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_1011.vcf.gz --id UKB-b:4210 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_1011.txt.gz --cohort_controls 228298 --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-4210/UKB-b-4210_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4210/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:03 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4210/UKB-b-4210_data.vcf.gz ...
Read summary statistics for 9574543 SNPs.
Dropped 12260 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, 1288528 SNPs remain.
After merging with regression SNP LD, 1288528 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0252 (0.0025)
Lambda GC: 1.1378
Mean Chi^2: 1.1427
Intercept: 1.0319 (0.0069)
Ratio: 0.2235 (0.0486)
Analysis finished at Thu Oct 17 14:45:49 2019
Total time elapsed: 1.0m:45.61s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9492,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 52,
    "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": 144551,
    "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": 1288528,
    "ldsc_nsnp_merge_regression_ld": 1288528,
    "ldsc_observed_scale_h2_beta": 0.0252,
    "ldsc_observed_scale_h2_se": 0.0025,
    "ldsc_intercept_beta": 1.0319,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.1378,
    "ldsc_mean_chisq": 1.1427,
    "ldsc_ratio": 0.2235
}

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 9562344 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 9574543 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 8.627722e+00 5.751006e+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 7.883507e+07 5.629954e+07 828.0000000 3.255050e+07 6.943041e+07 1.145625e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.438000e-04 1.671390e-02 -0.2218770 -5.737500e-03 -2.910000e-05 5.637900e-03 7.156120e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.235880e-02 1.063320e-02 0.0038113 4.621800e-03 7.517200e-03 1.673880e-02 1.964650e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.835526e-01 2.933061e-01 0.0000000 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▆▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.835530e-01 2.932806e-01 0.0000000 2.249158e-01 4.780595e-01 7.376875e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.083342e-01 2.571363e-01 0.0015340 1.517400e-02 8.487200e-02 3.256695e-01 9.984660e-01 ▇▂▁▁▁
numeric AF_reference 144551 0.9849026 NA NA NA NA NA NA NA 2.103218e-01 2.488405e-01 0.0000000 1.297920e-02 1.048320e-01 3.274760e-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 0.0084536 0.0070183 0.2300001 0.2283961 0.624412 0.7821490 NA
1 54676 rs2462492 C T 0.0086850 0.0069491 0.2099999 0.2113695 0.400027 NA NA
1 86028 rs114608975 T C -0.0042580 0.0111461 0.6999999 0.7024481 0.103439 0.0277556 NA
1 91536 rs6702460 G T 0.0065324 0.0068396 0.3400001 0.3395304 0.457059 0.4207270 NA
1 234313 rs8179466 C T 0.0184000 0.0134623 0.1700000 0.1716943 0.074698 NA NA
1 534192 rs6680723 C T -0.0004843 0.0078055 0.9500000 0.9505225 0.241203 NA NA
1 546697 rs12025928 A G 0.0100822 0.0097260 0.2999998 0.2999109 0.913395 NA NA
1 693731 rs12238997 A G 0.0046997 0.0065320 0.4700002 0.4718380 0.116744 0.1417730 NA
1 705882 rs72631875 G A -0.0036327 0.0095896 0.6999999 0.7048213 0.067374 0.0315495 NA
1 706368 rs55727773 A G 0.0017581 0.0048517 0.7199992 0.7170720 0.516008 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0029484 0.0101744 0.7700005 0.7719791 0.042020 0.0473243 NA
22 51219766 rs182321900 C T 0.0269520 0.0477371 0.5700002 0.5723511 0.001902 NA NA
22 51220146 rs868950473 C T 0.0180497 0.0473840 0.6999999 0.7032597 0.001946 NA NA
22 51221190 rs369304721 G A 0.0005092 0.0101612 0.9599999 0.9600367 0.049589 NA NA
22 51221731 rs115055839 T C -0.0027561 0.0076000 0.7199992 0.7168681 0.073020 0.0625000 NA
22 51222100 rs114553188 G T 0.0152695 0.0089214 0.0870001 0.0869780 0.054698 0.0880591 NA
22 51223637 rs375798137 G A 0.0151474 0.0089614 0.0909997 0.0909721 0.054351 0.0788738 NA
22 51229805 rs9616985 T C -0.0030327 0.0076271 0.6899999 0.6909087 0.072860 0.0730831 NA
22 51232488 rs376461333 A G 0.0212960 0.0179113 0.2300001 0.2344514 0.020113 NA NA
22 51237063 rs3896457 T C -0.0072838 0.0046597 0.1199999 0.1180173 0.297869 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624412 ES:SE:LP:AF:ID  0.00845356:0.00701831:0.638272:0.624412:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400027 ES:SE:LP:AF:ID  0.00868502:0.00694908:0.677781:0.400027:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103439 ES:SE:LP:AF:ID  -0.00425801:0.0111461:0.154902:0.103439:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457059 ES:SE:LP:AF:ID  0.00653241:0.00683955:0.468521:0.457059:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074698 ES:SE:LP:AF:ID  0.0184:0.0134623:0.769551:0.074698:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241203 ES:SE:LP:AF:ID  -0.000484336:0.00780549:0.0222764:0.241203:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913395 