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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}
 

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-9981/UKB-b-9981_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9981/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9981/UKB-b-9981_data.vcf.gz ...
Read summary statistics for 9640623 SNPs.
Dropped 12802 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, 1288673 SNPs remain.
After merging with regression SNP LD, 1288673 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0593 (0.0025)
Lambda GC: 1.429
Mean Chi^2: 1.561
Intercept: 1.0349 (0.0093)
Ratio: 0.0623 (0.0166)
Analysis finished at Thu Oct 17 14:44:30 2019
Total time elapsed: 1.0m:26.38s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9494,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 42,
    "n_p_sig": 5539,
    "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": 152867,
    "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": 1288673,
    "ldsc_nsnp_merge_regression_ld": 1288673,
    "ldsc_observed_scale_h2_beta": 0.0593,
    "ldsc_observed_scale_h2_se": 0.0025,
    "ldsc_intercept_beta": 1.0349,
    "ldsc_intercept_se": 0.0093,
    "ldsc_lambda_gc": 1.429,
    "ldsc_mean_chisq": 1.561,
    "ldsc_ratio": 0.0622
}
 

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 9627883 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 9640623 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 8.626566e+00 5.750549e+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 7.883907e+07 5.629637e+07 828.0000000 3.255768e+07 6.943855e+07 1.145693e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.440000e-05 4.557900e-03 -0.0659692 -1.634100e-03 1.100000e-05 1.672100e-03 6.063750e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.276500e-03 2.876600e-03 0.0009892 1.202400e-03 1.969300e-03 4.423000e-03 5.196530e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.578908e-01 3.003850e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.578939e-01 3.003611e-01 0.0000000 1.868812e-01 4.434327e-01 7.183517e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.071601e-01 2.570528e-01 0.0014020 1.468500e-02 8.319800e-02 3.234990e-01 9.985980e-01 ▇▂▁▁▁
numeric AF_reference 152867 0.9841435 NA NA NA NA NA NA NA 2.094513e-01 2.486914e-01 0.0000000 1.277960e-02 1.036340e-01 3.256790e-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 0.0011895 0.0018199 0.5099998 0.5133859 0.623789 0.7821490 NA
1 54676 rs2462492 C T -0.0032429 0.0018025 0.0719996 0.0720006 0.400424 NA NA
1 86028 rs114608975 T C 0.0057984 0.0028813 0.0439997 0.0441770 0.103554 0.0277556 NA
1 91536 rs6702460 G T -0.0032866 0.0017748 0.0640000 0.0640534 0.456838 0.4207270 NA
1 234313 rs8179466 C T -0.0010835 0.0035019 0.7600007 0.7570232 0.074478 NA NA
1 534192 rs6680723 C T 0.0022329 0.0020277 0.2700001 0.2708088 0.240981 NA NA
1 546697 rs12025928 A G 0.0069976 0.0025291 0.0056999 0.0056598 0.913494 NA NA
1 693731 rs12238997 A G 0.0020539 0.0016987 0.2300001 0.2266290 0.116405 0.1417730 NA
1 705882 rs72631875 G A -0.0028879 0.0024890 0.2500000 0.2459417 0.067290 0.0315495 NA
1 706368 rs55727773 A G -0.0038092 0.0012586 0.0025000 0.0024740 0.515695 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0033063 0.0026430 0.2099999 0.2109484 0.041968 0.0473243 NA
22 51219766 rs182321900 C T -0.0022731 0.0123583 0.8499999 0.8540647 0.001924 NA NA
22 51220146 rs868950473 C T -0.0018760 0.0122392 0.8800001 0.8781778 0.001974 NA NA
22 51221190 rs369304721 G A 0.0032375 0.0026391 0.2200002 0.2199214 0.049732 NA NA
22 51221731 rs115055839 T C 0.0019665 0.0019735 0.3200000 0.3190301 0.073257 0.0625000 NA
22 51222100 rs114553188 G T 0.0013157 0.0023233 0.5700002 0.5711938 0.054455 0.0880591 NA
22 51223637 rs375798137 G A 0.0012358 0.0023344 0.5999997 0.5965555 0.054087 0.0788738 NA
22 51229805 rs9616985 T C 0.0019084 0.0019806 0.3400001 0.3352883 0.073088 0.0730831 NA
22 51232488 rs376461333 A G -0.0008448 0.0046655 0.8600001 0.8563068 0.020048 NA NA
22 51237063 rs3896457 T C -0.0027342 0.0012110 0.0239999 0.0239570 0.298039 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623789 ES:SE:LP:AF:ID  0.00118946:0.00181993:0.29243:0.623789:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400424 ES:SE:LP:AF:ID  -0.00324294:0.00180252:1.14267:0.400424:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103554 ES:SE:LP:AF:ID  0.00579841:0.00288133:1.35655:0.103554:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456838 ES:SE:LP:AF:ID  -0.00328657:0.00177479:1.19382:0.456838:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074478 ES:SE:LP:AF:ID  -0.00108347:0.00350193:0.119186:0.074478:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240981 ES:SE:LP:AF:ID  0.00223294:0.00202773:0.568636:0.240981:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913494 ES:SE:LP:AF:ID  0.00699765:0.00252909:2.24413:0.913494:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116405 