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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}

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-4655/UKB-b-4655_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4655/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4655/UKB-b-4655_data.vcf.gz ...
Read summary statistics for 9809976 SNPs.
Dropped 14283 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, 1289058 SNPs remain.
After merging with regression SNP LD, 1289058 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.034 (0.0021)
Lambda GC: 1.2101
Mean Chi^2: 1.2338
Intercept: 1.0144 (0.0078)
Ratio: 0.0616 (0.0335)
Analysis finished at Thu Oct 17 14:46:22 2019
Total time elapsed: 1.0m:48.48s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9498,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 8,
    "n_p_sig": 95,
    "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": 181082,
    "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": 1289058,
    "ldsc_nsnp_merge_regression_ld": 1289058,
    "ldsc_observed_scale_h2_beta": 0.034,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.0144,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.2101,
    "ldsc_mean_chisq": 1.2338,
    "ldsc_ratio": 0.0616
}

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 1.000000 3 58 0 9795759 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9809976 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.622960e+00 5.748641e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.885940e+07 5.628697e+07 828.0000000 3.258588e+07 6.948636e+07 1.145937e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -2.790000e-05 1.734170e-02 -0.2440420 -5.598100e-03 -1.540000e-05 5.586200e-03 2.911780e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.247940e-02 1.165040e-02 0.0035435 4.332800e-03 7.231300e-03 1.660480e-02 1.860770e-01 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.778241e-01 2.942778e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.778244e-01 2.942524e-01 0.0000000 2.178952e-01 4.698735e-01 7.322236e-01 1.000000e+00 ▇▇▇▆▆
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.041582e-01 2.568442e-01 0.0010670 1.344600e-02 7.893700e-02 3.177190e-01 9.989330e-01 ▇▂▁▁▁
numeric AF_reference 181082 0.981541 NA NA NA NA NA NA NA 2.072957e-01 2.483637e-01 0.0000000 1.198080e-02 1.006390e-01 3.212860e-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 0.0057537 0.0065210 0.3800004 0.3775948 0.623637 0.7821490 NA
1 54676 rs2462492 C T -0.0002383 0.0064587 0.9699999 0.9705730 0.400285 NA NA
1 86028 rs114608975 T C 0.0016505 0.0103288 0.8700001 0.8730396 0.103567 0.0277556 NA
1 91536 rs6702460 G T 0.0046795 0.0063592 0.4600002 0.4618136 0.456749 0.4207270 NA
1 234313 rs8179466 C T 0.0144389 0.0125230 0.2500000 0.2489143 0.074589 NA NA
1 534192 rs6680723 C T 0.0082064 0.0072613 0.2599998 0.2584106 0.241261 NA NA
1 546697 rs12025928 A G -0.0020935 0.0090536 0.8200001 0.8171326 0.913315 NA NA
1 693731 rs12238997 A G 0.0095059 0.0060849 0.1199999 0.1182402 0.116485 0.1417730 NA
1 705882 rs72631875 G A -0.0060587 0.0089124 0.5000000 0.4966299 0.067468 0.0315495 NA
1 706368 rs55727773 A G -0.0043528 0.0045100 0.3300000 0.3344726 0.515729 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0127044 0.0094846 0.1800002 0.1804165 0.041835 0.0473243 NA
22 51219766 rs182321900 C T -0.0123802 0.0438712 0.7800007 0.7777946 0.001960 NA NA
22 51220146 rs868950473 C T -0.0158983 0.0434376 0.7099994 0.7143627 0.002014 NA NA
22 51221190 rs369304721 G A -0.0131184 0.0094570 0.1700000 0.1653930 0.049642 NA NA
22 51221731 rs115055839 T C -0.0111558 0.0070781 0.1199999 0.1150020 0.073063 0.0625000 NA
22 51222100 rs114553188 G T 0.0028223 0.0083196 0.7300002 0.7344357 0.054450 0.0880591 NA
22 51223637 rs375798137 G A 0.0028280 0.0083599 0.7400005 0.7351531 0.054082 0.0788738 NA
22 51229805 rs9616985 T C -0.0100702 0.0071027 0.1600000 0.1562507 0.072911 0.0730831 NA
22 51232488 rs376461333 A G 0.0066126 0.0167058 0.6899999 0.6922334 0.020028 NA NA
22 51237063 rs3896457 T C 0.0057662 0.0043416 0.1800002 0.1841366 0.298073 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623637 ES:SE:LP:AF:ID  0.0057537:0.00652098:0.420216:0.623637:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400285 ES:SE:LP:AF:ID  -0.000238259:0.00645869:0.0132283:0.400285:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103567 ES:SE:LP:AF:ID  0.00165053:0.0103288:0.0604807:0.103567:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456749 ES:SE:LP:AF:ID  0.00467952:0.00635922:0.337242:0.456749:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074589 ES:SE:LP:AF:ID  0.0144389:0.012523:0.60206:0.074589:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241261 ES:SE:LP:AF:ID  0.0082064:0.0072613:0.585027:0.241261:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913315 ES:SE:LP:AF:ID  -0.0020935:0.00905358:0.0861861:0.913315:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116485 