ES:SE:LP:AF:ID  0.0100822:0.00972599:0.522879:0.913395:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116744 ES:SE:LP:AF:ID  0.00469972:0.006532:0.327902:0.116744:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067374 ES:SE:LP:AF:ID  -0.00363272:0.00958956:0.154902:0.067374:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516008 ES:SE:LP:AF:ID  0.00175813:0.00485169:0.142668:0.516008:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032933 ES:SE:LP:AF:ID  0.00111963:0.0122342:0.0315171:0.032933:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036523 ES:SE:LP:AF:ID  0.000575047:0.0111166:0.0177288:0.036523:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036646 ES:SE:LP:AF:ID  0.000939753:0.0110716:0.0315171:0.036646:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03635  ES:SE:LP:AF:ID  1.26467e-05:0.0111504:-0:0.03635:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016305 ES:SE:LP:AF:ID  0.010935:0.0171975:0.283997:0.016305:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036885 ES:SE:LP:AF:ID  0.000175041:0.0110268:0.00436481:0.036885:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03699  ES:SE:LP:AF:ID  0.000491786:0.0109869:0.0177288:0.03699:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101324 ES:SE:LP:AF:ID  0.00598754:0.00798723:0.346787:0.101324:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959366 ES:SE:LP:AF:ID  -0.00183404:0.0106217:0.0655015:0.959366:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031352 ES:SE:LP:AF:ID  0.0035427:0.0192833:0.0705811:0.031352:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053169 ES:SE:LP:AF:ID  -0.00337223:0.0153026:0.0809219:0.053169:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036501 ES:SE:LP:AF:ID  0.000554773:0.0110598:0.0177288:0.036501:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036803 ES:SE:LP:AF:ID  0.00143508:0.0109632:0.0457575:0.036803:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843113 ES:SE:LP:AF:ID  -0.00381037:0.00567168:0.30103:0.843113:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056024 ES:SE:LP:AF:ID  -4.54563e-05:0.0091783:-0:0.056024:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122624 ES:SE:LP:AF:ID  0.00557925:0.00619967:0.431798:0.122624:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025482 ES:SE:LP:AF:ID  -0.00800519:0.0153731:0.221849:0.025482:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121855 ES:SE:LP:AF:ID  0.00544542:0.00620243:0.420216:0.121855:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132851 ES:SE:LP:AF:ID  0.00389994:0.00611103:0.283997:0.132851:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011023 ES:SE:LP:AF:ID  -0.000737031:0.0224364:0.0132283:0.011023:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005894 ES:SE:LP:AF:ID  0.0225297:0.0282394:0.376751:0.005894:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002182 ES:SE:LP:AF:ID  0.0267264:0.0494752:0.229148:0.002182:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036716 ES:SE:LP:AF:ID  0.00206077:0.0108534:0.0705811:0.036716:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838866 ES:SE:LP:AF:ID  -0.00422798:0.00549429:0.356547:0.838866:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838524 ES:SE:LP:AF:ID  -0.00403:0.00548936:0.337242:0.838524:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869644 ES:SE:LP:AF:ID  -0.00692803:0.00588367:0.619789:0.869644:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129955 ES:SE:LP:AF:ID  0.00681956:0.00589809:0.60206:0.129955:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03725  ES:SE:LP:AF:ID  0.000910839:0.0106656:0.0315171:0.03725:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037498 ES:SE:LP:AF:ID  0.000854157:0.0105977:0.0268721:0.037498:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869008 ES:SE:LP:AF:ID  -0.00685125:0.00587312:0.619789:0.869008:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  -0.00716347:0.00587565:0.657577:0.86911:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037449 ES:SE:LP:AF:ID  0.000142963:0.0106445:0.00436481:0.037449:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869009 ES:SE:LP:AF:ID  -0.00674955:0.00587302:0.60206:0.869009:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005117 ES:SE:LP:AF:ID  0.0292019:0.0302013:0.481486:0.005117:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005085 ES:SE:LP:AF:ID  0.0288212:0.0302806:0.468521:0.005085:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837934 ES:SE:LP:AF:ID  -0.00430022:0.00547307:0.366532:0.837934:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037461 ES:SE:LP:AF:ID  0.000498171:0.0106593:0.0177288:0.037461:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838555 ES:SE:LP:AF:ID  -0.0045582:0.00548808:0.387216:0.838555:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013718 ES:SE:LP:AF:ID  0.0316577:0.0192002:1.00436:0.013718:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005435 ES:SE:LP:AF:ID  0.00399321:0.0298267:0.05061:0.005435:rs184270342