AF:ID  -0.0149831:0.00639499:1.72125:0.036855:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037164 ES:SE:LP:AF:ID  -0.0148885:0.00633688:1.72125:0.037164:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842936 ES:SE:LP:AF:ID  0.00325889:0.00328554:0.49485:0.842936:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055786 ES:SE:LP:AF:ID  -6.2935e-05:0.00533563:0.00436481:0.055786:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122245 ES:SE:LP:AF:ID  -0.000483344:0.00359938:0.05061:0.122245:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025719 ES:SE:LP:AF:ID  0.0122862:0.0088613:0.769551:0.025719:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12146  ES:SE:LP:AF:ID  -0.000695479:0.00360094:0.0705811:0.12146:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132454 ES:SE:LP:AF:ID  -0.00143583:0.00354853:0.161151:0.132454:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011212 ES:SE:LP:AF:ID  -0.00469956:0.0129032:0.142668:0.011212:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005729 ES:SE:LP:AF:ID  0.00640036:0.0166363:0.154902:0.005729:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002325 ES:SE:LP:AF:ID  0.0212614:0.0276461:0.356547:0.002325:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.037098 ES:SE:LP:AF:ID  -0.013611:0.00627101:1.52288:0.037098:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838746 ES:SE:LP:AF:ID  0.000677058:0.00318345:0.0809219:0.838746:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838328 ES:SE:LP:AF:ID  0.000837014:0.00317956:0.102373:0.838328:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  -0.00256381:0.0034131:0.346787:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.1299   ES:SE:LP:AF:ID  0.00259636:0.00341962:0.346787:0.1299:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037607 ES:SE:LP:AF:ID  -0.013894:0.00616453:1.61979:0.037607:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037859 ES:SE:LP:AF:ID  -0.0139516:0.00612519:1.63827:0.037859:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869083 ES:SE:LP:AF:ID  -0.00234775:0.00340587:0.309804:0.869083:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869186 ES:SE:LP:AF:ID  -0.00219637:0.00340731:0.283997:0.869186:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037814 ES:SE:LP:AF:ID  -0.0138559:0.00615208:1.61979:0.037814:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869088 ES:SE:LP:AF:ID  -0.00241403:0.0034059:0.318759:0.869088:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005124 ES:SE:LP:AF:ID  0.0354845:0.0174975:1.36653:0.005124:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509  ES:SE:LP:AF:ID  0.037141:0.017544:1.46852:0.00509:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837764 ES:SE:LP:AF:ID  0.00093184:0.00317074:0.113509:0.837764:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037828 ES:SE:LP:AF:ID  -0.0142199:0.00616076:1.67778:0.037828:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838416 ES:SE:LP:AF:ID  0.000741607:0.00317975:0.0861861:0.838416:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013715 ES:SE:LP:AF:ID  -0.0195044:0.0111503:1.09691:0.013715:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005528 ES:SE:LP:AF:ID  0.0117162:0.0172042:0.30103:0.005528:rs184270342