ES:SE:LP:AF:ID  0.00950591:0.00608494:0.920819:0.116485:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067468 ES:SE:LP:AF:ID  -0.00605866:0.00891239:0.30103:0.067468:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515729 ES:SE:LP:AF:ID  -0.0043528:0.00451:0.481486:0.515729:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033059 ES:SE:LP:AF:ID  -0.0150595:0.0113651:0.721246:0.033059:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036709 ES:SE:LP:AF:ID  -0.0141227:0.0103203:0.769551:0.036709:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036834 ES:SE:LP:AF:ID  -0.013247:0.010279:0.69897:0.036834:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036524 ES:SE:LP:AF:ID  -0.014461:0.0103552:0.79588:0.036524:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016409 ES:SE:LP:AF:ID  0.0198313:0.0159584:0.677781:0.016409:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037072 ES:SE:LP:AF:ID  -0.0153032:0.0102396:0.853872:0.037072:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037173 ES:SE:LP:AF:ID  -0.0151581:0.0102042:0.853872:0.037173:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101636 ES:SE:LP:AF:ID  -0.00766838:0.00742762:0.522879:0.101636:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959078 ES:SE:LP:AF:ID  0.0133248:0.00985235:0.744727:0.959078:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031436 ES:SE:LP:AF:ID  -0.00515449:0.0179372:0.113509:0.031436:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053188 ES:SE:LP:AF:ID  -0.0144652:0.0142404:0.508638:0.053188:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036689 ES:SE:LP:AF:ID  -0.0153637:0.0102685:0.886057:0.036689:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037008 ES:SE:LP:AF:ID  -0.0138061:0.0101738:0.769551:0.037008:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843185 ES:SE:LP:AF:ID  -0.00393098:0.00527509:0.337242:0.843185:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055888 ES:SE:LP:AF:ID  0.0110455:0.00854056:0.69897:0.055888:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122317 ES:SE:LP:AF:ID  0.0105181:0.00577424:1.16115:0.122317:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025394 ES:SE:LP:AF:ID  -0.0184251:0.0143195:0.69897:0.025394:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121553 ES:SE:LP:AF:ID  0.00997022:0.00577653:1.07572:0.121553:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132461 ES:SE:LP:AF:ID  0.000618377:0.00569269:0.0409586:0.132461:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011088 ES:SE:LP:AF:ID  0.00175763:0.0207577:0.0315171:0.011088:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005702 ES:SE:LP:AF:ID  0.025484:0.0267476:0.468521:0.005702:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002251 ES:SE:LP:AF:ID  0.0253956:0.0450825:0.244125:0.002251:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036903 ES:SE:LP:AF:ID  -0.0134395:0.0100745:0.744727:0.036903:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838766 ES:SE:LP:AF:ID  -0.0014935:0.00510726:0.113509:0.838766:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838403 ES:SE:LP:AF:ID  -0.00177068:0.00510203:0.136677:0.838403:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869719 ES:SE:LP:AF:ID  -0.00738791:0.00547577:0.744727:0.869719:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129889 ES:SE:LP:AF:ID  0.00734318:0.00548804:0.744727:0.129889:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037433 ES:SE:LP:AF:ID  -0.0128731:0.00990129:0.721246:0.037433:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037668 ES:SE:LP:AF:ID  -0.0121333:0.00983975:0.657577:0.037668:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869079 ES:SE:LP:AF:ID  -0.00748038:0.00546556:0.769551:0.869079:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869165 ES:SE:LP:AF:ID  -0.00742061:0.00546771:0.769551:0.869165:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03763  ES:SE:LP:AF:ID  -0.0126761:0.00988203:0.69897:0.03763:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869083 ES:SE:LP:AF:ID  -0.0073609:0.00546547:0.744727:0.869083:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005188 ES:SE:LP:AF:ID  -0.01759:0.0278853:0.275724:0.005188:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005151 ES:SE:LP:AF:ID  -0.0169187:0.0279667:0.259637:0.005151:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837862 ES:SE:LP:AF:ID  -0.00141856:0.00508795:0.107905:0.837862:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037648 ES:SE:LP:AF:ID  -0.0131007:0.00989533:0.721246:0.037648:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838488 ES:SE:LP:AF:ID  -0.00147788:0.00510226:0.113509:0.838488:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013797 ES:SE:LP:AF:ID  -0.00705412:0.01779:0.161151:0.013797:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005547 ES:SE:LP:AF:ID  0.0401211:0.0274912:0.853872:0.005547:rs184270342