ES:SE:LP:AF:ID  0.00205389:0.00169871:0.638272:0.116405:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06729  ES:SE:LP:AF:ID  -0.00288786:0.00248897:0.60206:0.06729:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515695 ES:SE:LP:AF:ID  -0.00380925:0.00125863:2.60206:0.515695:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033023 ES:SE:LP:AF:ID  -0.00361309:0.0031718:0.60206:0.033023:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036639 ES:SE:LP:AF:ID  -0.00213848:0.00288112:0.337242:0.036639:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036754 ES:SE:LP:AF:ID  -0.00224542:0.00287024:0.366532:0.036754:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036454 ES:SE:LP:AF:ID  -0.00237652:0.00289092:0.387216:0.036454:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016405 ES:SE:LP:AF:ID  0.00265871:0.0044525:0.259637:0.016405:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036999 ES:SE:LP:AF:ID  -0.00185769:0.00285867:0.283997:0.036999:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037093 ES:SE:LP:AF:ID  -0.0020763:0.00284899:0.327902:0.037093:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101187 ES:SE:LP:AF:ID  -0.000256775:0.00207652:0.0457575:0.101187:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959084 ES:SE:LP:AF:ID  0.00237705:0.00274809:0.408935:0.959084:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031451 ES:SE:LP:AF:ID  0.00534044:0.00498869:0.552842:0.031451:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053271 ES:SE:LP:AF:ID  -0.00441353:0.00396838:0.568636:0.053271:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036615 ES:SE:LP:AF:ID  -0.00205146:0.00286724:0.327902:0.036615:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036932 ES:SE:LP:AF:ID  -0.002033:0.00284124:0.327902:0.036932:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843128 ES:SE:LP:AF:ID  -0.001162:0.00147237:0.366532:0.843128:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055936 ES:SE:LP:AF:ID  0.0041427:0.00238398:1.08619:0.055936:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122381 ES:SE:LP:AF:ID  0.0023996:0.00161143:0.853872:0.122381:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025706 ES:SE:LP:AF:ID  0.000597427:0.00396484:0.0555173:0.025706:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121619 ES:SE:LP:AF:ID  0.00244139:0.00161215:0.886057:0.121619:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132453 ES:SE:LP:AF:ID  0.00075923:0.00158874:0.200659:0.132453:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011131 ES:SE:LP:AF:ID  -0.00685011:0.00577907:0.619789:0.011131:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005727 ES:SE:LP:AF:ID  -0.00720793:0.00743905:0.481486:0.005727:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002261 ES:SE:LP:AF:ID  0.00606666:0.0125692:0.200659:0.002261:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036846 ES:SE:LP:AF:ID  -0.00171103:0.00281254:0.267606:0.036846:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838819 ES:SE:LP:AF:ID  -0.00158506:0.00142578:0.568636:0.838819:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838448 ES:SE:LP:AF:ID  -0.00142656:0.00142423:0.49485:0.838448:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869683 ES:SE:LP:AF:ID  -0.0026015:0.00152824:1.05061:0.869683:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129969 ES:SE:LP:AF:ID  0.00245309:0.00153137:0.958607:0.129969:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037349 ES:SE:LP:AF:ID  -0.00199602:0.00276531:0.327902:0.037349:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037592 ES:SE:LP:AF:ID  -0.0019829:0.0027478:0.327902:0.037592:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869027 ES:SE:LP:AF:ID  -0.00249954:0.00152525:1:0.869027:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869125 ES:SE:LP:AF:ID  -0.00251743:0.00152585:1.00436:0.869125:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037551 ES:SE:LP:AF:ID  -0.00196996:0.0027597:0.318759:0.037551:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869029 ES:SE:LP:AF:ID  -0.00250364:0.00152522:1:0.869029:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005125 ES:SE:LP:AF:ID  0.00342703:0.00783086:0.180456:0.005125:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005091 ES:SE:LP:AF:ID  0.00322727:0.0078514:0.167491:0.005091:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83791  ES:SE:LP:AF:ID  -0.00148941:0.00142035:0.537602:0.83791:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037564 ES:SE:LP:AF:ID  -0.00200835:0.00276359:0.327902:0.037564:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83854  ES:SE:LP:AF:ID  -0.00149305:0.00142434:0.537602:0.83854:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  0.0057784:0.00497218:0.60206:0.013775:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.00554  ES:SE:LP:AF:ID  0.00846435:0.00767835:0.568636:0.00554:rs184270342