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_2936.vcf.gz --id UKB-b:12412 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2936.txt.gz --cohort_controls 112268 --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-12412/UKB-b-12412_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12412/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12412/UKB-b-12412_data.vcf.gz ...
Read summary statistics for 9104569 SNPs.
Dropped 9196 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, 1287433 SNPs remain.
After merging with regression SNP LD, 1287433 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0118 (0.0042)
Lambda GC: 1.0481
Mean Chi^2: 1.0502
Intercept: 1.0242 (0.0061)
Ratio: 0.4823 (0.1207)
Analysis finished at Thu Oct 17 14:43:37 2019
Total time elapsed: 1.0m:43.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.948,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 98596,
    "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": 1287433,
    "ldsc_nsnp_merge_regression_ld": 1287433,
    "ldsc_observed_scale_h2_beta": 0.0118,
    "ldsc_observed_scale_h2_se": 0.0042,
    "ldsc_intercept_beta": 1.0242,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0481,
    "ldsc_mean_chisq": 1.0502,
    "ldsc_ratio": 0.4821
}

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 9095414 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 9104569 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 8.640537e+00 5.756887e+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 7.879460e+07 5.632721e+07 828.0000000 3.245509e+07 6.936708e+07 1.145284e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -7.300000e-05 5.692000e-03 -0.0788726 -2.192000e-03 -1.540000e-05 2.142000e-03 5.548040e-02 ▁▁▇▃▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.491100e-03 3.368700e-03 0.0015899 1.902200e-03 2.942200e-03 6.162700e-03 3.591660e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.936235e-01 2.906008e-01 0.0000001 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.936231e-01 2.905741e-01 0.0000001 2.400105e-01 4.908227e-01 7.458423e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.180214e-01 2.583047e-01 0.0031180 1.943100e-02 9.842500e-02 3.434420e-01 9.968820e-01 ▇▂▁▁▁
numeric AF_reference 98596 0.9891707 NA NA NA NA NA NA NA 2.184965e-01 2.501736e-01 0.0000000 1.657350e-02 1.162140e-01 3.422520e-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 0.0021470 0.0029305 0.4600002 0.4637928 0.624849 0.7821490 NA
1 54676 rs2462492 C T -0.0045649 0.0028979 0.1199999 0.1151952 0.400633 NA NA
1 86028 rs114608975 T C 0.0150736 0.0046267 0.0011000 0.0011221 0.103642 0.0277556 NA
1 91536 rs6702460 G T -0.0003481 0.0028507 0.9000000 0.9028163 0.457815 0.4207270 NA
1 234313 rs8179466 C T -0.0096160 0.0055978 0.0860003 0.0858316 0.074851 NA NA
1 534192 rs6680723 C T -0.0028584 0.0032707 0.3800004 0.3821575 0.240623 NA NA
1 546697 rs12025928 A G 0.0052980 0.0040695 0.1900002 0.1929489 0.913535 NA NA
1 693731 rs12238997 A G -0.0039572 0.0027422 0.1499999 0.1490063 0.115845 0.1417730 NA
1 705882 rs72631875 G A -0.0023670 0.0040174 0.5600000 0.5557285 0.066907 0.0315495 NA
1 706368 rs55727773 A G -0.0004331 0.0020282 0.8300000 0.8309222 0.515288 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0015492 0.0024451 0.5300002 0.5263530 0.138318 0.2052720 NA
22 51219387 rs9616832 T C -0.0011256 0.0031697 0.7199992 0.7225045 0.073857 0.0654952 NA
22 51219704 rs147475742 G A -0.0004302 0.0042464 0.9199999 0.9193137 0.042038 0.0473243 NA
22 51221190 rs369304721 G A -0.0018992 0.0042525 0.6600001 0.6551491 0.049595 NA NA
22 51221731 rs115055839 T C -0.0013003 0.0031720 0.6800001 0.6818597 0.073310 0.0625000 NA
22 51222100 rs114553188 G T -0.0015048 0.0037295 0.6899999 0.6865917 0.054615 0.0880591 NA
22 51223637 rs375798137 G A -0.0015577 0.0037468 0.6800001 0.6776078 0.054253 0.0788738 NA
22 51229805 rs9616985 T C -0.0012505 0.0031831 0.6899999 0.6944222 0.073172 0.0730831 NA
22 51232488 rs376461333 A G -0.0012987 0.0075174 0.8600001 0.8628369 0.020082 NA NA
22 51237063 rs3896457 T C -0.0004512 0.0019472 0.8200001 0.8167638 0.299107 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624849 ES:SE:LP:AF:ID  0.00214696:0.00293054:0.337242:0.624849:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400633 ES:SE:LP:AF:ID  -0.00456493:0.00289788:0.920819:0.400633:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103642 ES:SE:LP:AF:ID  0.0150736:0.00462668:2.95861:0.103642:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457815 ES:SE:LP:AF:ID  -0.000348083:0.0028507:0.0457575:0.457815:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074851 ES:SE:LP:AF:ID  -0.00961598:0.00559782:1.0655:0.074851:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240623 ES:SE:LP:AF:ID  -0.0028584:0.00327075:0.420216:0.240623:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913535 ES:SE:LP:AF:ID  0.00529805:0.00406946:0.721246:0.913535:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115845 