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-20379/UKB-b-20379_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20379/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20379/UKB-b-20379_data.vcf.gz ...
Read summary statistics for 9405107 SNPs.
Dropped 10939 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, 1288182 SNPs remain.
After merging with regression SNP LD, 1288182 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0634 (0.0036)
Lambda GC: 1.2517
Mean Chi^2: 1.3341
Intercept: 1.0245 (0.0088)
Ratio: 0.0733 (0.0262)
Analysis finished at Thu Oct 17 14:43:44 2019
Total time elapsed: 1.0m:37.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9489,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -6.0053e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 44,
    "n_p_sig": 1499,
    "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": 122244,
    "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": 1288182,
    "ldsc_nsnp_merge_regression_ld": 1288182,
    "ldsc_observed_scale_h2_beta": 0.0634,
    "ldsc_observed_scale_h2_se": 0.0036,
    "ldsc_intercept_beta": 1.0245,
    "ldsc_intercept_se": 0.0088,
    "ldsc_lambda_gc": 1.2517,
    "ldsc_mean_chisq": 1.3341,
    "ldsc_ratio": 0.0733
}

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 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 9394224 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 9405107 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 8.631124e+00 5.752819e+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 7.882960e+07 5.631002e+07 828.0000000 3.252350e+07 6.941392e+07 1.145592e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.000000e-06 5.170200e-03 -0.0732300 -1.927000e-03 2.100000e-06 1.917000e-03 7.579130e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.868600e-03 3.145800e-03 0.0012582 1.520400e-03 2.426200e-03 5.285700e-03 4.472000e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.727384e-01 2.966720e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.727381e-01 2.966472e-01 0.0000000 2.088296e-01 4.639922e-01 7.297783e-01 9.999997e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.117216e-01 2.575566e-01 0.0020310 1.658800e-02 8.954300e-02 3.318520e-01 9.979690e-01 ▇▂▁▁▁
numeric AF_reference 122244 0.9870024 NA NA NA NA NA NA NA 2.130519e-01 2.493110e-01 0.0000000 1.397760e-02 1.086260e-01 3.324680e-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 -0.0002055 0.0023189 0.9299999 0.9293899 0.623403 0.7821490 NA
1 54676 rs2462492 C T -0.0014897 0.0022926 0.5199996 0.5158303 0.400976 NA NA
1 86028 rs114608975 T C -0.0006472 0.0036794 0.8600001 0.8603722 0.103437 0.0277556 NA
1 91536 rs6702460 G T -0.0015147 0.0022588 0.5000000 0.5024851 0.457088 0.4207270 NA
1 234313 rs8179466 C T 0.0013839 0.0044610 0.7600007 0.7563963 0.074451 NA NA
1 534192 rs6680723 C T 0.0005972 0.0025818 0.8200001 0.8170856 0.241186 NA NA
1 546697 rs12025928 A G -0.0047453 0.0032212 0.1400000 0.1407091 0.913577 NA NA
1 693731 rs12238997 A G -0.0003295 0.0021604 0.8800001 0.8787864 0.116703 0.1417730 NA
1 705882 rs72631875 G A 0.0041754 0.0031723 0.1900002 0.1881047 0.067069 0.0315495 NA
1 706368 rs55727773 A G 0.0029464 0.0016021 0.0659994 0.0659070 0.515134 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0023816 0.0019376 0.2200002 0.2190292 0.137913 0.2052720 NA
22 51219387 rs9616832 T C -0.0025831 0.0025143 0.2999998 0.3042512 0.073612 0.0654952 NA
22 51219704 rs147475742 G A -0.0026743 0.0033694 0.4299995 0.4273675 0.041843 0.0473243 NA
22 51221190 rs369304721 G A -0.0047556 0.0033667 0.1600000 0.1577928 0.049574 NA NA
22 51221731 rs115055839 T C -0.0027080 0.0025152 0.2800000 0.2816497 0.073145 0.0625000 NA
22 51222100 rs114553188 G T -0.0017911 0.0029555 0.5400003 0.5445119 0.054643 0.0880591 NA
22 51223637 rs375798137 G A -0.0016625 0.0029696 0.5800000 0.5755916 0.054278 0.0788738 NA
22 51229805 rs9616985 T C -0.0024697 0.0025242 0.3300000 0.3278758 0.073012 0.0730831 NA
22 51232488 rs376461333 A G -0.0026316 0.0059394 0.6600001 0.6577124 0.020061 NA NA
22 51237063 rs3896457 T C -0.0031605 0.0015417 0.0400000 0.0403667 0.297860 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623403 ES:SE:LP:AF:ID  -0.000205487:0.00231894:0.0315171:0.623403:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400976 ES:SE:LP:AF:ID  -0.0014897:0.0022926:0.283997:0.400976:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103437 ES:SE:LP:AF:ID  -0.000647208:0.0036794:0.0655015:0.103437:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457088 ES:SE:LP:AF:ID  -0.00151469:0.00225876:0.30103:0.457088:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074451 ES:SE:LP:AF:ID  0.00138387:0.00446098:0.119186:0.074451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241186 ES:SE:LP:AF:ID  0.00059716:0.00258181:0.0861861:0.241186:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913577 ES:SE:LP:AF:ID  -0.00474527:0.00322116:0.853872:0.913577:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116703 ES:SE:LP:AF:ID  -0.000329484:0.00216044:0.0555173:0.116703:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067069 ES:SE:LP:AF:ID  0.00417535:0.00317226:0.721246:0.067069:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515134 ES:SE:LP:AF:ID  0.00294637:0.00160211:1.18046:0.515134:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03287  ES:SE:LP:AF:ID  -0.0009213:0.00404789:0.0861861:0.03287:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03645  ES:SE:LP:AF:ID  0.00049899:0.00367937:0.05061:0.03645:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036557 ES:SE:LP:AF:ID  0.000630985:0.00366625:0.0655015:0.036557:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036249 ES:SE:LP:AF:ID  0.00111431:0.00369329:0.119186:0.036249:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016355 ES:SE:LP:AF:ID  -0.00327094:0.00567694:0.251812:0.016355:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036782 ES:SE:LP:AF:ID  0.000657609:0.00365253:0.0655015:0.036782:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036873 ES:SE:LP:AF:ID  0.000729834:0.00364036:0.0757207:0.036873:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101076 ES:SE:LP:AF:ID  -0.0018775:0.00264501:0.318759:0.101076:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959309 ES:SE:LP:AF:ID  -0.00247385:0.00351045:0.318759:0.959309:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031432 ES:SE:LP:AF:ID  -0.00228761:0.00633213:0.142668:0.031432:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053418 ES:SE:LP:AF:ID  -0.0084246:0.00503944:1.02228:0.053418:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036416 ES:SE:LP:AF:ID  -1.65666e-06:0.00366166:-0:0.036416:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036745 ES:SE:LP:AF:ID  0.000133145:0.00362837:0.0132283:0.036745:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843032 ES:SE:LP:AF:ID  -0.000960197:0.00187495:0.21467:0.843032:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056041 ES:SE:LP:AF:ID  0.00118488:0.00303347:0.154902:0.056041:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122705 ES:SE:LP:AF:ID  -0.00121424:0.00204909:0.259637:0.122705:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025586 ES:SE:LP:AF:ID  0.00118495:0.00505895:0.091515:0.025586:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121928 ES:SE:LP:AF:ID  -0.00119579:0.00205001:0.251812:0.121928:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132582 ES:SE:LP:AF:ID  0.00037653:0.00202198:0.0705811:0.132582:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  -0.000784619:0.00735966:0.0362122:0.011132:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005771 ES:SE:LP:AF:ID  -0.0121632:0.00941391:0.69897:0.005771:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00224  ES:SE:LP:AF:ID  0.0187828:0.0160999:0.619789:0.00224:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036653 ES:SE:LP:AF:ID  -9.36335e-05:0.0035922:0.00877392:0.036653:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838725 ES:SE:LP:AF:ID  -0.000732744:0.00181485:0.161151:0.838725:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838352 ES:SE:LP:AF:ID  -0.000954427:0.00181306:0.221849:0.838352:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869399 ES:SE:LP:AF:ID  0.000462014:0.0019436:0.091515:0.869399:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130253 ES:SE:LP:AF:ID  -0.000166811:0.00194792:0.0315171:0.130253:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037121 ES:SE:LP:AF:ID  -0.000333022:0.00353284:0.0362122:0.037121:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037384 ES:SE:LP:AF:ID  -0.000694654:0.00350927:0.0757207:0.037384:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868732 ES:SE:LP:AF:ID  0.000168942:0.00194002:0.0315171:0.868732:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868802 ES:SE:LP:AF:ID  0.000187473:0.0019407:0.0362122:0.868802:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037334 ES:SE:LP:AF:ID  -0.000486322:0.00352485:0.05061:0.037334:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868732 ES:SE:LP:AF:ID  0.000170611:0.00193996:0.0315171:0.868732:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005082 ES:SE:LP:AF:ID  0.00850146:0.0100268:0.39794:0.005082:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005051 ES:SE:LP:AF:ID  0.00855335:0.0100506:0.408935:0.005051:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.8378   ES:SE:LP:AF:ID  -0.000904634:0.00180796:0.207608:0.8378:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037347 ES:SE:LP:AF:ID  -0.000591614:0.00353013:0.0604807:0.037347:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838436 ES:SE:LP:AF:ID  -0.000920458:0.00181304:0.21467:0.838436:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013889 ES:SE:LP:AF:ID  0.00110779:0.00630221:0.0655015:0.013889:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005567 ES:SE:LP:AF:ID  -0.0118267:0.00975576:0.638272:0.005567:rs184270342