ES:SE:LP:AF:ID  -0.00395719:0.00274224:0.823909:0.115845:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066907 ES:SE:LP:AF:ID  -0.00236702:0.00401736:0.251812:0.066907:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515288 ES:SE:LP:AF:ID  -0.000433057:0.00202819:0.0809219:0.515288:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032959 ES:SE:LP:AF:ID  0.00640848:0.0051085:0.677781:0.032959:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036582 ES:SE:LP:AF:ID  0.00529738:0.00464096:0.60206:0.036582:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036715 ES:SE:LP:AF:ID  0.00521556:0.00462171:0.585027:0.036715:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036396 ES:SE:LP:AF:ID  0.00566492:0.00465615:0.657577:0.036396:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016541 ES:SE:LP:AF:ID  0.00688584:0.00710077:0.481486:0.016541:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036949 ES:SE:LP:AF:ID  0.00506004:0.0046028:0.568636:0.036949:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037049 ES:SE:LP:AF:ID  0.00491943:0.00458744:0.552842:0.037049:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101363 ES:SE:LP:AF:ID  0.00259449:0.00333686:0.356547:0.101363:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959047 ES:SE:LP:AF:ID  -0.00234063:0.00442371:0.221849:0.959047:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03155  ES:SE:LP:AF:ID  0.000691995:0.00798158:0.0315171:0.03155:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05316  ES:SE:LP:AF:ID  -0.00226524:0.00641376:0.142668:0.05316:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036577 ES:SE:LP:AF:ID  0.00516964:0.00461736:0.585027:0.036577:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036824 ES:SE:LP:AF:ID  0.00433032:0.00457976:0.468521:0.036824:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843515 ES:SE:LP:AF:ID  0.00238466:0.00237198:0.508638:0.843515:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055337 ES:SE:LP:AF:ID  -0.00392279:0.00386225:0.508638:0.055337:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12211  ES:SE:LP:AF:ID  -0.0032026:0.00259507:0.657577:0.12211:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025775 ES:SE:LP:AF:ID  -0.00353675:0.00636987:0.236572:0.025775:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121376 ES:SE:LP:AF:ID  -0.00302685:0.0025958:0.619789:0.121376:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.131947 ES:SE:LP:AF:ID  -0.00265712:0.00256413:0.522879:0.131947:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.010932 ES:SE:LP:AF:ID  -0.00139032:0.00940952:0.0555173:0.010932:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.00585  ES:SE:LP:AF:ID  0.00172139:0.0118879:0.0555173:0.00585:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036807 ES:SE:LP:AF:ID  0.00472874:0.00452822:0.522879:0.036807:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839267 ES:SE:LP:AF:ID  0.00229557:0.00229898:0.49485:0.839267:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838926 ES:SE:LP:AF:ID  0.00240023:0.00229654:0.522879:0.838926:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86987  ES:SE:LP:AF:ID  0.00402579:0.00246129:1:0.86987:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129766 ES:SE:LP:AF:ID  -0.00424671:0.00246634:1.07058:0.129766:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037276 ES:SE:LP:AF:ID  0.00452506:0.00445407:0.508638:0.037276:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  0.00414223:0.00442432:0.455932:0.03754:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86921  ES:SE:LP:AF:ID  0.0042529:0.00245637:1.08092:0.86921:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869316 ES:SE:LP:AF:ID  0.0042665:0.00245728:1.08092:0.869316:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037485 ES:SE:LP:AF:ID  0.00476381:0.00444428:0.552842:0.037485:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869219 ES:SE:LP:AF:ID  0.0042796:0.00245647:1.09151:0.869219:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005047 ES:SE:LP:AF:ID  -0.0067898:0.0127016:0.229148:0.005047:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005015 ES:SE:LP:AF:ID  -0.00664713:0.0127277:0.221849:0.005015:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838363 ES:SE:LP:AF:ID  0.00252081:0.00229021:0.568636:0.838363:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037493 ES:SE:LP:AF:ID  0.00444557:0.00445103:0.49485:0.037493:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838957 ES:SE:LP:AF:ID  0.00275232:0.00229639:0.638272:0.838957:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013912 ES:SE:LP:AF:ID  -0.000892088:0.00794705:0.0409586:0.013912:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005512 ES:SE:LP:AF:ID  0.00740491:0.0123927:0.259637:0.005512:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.840032 ES:SE:LP:AF:ID  0.00234414:0.00232706:0.508638:0.840032:rs3131965